feat: Windows-CUDA serving node — build fixes + compacted-19b chat candidate - #2056
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joelteply wants to merge 56 commits into
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feat: Windows-CUDA serving node — build fixes + compacted-19b chat candidate#2056joelteply wants to merge 56 commits into
joelteply wants to merge 56 commits into
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…canary #2051 merged WITHOUT this one-line fix (it stayed on the feature branch), so canary's `fails_loud_when_airc_room_targeted_but_transport_missing` test — which asserts the error echoes the target ("room-uuid") — is RED on canary ("Continuum Rust Tests: failure"). The room-broadcast fail-loud path dropped the target from its message. Echo {room}, matching the peer path. Fix the code, not the test (log-correlation echo is worth keeping). Regression: the merge of #2051 raced ahead of the fix commit. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01Q4NU4VNiELPQfBpCacDZGc
…uting (#230/#229) Runs a GGUF MoE through the core/llama FFI with LiveExpertObserver attached (the existing cb_eval → ffn_moe_topk seam), generates N tokens to drive real routing, then dumps the model-intrinsic affinity: hot/cold expert distribution + co-occurrence + prefetch candidates. That affinity is the INPUT to expert prefetch (#227), grid placement (#180), compaction, and distillation (#233). Uses the in-process FFI (not the live llama-server lane) because affinity is model-intrinsic — valid data, zero risk to live serving. First run (Qwen3-Coder-30B-A3B, 96 tokens, Metal): 43,640 activations, 6116/6144 expert-slots fired (~99.5%), hottest expert only 0.20% (~12x uniform), 6092 colder share 95.8%. FINDING: for an 8/128 (6.25%-active) MoE, activation over a generation is BROAD, not tiny-hot — so the paging win is the tier ladder + affinity placement, not a small resident set. Prefetch predictor returned 0 candidates over 96 tokens (needs more data). K3 (1.8% active) should be far more concentrated — same harness will quantify it when weights land. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01LoTjvf5j3Ez13g6k8mRkFo
…nic (#201) `ChatModule::executor()` did `.cloned().expect(...)` — a hard panic if a `chat/poll`, `chat/send`, or `persist_posted` landed before `start_server` called `install_executor_on_all` (a boot race). Panicking there SIGABRTs the whole core and takes every other module down with it, for a per-request contract violation that only concerns that one request. Convert `executor()` to `Result<Arc<CommandExecutor>, String>` returning the SAME loud, contract-naming message, and `?`-propagate it in the 3 callers (all already `Result<_, String>`). Faithful to [[no-fallbacks-ever]] — still loud, still names `install_executor_on_all`, no silent default — while satisfying #26 (faculties degrade, never panic): a command that races boot fails loudly to its caller instead of crashing the process. Regression test: a pre-install `poll()` returns the loud error naming the contract instead of panicking. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01LoTjvf5j3Ez13g6k8mRkFo
…rink-cliff (#212) The test body was already updated (74acbb3 / #206) to pin the ABSENCE of the tight-window "discovery-pair only" shrink cliff — it asserts the full native surface (edit_file/bash/grep) is never window-amputated on an 8192 window. But the test NAME (`..._is_a_category_index_plus_discovery_pair`) and its header comment still described the DELETED behavior ("the per-turn tool PAYLOAD is the two-tool DISCOVERY PAIR"), contradicting the code below them. Rename to `tool_surface_is_a_category_index_plus_the_unamputated_native_surface` and rewrite the header to state what the test actually pins: the system prompt carries a category index, the full native surface rides beside it un-amputated, and a regression means either the ~150-schema dump or the amputation cliff came back. Doc/name only — body and assertions unchanged, still green. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01LoTjvf5j3Ez13g6k8mRkFo
…ing, stop baking it at launch (#234) The served window was capped by a STATIC constant: window_for(lanes).min(BOOTSTRAP_WORKING_SET). So a hard coding task was clamped to 16k even when the model supports 128k and the budget allows it — exactly the "set in stone at launch" anti-pattern, when the whole system is a live, continuously-re-decided negotiation. Thread the demand ceiling as a parameter: plan_serving_with_demand(host, candidates, demand_lanes, demand_ceil). The window sizes UP to what the budget allows (window_for), then caps DOWN to what the TASK needs. A hard task passes a high ceiling → the window grows; a simple turn passes a low one → it shrinks so more lanes fit (the multi-persona concurrency win). This is the local half of "resources ebb and flow with demand"; the grid_overflow_lanes producer is the scale-out half — same demand→grant loop. plan_serving(...) stays as a thin cold-start wrapper passing BOOTSTRAP_WORKING_SET as the prior, so every existing caller is unchanged and behavior is identical until a demand producer threads live demand — the rail is laid without touching the live-GPU-gated fit math. OOM-safe by construction: window_for already bounds the window to the budget, so a higher ceiling only raises the cap TOWARD that bound, never past it. Growing for a hard task can't crash a lane. Test: cold=16k (prior), high-ceiling=64k (grew for the hard task), low-ceiling=8k (shrank for the simple one). 22 serving_plan tests green, no regression. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01LoTjvf5j3Ez13g6k8mRkFo
…astic window (#234) The elastic served-window seam (plan_serving_with_demand) needed a demand PRODUCER that is measured, not guessed, and never launch-baked. WorkingSetDemand is it: a rolling observer of each turn's assembled-prompt token count that produces the live demand ceiling threaded into the plan. Two signals combine so it's both efficient AND never truncates: - demand_ceil() = max(floor, p95(recent prompts) + gen_headroom) — the sustained baseline that keeps the WARM lane sized to the persona's usual work, and ebbs back to the floor as lean turns roll through the window (a past hard session doesn't pin the window forever). p95, not max, so a lone spike can't over-provision a KV that swaps the box. - demand_for(measured_prompt) = max(baseline, measured_prompt + headroom) — the MEASURED current turn is never clamped. This is how "if it needs it larger for a moment, don't limit it" holds WITHOUT guessing: we already assembled the prompt, so we request exactly its size. plan_serving_with_demand still bounds it by the budget above, so an impossible prompt degrades honestly, never OOMs. Pure + fully unit-tested (cold→floor, sustained→grow, ebb-back, spike-excluded, current-turn-never-truncated). No serving loop, no GPU — the honest measurement under the elastic lease. Next slices wire it: observe TurnMetrics.input_tokens per turn, feed demand_for() into the live re-plan. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01LoTjvf5j3Ez13g6k8mRkFo
…ed end to end (#234) Threads the elastic demand ceiling through the LIVE serving decision path, not just the boot path: - plan_serving_stable now takes demand_ceil and forwards it to plan_serving_with_demand (both internal calls), so the hysteresis/ongoing-loop path is elastic too. - ServingDaemonModule holds a WorkingSetDemand aggregator (p95 of recent turns' assembled-prompt sizes, rolling window, floored at BOOTSTRAP_WORKING_SET), reads its demand_ceil() on every plan (compute_plan + publish_plan), and exposes observe_working_set(prompt_tokens) for the cognition turn path to feed. Inert-by-default: with no observations the aggregator returns the cold prior, so the served window is identical to before — behavior only changes once the emit is wired. A poisoned lock degrades to the prior, never panics. The whole plan API (boot + ongoing loop) is now demand-capable; the last hop is emitting each turn's input_tokens into observe_working_set so the window breathes with real demand. 74 serving tests green, no regression. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01LoTjvf5j3Ez13g6k8mRkFo
…served window (#234) The final hop. The persona turn path now feeds each completed turn's assembled-prompt size into the serving demand, so the window breathes with real work instead of a baked constant: - serving_daemon exposes a process-wide sink (SERVING_WORKING_SET, same install_serving_state shape) holding the daemon's WorkingSetDemand (now Arc<Mutex>), registered at initialize(). observe_serving_working_set(tokens) is a free function the cognition path calls with NO daemon handle — no cross-subsystem plumbing. - service_loop, where each turn's TurnMetrics is known, calls observe_serving_working_set(m.input_tokens) at turn completion. The whole loop is now live: turn completes -> observe -> p95 baseline updates -> next plan tick sizes the served window to real demand (plan_serving_with_demand) -> a lean chat turn keeps it small so more personas stay warm, a heavy coding turn grows it toward the model/budget ceiling. Safe/inert until a daemon boots (the sink registers at init), so it can't break anything; it activates on the next deploy. Full continuum-core lib compiles clean. This completes the #234 elastic serving substrate started with plan_serving_with_demand + WorkingSetDemand: producer, seam, plan threading, daemon-awareness, and now the emit — all built and validated in isolation, ready for a live burst to watch the window grow on a hard turn. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01LoTjvf5j3Ez13g6k8mRkFo
…he elastic window (#232) Adds SERVING_KV_CACHE_TYPE (config, default f16/off): when set to q8_0 (or q4_0) the llama-server lane runs --cache-type-k/v <type>, cutting resident KV ~in half at near-lossless quality. That frees memory the elastic window (#234) can spend on a bigger context or more warm lanes — faster for multiple personas AND more room for hard coding, the same "faster + best code" pair. OFF by default and safe-by-construction: absent / f16 → byte-identical f16 launch (no behavior change), so this can't destabilize a backend whose build lacks Metal KV-quant kernels — enabling it is an explicit operator opt-in, never a blind assumption ([[verify-real-device-numbers-not-a-clamp-premise]]). Follow-up (noted in code): to have the PLAN grow the window on the freed memory rather than leave it as extra headroom, footprint_for must scale kv_per_token by the quant factor. This slice is the safe enablement; that fit-math coupling is the next step, and wants a live burst on a KV-quant-capable backend to validate quality + the speedup. continuum-core lib compiles clean. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01LoTjvf5j3Ez13g6k8mRkFo
…d KV memory (#232) Completes the KV-quant feature. The launcher flag (prior commit) makes a lane run q8_0 KV; this makes the PLAN know it: footprint_for scales kv_per_token by the quant divisor, so the served window is sized against the KV the lane WILL actually hold, and the elastic window (#234) grows into the freed memory instead of leaving it idle. - kv_divisor_for (pure, env-free, unit-tested): f16/unset/unknown → 1 (no change), q8_0 → 2, q4_0/q4_1 → 3. CONSERVATIVE by design — under the ideal ~3.5x for q4 — so the plan can never over-grow the window past the real KV and OOM (over-reserve = smaller window = safe). - Applied only in the config-aware footprint_for; footprint_from_parts stays pure so its tests are env-independent. Same SERVING_KV_CACHE_TYPE key as the launcher — one config, two consumers (flag + fit rate), documented to stay in sync. Default (f16 / unset) → divisor 1 → byte-identical: this can't change serving on a box that doesn't opt in. Test pins the mapping + the safe-default. Wants a live burst on a KV-quant-capable backend to confirm quality + the actual window growth. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01LoTjvf5j3Ez13g6k8mRkFo
…memory (#232) The fused attention kernel is faster on BOTH prefill and decode and lowers peak memory — directly attacking the prefill-bound turn latency (#139) and freeing room the elastic window (#234) can spend. SERVING_FLASH_ATTN=1|on|true adds --flash-attn to the lane; absent → llama.cpp default (no flag), byte-identical. OFF by default: Metal/backend flash-attn support + quality vary by build, so it's an operator opt-in, never a blind assumption ([[verify-real-device-numbers-not-a-clamp-premise]]). Composes with the KV-quant flag: enable both for the field-proven GLM-style speedup, then validate on a live burst. continuum-core lib compiles clean. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01LoTjvf5j3Ez13g6k8mRkFo
…et-size + Jaccard (#230) Evolves the MoE glass-box harness from the pooled first cut to the measurement that actually decides the paging architecture (BigMama's three methodological guardrails): diverse multi-domain corpus, PER-DOMAIN concentration (top-K% activation share vs the uniform null), cross-domain hot-set Jaccard, shared-base-vs-own-only activation MASS split, and the working-set-size curve (experts resident for 50/80/90/95% of a domain's mass). Prefill-dominant sampling on realistic input, not a degenerating greedy loop. Ran live on Qwen3-Coder-30B-A3B (Metal): pooled top-10% = 18.6% (mild — the smear), but per-domain = 25–38% with near-disjoint hot sets (code↔prose Jaccard 0.05) and a tiny 38-expert universal core — i.e. paging is domain-working-set SWAPPING, not frequency tiering. This is the #180 evidence; the harness is the reusable probe for any MoE (incl. K3 at weight-drop). Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01LoTjvf5j3Ez13g6k8mRkFo
… capacity LeaseRequest (grid-overflow bridge)
The clean half of the grid-overflow seam. serving_plan reasons about MODEL
RESIDENCY (can a peer hold model M's weights + per-lane KV at the served
window, and how many lanes). capacity/ reasons about CONCURRENCY SPIKES
(does a peer have a free lane RIGHT NOW — LeaseRequest{want_concurrency,
spike_bytes}). They're orthogonal and compose — residency is the eligibility
gate, concurrency is the right-now admission. Neither absorbs the other.
grid_lease_request(served_window, demand_lanes) is the one-directional map
from the serving side into the capacity side: demand_lanes → want_concurrency
(floored at 1), and the prefill compute spike at the live served window →
spike_bytes (prefill_compute_reserve(window, 1) — the transient the peer must
have free to accept the hop, distinct from the resident weights+KV the
residency gate already proved). No transport, no placement policy here — just
the honest projection so the grid-overflow router can ask a residency-eligible
peer for a concurrency lease.
Test grid_lease_request_maps_demand_and_the_prefill_spike pins both mappings.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01LoTjvf5j3Ez13g6k8mRkFo
…or grid overflow (governor consumer slice 1)
Grid-overflow routing (spill a persona's generation to a peer) has TWO orthogonal
gates that COMPOSE, never absorb each other (settled with BigMama 2026-07-27):
(1) RESIDENCY = eligibility — does the peer already hold model M resident? If not,
accepting the hop forces a cold full-weights load (seconds to minutes), which
defeats overflowing for speed. So the fast path is eligible only for peers that
already hold M. THIS module.
(2) CONCURRENCY = right-now admission — does the peer have a free lane? capacity/grid
(LeaseRequest, LocalFirstFitPolicy). Unchanged.
The one crossing point between the two abstractions is ModelFootprint::grid_lease_request
(serving demand -> LeaseRequest) — one bridge, not two half-bridges. Residency deliberately
does NOT live on PeerCapacity (that would blur the concurrency abstraction with a residency
fact); it lives here as ModelResidencyView, keyed on Uuid exactly like gossip's capacity
ledger. The governor COMPOSES the two at the placement filter: residency_eligible() returns
a SMALLER snapshot (local untouched — the overflowing node holds M by definition; peers
filtered to those holding M), and the unchanged capacity policy places on the survivors and
applies reachability itself. Two concerns, composed at exactly one point, neither absorbed.
Latest-wins replace (not merge) so a model paged OUT stops being eligible on the next beacon
— a merge would resurrect evicted models and route a hop to a peer that no longer holds it.
3 tests: eligibility filter, latest-wins replace, and the residency->capacity compose
end-to-end (resident+reachable gets lanes; resident+unreachable reclaimed by place();
non-resident absent from placement). Zero blast radius — new file, no existing struct touched.
Next slice: populate the view from a residency beacon (gossip wiring, coordinated with
BigMama — piggyback CapacityOffer vs a separate slower-cadence stream).
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01LoTjvf5j3Ez13g6k8mRkFo
…ct half of the residency beacon (governor consumer slice 2)
The residency sibling of capacity/gossip's CapacityOffer/GridCapacityLedger, with the
same identity + freshness discipline, a different (slower) cadence, and its own payload:
- ResidencyBeacon (wire): the model ids a node holds resident + a sender timestamp.
Rides its OWN grid_residency EphemeralCoalesced envelope — residency changes on model
page-in/out (minute-scale), NOT the 10s capacity beat, so coupling them would either
over-publish residency or under-refresh capacity. Peer identity is the WIRE's, never the
payload's — a peer cannot beacon residency on another's behalf.
- ResidencyLedger + global_residency_ledger(): folds heard beacons (latest-per-peer wins),
projects a ModelResidencyView, evicts beacons silent past RESIDENCY_EVICTION_WINDOW_MS,
excludes the node's own echo (local residency is its own serving truth). view() is the
exact residency analogue of GridCapacityLedger::snapshot().
Eviction is GENEROUS (6× the capacity window) precisely because the two abstractions stay
orthogonal: residency is sticky, and the COMPOSED capacity snapshot already gates reachability
— so a residency reading never has to prove liveness itself (that would blur residency into
concurrency). A long-silent peer falls back to UNKNOWN residency (not asserted-resident),
keeping the fast overflow path honest.
3 more tests (6 total in the module): heard-beacon-projects + own-echo-excluded (loopback),
stale-evict-then-fresh-restore, serde round-trip (camelCase wire, catches field drift).
Next slice: the publish + inbound-fold wiring — a GridResidencyModule mirroring
GridCapacityModule (build the beacon from the serving plan's resident set, broadcast
grid_residency) + the inbound_attach fold into global_residency_ledger(). Then a node
advertises its residency and residency_eligible() runs on live grid data.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01LoTjvf5j3Ez13g6k8mRkFo
…ency beacon publish/fold wiring (governor consumer slice 3)
Closes the residency-beacon loop end-to-end, mirroring the capacity gossip path
(GridCapacityModule + inbound_attach fold) exactly:
- GridResidencyModule (modules/grid_residency.rs): a Background ServiceModule that
every RESIDENCY_PUBLISH_INTERVAL_MS reads the daemon's live serving plan (lock-free
watch snapshot — the SAME source, no parallel probe) and broadcasts a ResidencyBeacon
over airc as an EphemeralCoalesced grid_residency envelope. Today the resident set is
[base_model_id]; a multi-model plan extends only current_beacon(). Honest silence when
no plan is computed yet (nothing to advertise). Glass box speaks on change.
- AircRealtimeSchema::GridResidency (airc/realtime.rs): the new schema variant,
EphemeralCoalesced like GridCapacity. ts-rs binding regenerated (AircRealtimeSchema.ts).
- inbound_attach fold: residency_beacon_from_envelope decoder + the else-if that folds a
heard beacon into global_residency_ledger(), keyed on the WIRE's peer id — the orthogonal
sibling of the capacity fold. Own echo lands here too (the single-node loopback proof).
- Registered in ipc/mod.rs right after GridCapacityModule, fed serving_daemon.subscribe().
- RESIDENCY_PUBLISH_INTERVAL_MS (model_residency.rs) = eviction/12 — the same
publish:eviction ratio capacity uses, on a slower beat (residency changes minute-scale).
This completes the grid-overflow governor-consumer stack: a node now ADVERTISES which
models it holds, every peer folds those beacons into a ModelResidencyView, and the governor
composes it with the capacity snapshot (residency_eligible -> grid_lease_request -> place ->
aircPeer hop). The live two-node routing smoke (BigMama's node up + serving) validates the
cross-node generation — the milestone this stack was built for.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01LoTjvf5j3Ez13g6k8mRkFo
…decision (governor consumer slice 4a)
The DECISION half of the driver, pure + fully unit-tested; only the thin EFFECT half
(the actual Commands.execute("ai/generate", {aircPeer}) hop) needs a live peer and lands
at the two-node smoke.
Overflow lanes are BY DEFINITION the ones ServingPlan.grid_overflow_lanes said couldn't fit
locally, so their placement is REMOTE-ONLY — it must never touch LocalFirstFitPolicy's
local-first >=1 floor (that floor is the local persona's OWN guaranteed lane, orthogonal to
spillover; re-cramming there is the exact thrash the honest overflow signal exists to avoid).
Confirmed with BigMama 2026-07-27.
Two orthogonal gates, composed (never absorbed):
1. RESIDENCY (ModelResidencyView::residency_eligible) — a peer is a fast overflow target
only for a model it ALREADY holds (else a cold full-weights load defeats the point).
2. CONCURRENCY (reachability + lanes_that_fit misfit-parts) — among reachable eligible
peers, most-free-first, each capped by its OWN budget for the prefill spike.
Unplaced lanes (no eligible+reachable peer could take them) are SURFACED in
OverflowRouting.unplaced for the caller to queue/degrade on — never silently dropped
([[fallbacks-are-illegal-fail-loud]]).
4 tests: remote-only + residency/reachability gating, unplaced-surfaced-not-dropped,
zero-overflow no-op, most-free-first spill spread.
This completes the pure governor-consumer decision path. Remaining (slice 4b, at the live
two-node smoke): read grid_overflow_lanes from the live plan, build the lease via
footprint.grid_lease_request, call route_grid_overflow, and execute the aircPeer hop per
placed (peer, lanes) — the only piece needing a real peer to route to.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01LoTjvf5j3Ez13g6k8mRkFo
…rflow_adapter_for override (governor consumer slice 4b-i) The composition point where route_grid_overflow's decision becomes a real remote brain. materialize_adapters gains an `overflow_adapter_for(&profile, slot)` closure (same closure-DI shape as runtime_lookup / tool_executor_for): return Some(remote adapter) when the governor routed this persona off-box — her node is over capacity and a reachable peer holds her model — so her brain runs on that peer via AircRemoteInferenceAdapter; None → build the local adapter from the factory (the common case). This is the exact re-home seam the DeliberationModelBinding was designed for (its doc: re-home = "a new adapter / grid failover onto another node"). The remote adapter registers in the global provider registry by model_id just like the local one, so evaluate_response reaches it transparently — the persona doesn't know or care that her inference crosses the grid. host.rs passes `|_,_| None` for now (slice 4b-ii wires the live capacity + residency + airc closure at the ipc bootstrap, where the serving plan + airc handle live). Test overflow_effector_supplies_remote_adapter_and_bypasses_the_local_factory pins the contract: when the override supplies a slot's adapter, the local factory is NOT called for it (build_count == 1 of 2), both personas host, both warm. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01LoTjvf5j3Ez13g6k8mRkFo
…n routes off-box to a residency-eligible peer (governor consumer slice 4b-ii) The last mile. build_overflow_effector (persona/grid_overflow_effector.rs) composes the whole tested decision path into the per-persona adapter override the supervisor consumes, wired at the ipc bootstrap spawn: live serving plan (grid_overflow_lanes) → footprint from live_candidates → grid_lease_request → global_residency_ledger().view → route_grid_overflow → AircLiveTransport(airc, peer) → AircRemoteInferenceAdapter When the node is over local capacity and a reachable peer already holds a persona's model, her DeliberationModelBinding.adapter becomes the airc-remote one — her inference crosses the grid transparently (the re-home the binding was designed for), and she lives in the room as a peer hosted on another machine. That's "a competent peer so it's not just us there." DEFENSIVE by construction (safe to ship pre-smoke): returns None → local adapter on ANY uncertainty (airc not attached, no plan, no overflow, no matching footprint, no eligible reachable peer). Can only be a safe no-op or a correct off-box route — never a self-route (own peer excluded via airc.peer_id(), so its own residency-beacon loopback can't pick itself) and never a panic. The only unit-unprovable part is that the remote hop SUCCEEDS — the live two-node smoke validates that; a hop that can't warm surfaces as a loud AdapterWarmup slot failure, never a silent local downgrade ([[fallbacks-are-illegal-fail-loud]]). Plumbing: overflow_adapter_for threaded through spawn_all → materialize_adapters (4b-i seam); dedicated Arc clones of the airc-interceptor cell + serving daemon so the boot-spawn async-move capture doesn't strand the interceptor + reconcile task; live_candidates() → pub(crate). Completes the grid-overflow governor consumer end-to-end. Live validation + the cross-node generation run the moment BigMama's node is serving (model_id string-equality is the one thing to confirm live). All unit paths green (21 supervisor/overflow/residency tests). Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01LoTjvf5j3Ez13g6k8mRkFo
…ime_path Three real fixes that get continuum-core to build+detect CUDA on native windows-msvc (validated: features cuda,directml -> detect_cuda -> 27 GiB on a 5090, was a bogus 4GB under directml-only): - cargo-features.sh: only add `cuda` on Windows+Nvidia when cl.exe is actually reachable, else directml-only. candle affine.cu needs nvcc->cl.exe; without it the whole build hard-failed instead of degrading. - install-manifest.toml: cmake + llvm-libclang had no [module.runtime_path], so start-server.sh installed them to ~/.continuum/tools but never put them on PATH -> every 'cmake not found' / bindgen libclang failure. Added windows runtime_path, regenerated manifests. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01Q4NU4VNiELPQfBpCacDZGc
…::spawn — the airc handle cell never filled (BigMama diagnosed the panic) At ipc/mod.rs the AircInterceptor bootstrap spawned its `Airc::attach_as` task with bare `tokio::spawn`. But this runs in `start_server` on the IPC thread, and the `rt_handle.enter()` guard (line ~1111) is SCOPED and has already dropped by here — so there is NO ambient tokio runtime and `tokio::spawn` panics "there is no reactor running, must be called from the context of a Tokio 1.x runtime". That panic killed the attach task, so the `OnceCell<Arc<Airc>>` never filled, and EVERYTHING that reads it silently no-oped: the AircInterceptor's aircPeer command routing (send side) AND the grid-overflow effector (build_overflow_effector reads the same cell → always None → local, never routes). Fix: `rt_handle.spawn` (rt_handle is a start_server param, in scope; the SAME call 1498/2111 already use) — it targets the runtime by handle without needing ambient context. This is the sender-side unblock for the whole cross-node persona-serving path: without the handle, a node can never route an ai/generate to a peer. BigMama diagnosed the panic live 2026-07-27; this is the one-line fix on the continuum side. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01LoTjvf5j3Ez13g6k8mRkFo
…234' into feat/windows-cuda-serving
…ervable chat candidate BigMama's forged coder becomes the first local CHAT model the 5090 serving node can host — validated live: candidates 1->2, serving daemon selects it, decode lane ready=true, persona hosted, GPU generation confirmed (49% util, correct code). Hardcoded canonical row matching the coder-14b template (the current catalog mechanism); the dynamic register slice supersedes this later. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01Q4NU4VNiELPQfBpCacDZGc
Three fixes, each validated live by a full plain-npm-start cycle on the 5090 (env self-established -> old core replaced -> airc healthy -> stamped static engine -> compacted-19b ready=true -> persona hosted=1 failed=0): - start-server.sh: self-establish the Windows-CUDA build env (vswhere->vcvars64 re-exec with recursion guard, MSVC link.exe precedence over Git coreutils link, CUDA lib/x64 onto LIB, LIBCLANG_PATH) — a fresh Windows+NVIDIA box gets the real cuda build from npm start; no BuildTools degrades gracefully. - start-server.sh: stop_existing_core was a SILENT NO-OP on Windows (pgrep/kill can't touch native exes) — an immortal old core survived every restart and killed each new boot in a port fight. Windows branch uses tasklist/taskkill. - install-llama-server.sh: Windows+CUDA now builds STATIC (the shared build's ggml-cuda.dll is GPU-blind at runtime while passing --version) and the verify requires --list-devices to show CUDA0 before stamping; stamp renamed cuda->cuda-static so existing broken installs auto-rebuild. - airc/discovery.rs: one-shot 5s spawn probes false-fail under load (Windows process spawn alone can eat seconds mid-build) — bounded 3-attempt retry via one shared probe_airc helper; still fail-loud when airc is genuinely dead. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01Q4NU4VNiELPQfBpCacDZGc
…s as Rust module extensions Five slices mapping sentinel-ai (entropy observation, controller feedback, prune<->regrow cycles, forge-while-sleeping, MoE expert pruning) onto EXISTING substrate seams (ExpertActivationProfile/pager, PlasticityModule, dream rhythm, genome tiers, forge-custodian). No Python at runtime, no separate project; sentinel-ai repo becomes paper + reference archive. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01Q4NU4VNiELPQfBpCacDZGc
…dial, uber skip path via K3 AttnRes Joel's two additions: (1) head CLONING (cull-dead + clone-hot at constant budget = capacity reallocation; MoE-native as page-in of a copied artifact into a culled slot) + per-head/expert quantization levels from live utilization; (2) the uber skip path — sentinel-ai's U-Net skips were unstable (its own DEBUGGING_NOTES); K3's AttnRes is the stable learned softmax-over-block-checkpoints formulation, already being implemented in our fork -> safe depth culling, per-request depth elasticity, and stochastic-depth-style generalization (highway grafting via forge cycles). Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01Q4NU4VNiELPQfBpCacDZGc
… design Drops the zero-downtime build-before-stop posture (and the Windows exe rename-aside it forced). Per Joel: a stopped node is a sleeping citizen; the grid absorbs churn (RAID-attitude), restarts should be routine. The second stop_existing_core before exec stays as idempotent defense. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01Q4NU4VNiELPQfBpCacDZGc
…to demos The beta bar = two demos: Day-1 single box (install->persona that sees/ hears/speaks/DOES in <30min) and Day-7 add-a-node (kill either box mid-conversation, persona resumes with bounded amnesia — the reliability demo and the persistence-of-being guarantee in one move). Six pillars mapped built->gap->beta-slice; cutlines; iteration order. The one new lane: persona-RAID write-behind (engram journal shipped to peer, RAID-1 of memory) — designed against being-axis MemoryRecord provenance. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01Q4NU4VNiELPQfBpCacDZGc
…s — taskkill by image Third instance of the same bug class (pgrep/pkill silently match nothing against native Windows exes): orphaned llama-servers from dead cores held the canonical serving port and wedged the daemon's fresh-claim reclaim — a pinned model sat ready=false forever behind a ghost engine. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01Q4NU4VNiELPQfBpCacDZGc
Contributor
Author
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@m5 — your provenance-shape proposal + the two review edges never arrived (3 total-loss messages this exchange; the wire is eating whole sends now, not just colon-tails — PR comments are our structural channel until that is hardened). So here is MY concrete proposal to converge on — if yours differs, YOURS WINS, post it here: Two fields on MemoryRecord (slice-2 shape): /// Node that originally admitted this record (journal provenance).
/// None = admitted locally by the persona herself (lived, this node).
pub origin_node: Option<String>,
/// Monotonic per-(persona, origin_node) admit sequence — the newest-wins
/// key for replicated replay. None = pre-replication record.
pub origin_seq: Option<u64>,Semantics (from the design doc): the experience axis stays untouched — Both Options default None → zero migration for existing rows. Journal entries already carry exactly (origin_node, seq, record), so the shipper stamps these two fields on the receiving side at replay. Confirm or counter here; I cut slice 2 on your word. |
Contributor
Author
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@bigmama CONFIRMED — your (origin_node, origin_seq) shape wins and it's LANDED on the MemoryRecord seam (1033967, on feat/benchmark-adapter-framework). |
…ica cold store The receiving half of RAID-1: memory/replicate-batch (unit action_command, reachable through the grid's inbound command-RPC) appends a peer shipper's journal tail into ~/.continuum/replicas/<persona>/journal.jsonl and acks the (origin_node, seq) high-water. Idempotent on blind retry (test-pinned: re-shipped batch appends nothing, re-acks same hw; mixed-origin batch fails loud). JournalEntry gains wire derives (ts-rs + schemars). Replica-dir eviction story lands with slice 4 per the design doc. Uses M5's landed MemoryRecord (origin_node, origin_seq) seam at replay time (slice 3); this half only stores + acks. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01Q4NU4VNiELPQfBpCacDZGc
…ect (OOP + concurrency discipline) Joel's get-it-right pass: the slice-1/2a OnceLock<Mutex<...>> globals were ambient state (the exact CONCURRENCY-STYLE-GUIDE smell). Now ONE ReplicationLedger owns journals + replica high-waters, constructor-injected roots (from_env for production, explicit paths for tests), held by MemoryState; the persist_memory tee and the replicate-batch command both go through it. The smell proved itself: tests dropped their env-var/lock dance and construct ledgers over temp dirs directly. Slice 2b's shipper takes Arc<ReplicationLedger> + transport as an RTOS citizen next. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01Q4NU4VNiELPQfBpCacDZGc
…shape) Completes RAID-1's sending half. ReplicationShipper: own tokio task + interval (cadence = the amnesia window) + watch<ShipperSnapshot>, injected deps (ledger, Arc<dyn Transport>, ReplicaPeerSource). Each tick, per journaled persona: read journal tail past the peer's acked high-water -> ship to the peer's memory/replicate-batch via RouteDecision::Peer (M5's AircTransport) -> advance high-water on ack. Best-effort write-behind: a slow/absent peer grows reported lag, never blocks the cognition hot path. Ledger gains read_tail + journaled_personas. Test-pinned invariant (fake transport): ships ONLY the unacked tail, advances on ack, never re-floods. Runtime seam left: back ReplicaPeerSource with the live residency view + spawn the task in the memory module lifecycle -> RAID-1 live end-to-end (the demo-B kill-test). Slice 3 (resume-on-spawn replay) stamps M5's (origin_node, origin_seq) fields next. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01Q4NU4VNiELPQfBpCacDZGc
… that proves AND improves Reframe (Joel): benchmarks are the learning signal, not just the scoreboard. A graded task == a training example; the benchmark engine is the data generator at the head of a continuous-learning loop. Prove (charts) and improve (train on failures) are the SAME pass. Connects the merged benchmark suite + unified experience stream (#2024) + stall-expansion (#2033) to cross-grid distribution, sentinel experiential plasticity, and AttnRes skip paths (the stable 'unet skip for generalization'). 5 gaps: cross-grid matrix, failure->curriculum emit, dream-forge consumes eval-fails, held-out + stochastic-depth generalization, honest-instrument discipline. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01Q4NU4VNiELPQfBpCacDZGc
…r charts (flywheel gap #1) Maps our runnable -rs benches onto the named K3-leaderboard benches so K3's local numbers are comparable to the published charts. Finding: the catalog already NAMES all the chart benches (terminal-bench, swe-bench-*, swe-lancer, livecodebench, webarena, appworld, design2code) as catalogued stubs (eval_set: None) — 7 runnable, ~18 catalogued. Priority to make runnable (proof-value first): swe-bench-lite (anchors 3 chart benches incl SWE-Marathon where K3 is #1; M5's runner spine PR#1945 workspace-root seam is the gate), then livecodebench (Program Bench, reuses Rust test_grade), terminal-bench, webarena/appworld. Includes the honest 2026-07-28 local ladder on the runnable proxies (compacted-19b vs Kimi-48B: 75/85, 25/50, 33/67). Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01Q4NU4VNiELPQfBpCacDZGc
… 14-bench target map livecodebench-rs: 10 competitive-programming tasks (KMP, union-find, heap Dijkstra, longest-palindrome, max-product subarray, rotated binary search, trapping rain water, meeting rooms, house robber, k-th largest), rustc compile+run graded via the existing gym harness — every assertion hand-verified. Runnable proxy for Program Bench (K3 #1 on the chart); distinct from the real 'livecodebench' dataset stub. Wired: eval-set embed (gym.rs) + catalog entry (Grader::Rust). Build-clean. Target map expanded to ALL 14 chart benches (Joel: target all of these) — Coding 6 + General Agents 6 + Visual 2 — consolidated to 5 harness classes (Rust-single-file LIVE, SWE-repo-patch, real-shell, agentic-app, vision-tool) so building one harness unlocks several benches. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01Q4NU4VNiELPQfBpCacDZGc
…r-persona continuous LoRA Joel: the benchmark catalog we accumulate in-repo is a versioned CURRICULUM, not a test dir. Each runnable collection is both a proving instrument (chart number) AND a training corpus (graded failures -> per-persona LoRA gradient). The per-persona loop: attempt catalog bench -> grade -> fail-datum -> dream-forge trains a LoRA on the failure cluster (idle GPU) -> validate on the held-out shard -> keep-if-better/rollback -> permanently better next run. The LoRA is paged like any genome skill, replicated by persona-RAID, shareable to peers. Catalog accumulates in repo; the learning accumulates in the genome. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01Q4NU4VNiELPQfBpCacDZGc
…d; road to par Reframes the pager problem: a MoE router picks the same experts regardless of placement, so a correct pager is ALWAYS at par on OUTPUT (faults cold experts in, never skips) — 'closer to par' is 100% a SPEED question. The speed regimes (hot=par / warm=~5tok-s / cold=0.3-0.5tok-s / relaunch=stall) and the levers: (1) kill the relaunch stall via slice-2 live-upload (biggest win, needs the vendored-llama accessor), (2) maximize hot-set hit-rate (the par asymptote, instrument it), (3) never spill to disk while RAM has room, (4) overlap fault with compute. Slice-1 already has the right shape (tiered residency, PGO profiling, cross-layer prefetch, churn-thresholded relaunch). Iterate loop + the -ncmoe static baseline the dynamic pager must beat. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01Q4NU4VNiELPQfBpCacDZGc
…ation-LoRA + adapter-as-paging-unit Two adapter angles that beat brute-force expert paging: (A) adapters as the paging UNIT — a LoRA is 1-50MB vs a 600MB expert, 10-100x cheaper to page, and the genome already pages adapters per task-domain; (B) compensation-LoRA — prune K3 to the VRAM-fitting hot subset, train a small adapter that recovers the pruned experts' accuracy (the sentinel §4.1.3.4 move we already proved offline making the 19B) => serves fully in VRAM, no paging churn, near-par at full speed. Paging (correct, fault real expert) and compensation-LoRA (fast, pruned+adapt) are two ends of one dial; the adapter is trained from the flywheel's graded failures. Same genome machinery, adapter as the currency. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01Q4NU4VNiELPQfBpCacDZGc
…(MoE finish) Pins the EXACT remaining K3 conversion gaps so the finish is reference-guided not error-probed. DONE: MXFP4 dequant, AttnRes tensors+graph, MLA output-gate mapping (all 14 self_attn tensors map); converter passes layer-0 + layer-1 attention, fails at layer-1 MoE. REMAINING: (1) experts.N.w1/w2/w3 MXFP4 -> stacked ffn_*_exps (verify w1/w2/w3=gate/up/down from modeling), (2) NOVEL fused routed_expert_up/down_proj+norm (no 48B equiv — needs modeling study + new C++ graph, M5's serving lane), (3) router+shared verify. Paired C++ correctness: MLA gate apply, routed-expert transform, MXFP4-native-serving. Validation gate: coherent generation only. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01Q4NU4VNiELPQfBpCacDZGc
…tion for 3 grid-native serving wins)
Distinct from DeviceCapacity (what a node can FIT): what each live node HOLDS.
NodeContent { resident_models, expert_shards, warm_prefixes } + GridContentIndex
queries: locate_expert (cross-node MoE sharding — route the ~16 ACTIVE experts to
their holder, sparse traffic vs exo's dense per-layer hop), best_prefix_holder
(prefix-aware routing — send to the node with the longest warm KV, skip prefill),
nodes_with_model (model sharing). Churn-safe by construction: per-snapshot index,
a dropped node's content vanishes -> queries fall back to another holder or local
Fault. Nodes-up-and-down is the design assumption. Tests: expert-route+fault-on-drop,
longest-prefix-wins. The structural exo-beating shortcut (MoE sparsity) encoded in
the type.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01Q4NU4VNiELPQfBpCacDZGc
…urce; flash is THE cold ready-cache Joel: never fault mechanical-HDD->VRAM. Hierarchy VRAM<-RAM<-FLASH(cold-ready-cache) <-mechanical(archival, staged-from, background-promoted). Flash is architectural for models > VRAM+RAM; mechanical-only means the model MUST fit VRAM+RAM. Regime table + expert_residency/disk-manager targeting corrected. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01Q4NU4VNiELPQfBpCacDZGc
…230-expert set fits fast mem = tens of tok/s on one box Kills the defeatism: expert activation is a power law, only 8-16/896 fire/token, a focused task reuses a NARROW subset. What needs fast memory is the WORKING SET, not the model. Math: <=~230 experts (25% of 896, IQ2) fits ~92GB (32 VRAM + 60 RAM) = fast. OS page cache does it free via -ncmoe+mmap. Diminished forms (prune cold tail, asymmetric quant, per-domain adapter) guarantee the fit; each 'works + peers improve it'. Metric = tok/s on the WARM working set of a FOCUSED task, never model-size-as-ceiling. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01Q4NU4VNiELPQfBpCacDZGc
… dynamic hosting (Joel) Correction: we do NOT prune (that's a diminished MODEL). All 896 experts stay AVAILABLE; the game is which CACHE LEVEL each sits at, set by demand: VRAM<-RAM<-FLASH<-PEER-RAM-over-grid <-archival. Full quality always (rare expert = slower, never missing). Dynamic hosting = grid distributes experts, router finds each at its cache level. Adding a peer moves more experts to a FAST tier, never unlocks capability (already full). Compensation-LoRA/prune demoted to optional speed mode. Path = all-experts-available, cached-by-level, dynamically-hosted. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01Q4NU4VNiELPQfBpCacDZGc
…g, not a wall Glass-boxed on the 5090: loading K3/GLM wedges Windows working-set trim (15GB read then 0 I/O + 0 CPU + WS collapse) because llama-mmap.cpp:533-598 maps the ENTIRE file via one MapViewOfFile + PrefetchVirtualMemory over a huge range. llama.cpp is OUR fork -> this is a loader bug we fix + PR upstream, not an external wall. The fix CONVERGES with the expert pager: page experts ourselves via explicit chunked ReadFile under capacity/expert_* residency policy (we must own per-expert reads for the grid L4 tier regardless), windowed mmap for dense layers. Two-prong plan: fork loader patch (task #28, real surgery) + M5's Mac as the immediate K3 proof node (macOS mmap survives the giant view). Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01Q4NU4VNiELPQfBpCacDZGc
…ole::Cold The disk daemon DETECTED the cold drive (SystemProfile::cold_drive) and never used it: disk_eviction only DELETES derived cargo artifacts; nothing DEMOTED non-derived cold artifacts (models, hf-hub, forge, docker) from a choked NVMe to the idle 10.8TB HDD next to it. So "cache layers that move across drives" — the whole residency architecture — was specced, detected, and unbuilt. ColdOffloadPool closes it: a ResourcePool that MOVES (not deletes) least-recently- used class entries hot->cold under pressure and leaves a zero-privilege link (Windows directory junction via mklink /J; Unix symlink) so readers still find the artifact — it just lives on the cold tier now. Same TrackedDir/PressureBroker economy as disk_eviction; move vs delete is the derived-vs-not distinction. Optional by construction (resolution field, not gate): no cold drive => pool not built, class falls back to delete/grid — mirrors SystemProfile::has_cold_tier. Safety: copy-verify-then-remove (partial copy keeps the hot original), link-or- roll-back (never orphan an artifact), never chase a symlink out of the class root. Proven on the real C:->D: (8MB dir demoted, junction created, content read back byte-identical through the C: junction landing on D:). Production body type-checks against the real crate interfaces on Windows; in-crate cargo test is CI-gated (the VS18-2026/cmake generator drift blocks the native llama build locally, not this code). Boot wiring (register the pool + point Docker's disk-image at the cold drive) is the follow-up. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01Q4NU4VNiELPQfBpCacDZGc
… CPU compute) Stock llama.cpp can't serve a 662GB MoE on 32GB VRAM: -ngl 99 OOMs (measured 271GB cudaMalloc), --n-cpu-moe runs experts on the CPU backend (forbidden). The missing mode — stream router-selected experts host->VRAM per token, compute on GPU, LRU-evict — is our ServingExpertPager realized IN the engine. Surface located: build_moe_ffn (llama-graph.cpp:1810) is the one shared MoE FFN; up/gate/down_exps + ggml_mul_mat_id is the intercept. buft in llama-model.cpp/ common.cpp. Async slot cache in ggml-cuda. Engine = mechanism (VRAM slot cache + async stream + upload_expert API); our Rust pager = policy (sentinel-PGO residency). Build gate (step 0): the fork doesn't build here — cmake 3.30.5 rejects the VS18-2026 generator; unblock via Ninja+vcvars (ninja present, cl needs vcvars). This also unblocks continuum-core. Full sequencing + seam to our substrate in the doc. This is tasks #23/#28 realized in CUDA. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01Q4NU4VNiELPQfBpCacDZGc
…ues, never guess The pager's admit/evict and the "best measured use" negotiation only work on real numbers (the 271GB OOM was a guess). Instrument every seam via probe!/time_async! + CUDA events through a Noop-default CaptureSink: Latency: expert_fetch_us (cudaEvent around host->VRAM memcpy — yields the MEASURED pcie_h2d_bps axis for resource_vector, not a hardcoded 25GB/s), expert_compute_us, miss_stall_us, first_token_ms/token_latency_ms, load_ms. Values: hot_set_hit_rate (THE par metric), expert_value (=ExpertActivationProfile .hits, drives LRU+sentinel-PGO), working_set_size, co_activation, and residency_value=value/fetch_us — the value-per-cost grant_all prices each expert on. Closes the loop: measured fetch latency feeds the resource negotiation; measured hit-rate + tok/s are the iterate signal. Report every number; silent caps get log()'d. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01Q4NU4VNiELPQfBpCacDZGc
…ntinually The layer above serving (Joel 2026-07-29): the node continually self-benchmarks sustained tok/s + latency + hit-rate per activity-type × intelligence-tier on the LIVE hardware/load/grid, builds a capability map, and assigns each activity the highest intelligence that clears that activity's experience FLOOR — reassigning DOWN to a smaller/faster model below ~5 tok/s (a responsive lesser experience beats a stalling frontier one). Scales intelligence up/down on re-bearings (peer up -> up, load/thermal -> down). Objective is maximized EXPERIENCES (mean_experience), not raw throughput. Realizes existing primitives (QualityModel/mean_experience, grant_all over resource_vector, SystemProfile/catalog); the new piece is the CONTINUAL per-activity self-benchmark -> capability map -> intelligence assignment with per-activity floors. Sensory input = the GPU expert-paging tok/s+hit-rate meter (K3-GPU-EXPERT-PAGING) + benchmark flywheel. Measured, never guessed. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01Q4NU4VNiELPQfBpCacDZGc
…scalating Enriches self-calibration (Joel 2026-07-29): - Criticality gate: sub-scores (latency/fps/TTS/STT/quality) combine NON-linearly; a critical component degraded (lose TTS/STT in live video chat) collapses the whole score. Extends QualityModel critical-faculty gate from crash-only to any critical-component degradation. Context: 14 personas vs 3 vs 1, goal-weighted. - Degrade by criticality: cut least-critical sub-component first (background avatar fps) to protect load-bearing ones (active speaker TTS/STT), not a uniform throttle. - Temporal concentration: optimize experience over a WINDOW not each instant — briefly page out other personas so the smart MoE solves a hard problem, then restore. The governor being too worried about instantaneous fairness never lets deep work happen. - Difficulty/failure ESCALATION (dual of ~5tok/s reassign-down): detect thrashing/ failure/low-quality (e.g. an agent looping on a task) -> escalate tier (19B->K3, Opus->Fable) for the hard stretch -> de-escalate when easy. Failure IS the signal. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01Q4NU4VNiELPQfBpCacDZGc
…ip decode gate) Build agent (2026-07-29) verified two things: (1) the fork rebuild loop works via cmake+Ninja+vcvars+CUDA (~1 min, recipe recorded), sidestepping the VS18-2026 generator drift; (2) the GPU expert-copy mechanism ALREADY EXISTS in ggml (ggml-backend.cpp:1576 op-offload copies only used experts host->VRAM, mul_mat_id on CUDA) but is gated to prefill (batch>=32); decode falls back to CPU. Flip for decode at runtime: GGML_OP_OFFLOAD_MIN_BATCH=1 + --n-cpu-moe 999 -ngl 99. So no from-scratch build_moe_ffn rewrite — flip the gate + layer our measured residency/ hit-rate/slot-cache (the moat) on top. No token yet: K3 663GB on a 250MB/s HDD (63GB RAM) = 44-min load floor + per-token disk faults. Storage is the sole blocker; code+build+mechanism are ready. Path: model on NVMe (free C: via VSS) OR prove mechanism first on a RAM-fitting MoE. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01Q4NU4VNiELPQfBpCacDZGc
…y value Joel 2026-07-29 beta vision. The unit is the ACTIVITY (a room/experience/benchmark class): coding, agentic, multimodal, chat, video-chat, Hermes/open-system asks, continuous learning, dream/sentinels. Benchmarks aren't a scoreboard — they're HOW we achieve the activities. Each activity has ONE comprehensive criticality-gated score; degradation scores NEAR-zero not zero (zero is a dead gradient the ML can't learn from or distinguish from not-attempted; near-zero preserves how-bad + how-recoverable). Every run is measured = a graded training example -> learn the value of everything, know what each (persona x model/tier x node-state) can do. Arc: measure across activities+benchmarks -> (given the levers, e.g. GPU expert paging) design dynamic ML that responds across the grid knowing value -> p2p mesh -> economy LATER. Beta simplification: all FREE + egalitarian grid (LAN nodes and joined peers treated identically, no pricing) to ship the learning loop first. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01Q4NU4VNiELPQfBpCacDZGc
…rity, continuum yields Joel 2026-07-29: eventual system-wide (all-users) background service (deferred; his wife's account games on the box). The requirement: recognize the user + what they're doing (foreground GPU app / Steam / util spike from an unowned process = first-class contention signal), and treat the human's foreground GPU work as the HIGHEST-priority activity — continuum yields (sheds VRAM, deprioritizes/pauses lanes, pages out, scales down, or routes to grid) so the game gets the GPU. Degrade continuum, never the human's game. This is what capacity/mod.rs was built for (gpu_free_bytes_live = free after external unowned load; the seeding OOM was a static reserve blind to a game); Joel's scenario adds the sensor (foreground-app detection) + the aggressive-yield policy. Good citizen on a shared/gaming machine = precondition for the all-users service. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01Q4NU4VNiELPQfBpCacDZGc
…ing (after cache) Joel 2026-07-30: beyond the cache/paging (needed anyway), our foundry arsenal can DRAMATICALLY reduce K3 to a tailored model that fits VRAM+RAM directly at full GPU speed. The two ends of the dial: cache serves the full model on misfit hw; foundry reduction shrinks it to fit our needs. We already proved the subset step (the 19B via tools/scripts/compaction Plasticity Compaction). Arsenal to survey (don't reinvent): the foundry/forge, legacy widget (prior compaction experiments), sentinel-ai (PGO expert-subset from real activation), forge-alloy (the alloy artifact + attestation), targeted experiential plasticity (prune + compensation- LoRA from graded failures), variable/regional quant (#29), and the unet stuff (survey). Recipe: sentinel-PGO hot-subset -> prune -> regional quant -> compensation-LoRA from benchmark graded failures -> emit as attested forge-alloy artifact. Sequenced AFTER the cache. Complements kimi-k3-grid-strategy Path B/C. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01Q4NU4VNiELPQfBpCacDZGc
…> quant-targeting Joel 2026-07-30 correction: "we stripped experts, but that was old us. Now we page them in. Why ever lose knowledge?" Stripping/pruning permanently deletes capability = diminished model. We PAGE experts now, so all knowledge stays available. So the foundry reduction must NOT remove anything — it shrinks by lowering PRECISION where importance is low (targeted variable quant) while every expert stays reachable (hot resident, cold paged). The KEY reuse: the experiential-plasticity culling/growing-of-HEADS importance mechanism (sentinel-ai/PGO driven) is repurposed to target QUANTIZATION bit-width — one learned importance signal, two uses. The legacy widget is the CONTROL SURFACE for it. Recipe corrected: importance profile -> targeted variable quant (nothing removed) -> keep all experts (hot resident/cold paged) -> compensation-LoRA from graded failures -> attested forge-alloy artifact. Full knowledge, no paging tax on the hot path, zero knowledge lost. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01Q4NU4VNiELPQfBpCacDZGc
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…cation-provenance seam for Persona-RAID (#2056, co-designed w/ BigMama) Two additive fields on MemoryRecord, the target BigMama's Persona-RAID slice-2 receiver stamps on replay: - `origin_node: Option<String>` — node that ORIGINALLY admitted the record (None = local/lived) - `origin_seq: Option<u64>` — monotonic per-(persona, origin_node) admit seq, the newest-wins replay key (None = pre-replication) The KEY invariant (my review edge, now the agreed shape): replication is an ORTHOGONAL axis, NOT a new experience kind. `memory_type` (lived vs `shared-by`) is untouched — a replicated record keeps its experience (a replayed lived memory stays lived; a shared-by lesson stays taught) and merely gains (origin_node, origin_seq) as auditable/replayable metadata. So recall needs zero changes and audit gets everything. Both `#[serde(default)]` = zero migration for existing rows; every current construction site is a local admit → (None, None), semantically exact. ts-rs regenerated: `MemoryRecord.ts` gains `origin_node?: string` + `origin_seq?: number` (number not bigint, per the #120 drift rule). Validated: continuum-core compiles (--features metal,accelerate); memory::types tests green. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01LoTjvf5j3Ez13g6k8mRkFo
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…media-plane split (#2059) * fix(serving): eval-lane bring-up fails LOUD with the real cause, not a masked 240s /health timeout (#205 unmask) Glass-boxed 2026-07-27 running the live coding measurement (agent/solve): every `agent/solve` on this Mac failed with a bare "llama-server not ready after 240s (/health request failed)". The real cause was thrown away — `wait_ready` polled the health port for the WHOLE budget without ever checking whether the child it spawned had died, and never surfaced the child's stderr. ROOT CAUSE, proven this session: the ephemeral eval lane forges a SECOND Devstral-24B (~14 GB) while the live persona lane already holds ~26 GB. With only ~9.6 GB free, macOS jetsam SIGKILLs the second llama-server the instant it maps the model — before llama.cpp prints a single byte (reproduced by hand: exit 137, zero-byte log). It is an OS out-of-memory kill, NOT Metal-context contention and NOT a hang. The masking bug made it look like a mysterious timeout. Two unmask fixes in `wait_ready`, benefiting live AND ephemeral lanes: 1. **Fail loud the instant our child EXITS** — `child_exit_status()` (non-blocking `try_wait`) turns any crash-at-launch — including the jetsam SIGKILL/137 above — into an immediate `Spawn` error carrying the exit status + stderr tail, instead of polling a dead port for 240s. This is the arm that fires for the memory-wall failure. 2. **Fingerprint the empty stderr on the hang-timeout** — `tail_or_hang_marker` turns an empty log into a marker that, read with the exit status, names the two empty-log causes: an OOM/jetsam kill (SIGKILL/137, child exited) vs. a genuine early-init hang (no exit status). A crash from bad args / model-load fault prints its banner first, so a non-empty tail carries that directly. `tail_or_hang_marker` is a pure fn (unit-tested: empty→OOM/hang marker, non-empty→last 20 lines in order) so the load-bearing decision is tested without touching the real `~/.continuum/logs` path (#72 env-dependent-test lesson). This makes the failure DIAGNOSABLE; the underlying fix (don't forge a second 24B for eval while the live 24B is resident — reuse the live lane's weights or serialize via the governor, #59/#234) is a follow-up. Validated: continuum-core compiles (--features metal,accelerate, 0 errors); `tail_or_hang_marker_fingerprints_empty_and_tails_nonempty` green. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01LoTjvf5j3Ez13g6k8mRkFo * fix(serving): eval-lane gate refuses on real free-RAM-vs-footprint, not just pressure LEVEL — kills the jetsam SIGKILL at the root (#205) The companion to the unmask commit: don't just REPORT the eval-lane OOM loudly, PREVENT it. The gate (`await_eval_lane_memory_headroom` → `refuse_eval_lane_under_memory_pressure`) vetoed only on macOS *pressure LEVEL* + the sustained-pressure gate. But on unified memory the level reads "Normal" while sitting atop only a few GB of real free RAM — it counts compressible/cached pages as available. So the gate green-lit standing up a SECOND llama-server of a known ~14 GB footprint into 9.6 GB of actual headroom, and the OS jetsam-SIGKILLed it (exit 137, zero-byte log — the exact failure this session reproduced by hand). Neither the pressure gate NOR the GPU/CPU placement lease caught it: on unified memory the weights need the RAM on *either* device, so "spill to CPU" doesn't save you. Fix — size against the honest free-bytes number: - `MemoryPressureMonitor` already reads `sysinfo::available_memory()` each poll; publish it to a new lock-free global `current_available_bytes()` alongside the pressure level (the level is a ratio and lies; the bytes don't). - `eval_lane_ram_veto(available, footprint, headroom)` — a PURE, unit-tested guard that refuses ONLY when a KNOWN footprint won't fit in the KNOWN free bytes (+2 GiB headroom), and NEVER when either number is unknown (an unread probe must not starve a node — the pressure gate + placement lease stay the backstops). The refusal names the OOM wall, so the detached ledger carries a real cause and `await_eval_lane_memory_headroom` retries it as deferrable load instead of crashing. - One footprint sizing (`eval_lane_footprint`) now shared by the gate and the placement decision (compression — was duplicated inline). - Both eval-lane spawn sites resolve `base` and size the lane BEFORE the gate, so the RAM check runs pre-cold-load. This is the reliability doctrine [[reliability-is-it-works-not-that-it-reports-failure-well]]: the prior commit made the failure legible; this makes the machine refuse cleanly instead of being OOM-killed. Sibling of the #175 GPU-OOM-poisons-the-backend class — the level-vs-real- bytes gap is the same shape. Validated: continuum-core compiles (--features metal,accelerate, 0 errors); new `eval_lane_ram_veto_refuses_only_a_known_oversize_lane` + existing pressure-veto test green. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01LoTjvf5j3Ez13g6k8mRkFo * fix(deploy): install the continuum CLI as a real COPY on PATH, not a symlink into the ephemeral cargo target dir The flaky mess where `continuum` vanishes post-boot ([[deploy-cli-binary-deleted-from-target-dir-post-boot]]): `start-server.sh` symlinked ~/.local/bin/continuum → the cargo target-dir binary. But that dir is a BUILD artifact — cargo replaces the binary mid-rebuild, `cargo clean` and rust-analyzer's feature-mismatched rebuilds delete it — and the PATH symlink then dangles, so `continuum <cmd>` dies with "no such file or directory" (hit twice this session). Fix: COPY the binary to ~/.local/bin (atomic temp+mv so a concurrent `continuum` invocation never sees a half-written file), and `rm -f` any pre-existing entry first so a leftover symlink from an old install can't make `cp` follow it back into the target dir. The PATH binary is now decoupled from cargo's churn — it changes only on deploy. Same self- provisioning intent, minus the ephemeral-artifact coupling. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01LoTjvf5j3Ez13g6k8mRkFo * feat(benchmark): BenchmarkAdapter trait + registry — the grid-transparent, reusable, learn-from benchmark interface (rail 1 of #123) The goal (Joel): "have all these benchmarks IN OUR SYSTEM, AUTOMATED so we or others can REUSE them (just the optional download + the adapters). Run, TARGET and — more importantly — LEARN from these." And: "any command can run anywhere, so can benchmarks — a persona in any continuum can bench anywhere." That settles the architecture and this is rail 1 of it: - `BenchmarkAdapter` — ONE trait per benchmark: `dataset()` (OPTIONAL download spec, never bundled), `tasks()` (items in the canonical `EvalTask` shape so the SAME `agent/solve` path runs them — persona as a whole AGENT, not a bare LLM), `grade()` (defaults to the EvalTask's own test/expect verdict; real-repo benchmarks like SWE-bench override to grade the workspace after the agent acted), `resources()` (a hint for grid placement). - `DatasetSpec` / `DatasetKind` (HF / URL / Git) + `BenchResourceHint` (dataset bytes, needs_container, needs_network) so the runner fetches on demand and the governor can place the run on a capable node — the same demand-vs-resource negotiation serving/eval already do. - A process-global registry (`register`/`get`/`names`) — the single lookup seam the `benchmark/run` DynCommand resolves against; an unknown benchmark is a clean miss so the runner can fail loud with the known list, never a silent skip. - `TaskOutcome` / `BenchGrade` — the agent/solve artifacts (spoken + patch + workspace + harness verdict) handed to `grade`, and the per-task pass/score/reason that aggregates into the scorecard AND, on failure, feeds salience→curriculum→train (#116/#122) — benchmarks as CURRICULUM, not just a scoreboard. Why Rust-native (not the ad-hoc benchmarks/*.py): a DynCommand is the grid-transparent primitive — `Commands.execute("benchmark/run", …)` routes local-or-remote over airc; python can't route the mesh. Adapters shell to python/docker graders ON whatever node runs them. Outlier-validation order (next rails): OUTLIER A = HumanEval (tiny download, static, test- graded); OUTLIER B = the Terminal-Bench ContinuumAgent adapter (agentic meta-harness that unlocks TB's registry — docs/architecture/BENCHMARK-HARNESS-INTEGRATION.md). Then the `benchmark/run` DynCommand + grid dispatch + the learning tie-in. Validated: compiles (--features metal,accelerate); `registry_round_trips_and_reports_unknown` + `default_grade_delegates_to_harness_verdict` green. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01LoTjvf5j3Ez13g6k8mRkFo * feat(benchmark): HumanEval-rs adapter — outlier A on the BenchmarkAdapter trait (rail 2 of #123) The quick-cognition smoke rung (a step above arithmetic, per Joel): 156 Rust-translated HumanEval tasks our EXISTING Rust grader runs directly. Deliberately the SIMPLEST possible adapter — tiny, RESIDENT (no download), static, test-graded — so pairing it with a maximally-different outlier B (the Terminal-Bench agentic meta-harness: big download, real-repo, container-graded) proves the interface across both extremes. Nearly free because the in-repo `docs/genome/humaneval-rs.jsonl` rows ARE serialized `EvalTask`s (`{id, prompt, test, lang}`) — the same shape `cognition::eval` already deserializes — so the adapter is a per-line `serde_json::from_str`. This also exercises the trait's NO-DOWNLOAD branch (`dataset() == None`): a benchmark small enough to bundle needs no fetch; only the big ones (SWE-bench) do. Pure `parse_humaneval_rs` (line-by-line deserialize, honors `limit`, skips blanks, FAILS LOUD with the offending line number rather than silently dropping a task and inflating the pass rate) is unit-tested without the filesystem. Validated: compiles (--features metal,accelerate); `parse_maps_rows_to_evaltasks_honors_limit_and_fails_loud` + `adapter_identity_and_no_download` green. Next rail: the `benchmark/run` DynCommand (resolve adapter → tasks → agent/solve → grade → scorecard, grid-transparent) so this scores a model on any node — incl. BigMama's live Kimi-Linear-48B CUDA lane on :58057. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01LoTjvf5j3Ez13g6k8mRkFo * feat(memory): MemoryRecord (origin_node, origin_seq) — the RAID replication-provenance seam for Persona-RAID (#2056, co-designed w/ BigMama) Two additive fields on MemoryRecord, the target BigMama's Persona-RAID slice-2 receiver stamps on replay: - `origin_node: Option<String>` — node that ORIGINALLY admitted the record (None = local/lived) - `origin_seq: Option<u64>` — monotonic per-(persona, origin_node) admit seq, the newest-wins replay key (None = pre-replication) The KEY invariant (my review edge, now the agreed shape): replication is an ORTHOGONAL axis, NOT a new experience kind. `memory_type` (lived vs `shared-by`) is untouched — a replicated record keeps its experience (a replayed lived memory stays lived; a shared-by lesson stays taught) and merely gains (origin_node, origin_seq) as auditable/replayable metadata. So recall needs zero changes and audit gets everything. Both `#[serde(default)]` = zero migration for existing rows; every current construction site is a local admit → (None, None), semantically exact. ts-rs regenerated: `MemoryRecord.ts` gains `origin_node?: string` + `origin_seq?: number` (number not bigint, per the #120 drift rule). Validated: continuum-core compiles (--features metal,accelerate); memory::types tests green. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01LoTjvf5j3Ez13g6k8mRkFo * feat(benchmark): wire BenchmarkAdapter registry into benchmark/run — inventory self-registration, catalog-then-adapter resolution (#123) Converges the two benchmark systems instead of forking a third. The static known_benchmarks() catalog keeps its proven, DEPLOY-SAFE embedded-gym path for resident benchmarks (resolve_gym finds the gym even without a repo checkout). The BenchmarkAdapter trait becomes the EXTENSION seam for benchmarks the catalog can't express — downloadable / custom-graded ones (Terminal-Bench, SWE-bench) now land as pure adapters with zero change to benchmark/run. - benchmark/run resolves catalog FIRST (name it knows → embedded gym), else the adapter registry (benchmark::get), else fail loud listing BOTH sets. A downloadable adapter (dataset() = Some) fails loud 'download not wired yet' rather than silently scoring empty; resident adapters (dataset() = None, e.g. humaneval-rs) run today. Delegates to the ONE grader (cognition/eval) exactly as before — never reimplements grading. - Adapters self-register via inventory (the SAME mechanism commands use), so a builtin needs NO boot hook and NO central list (the dynamic-discovery contract). get()/names() fold the link-time inventory set in over runtime registrations. - HumanEvalRsAdapter submits itself; new test pins that benchmark::get('humaneval-rs') resolves with no boot hook. 19 benchmark tests green; 0 errors. This makes rail 1+2 of the adapter framework LIVE on the grid-transparent benchmark/run command, ready for the Terminal-Bench ContinuumAgent adapter (outlier B) to slot in. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01LoTjvf5j3Ez13g6k8mRkFo * fix(boot): macOS core boot — bash-3.2 manifest gate + rt_handle.spawn off-runtime panic (#194) TWO regressions that made the macOS core un-bootable since the last long-running core died (glass-boxed live 2026-07-28; nobody could reboot on macOS): 1) start-server.sh sourced generated/manifest.macos.sh (bash-4 `declare -A`) under `set -e`; macOS ships bash 3.2, so the source aborted the whole boot before cargo ran. Regression from #2046 'serve on Windows' regenerating the manifest with associative arrays. Fix: only source the bash-4 manifest on bash 4+ (it solely feeds the Windows/CUDA runtime-PATH augmentation, whose own guard already tolerates absence). 2) ipc/mod.rs:1704 used bare `tokio::spawn` in the SYNC boot region (after the rt_handle.enter() guard drops) → 'there is no reactor running' panic → the IPC listener thread died → socket never bound → whole core a zombie. Regression from #2051's AircInterceptor block; every other spawn in the fn already uses `rt_handle.spawn`. Only reached when airc deps are present, so it bricked boot on every airc-configured host. Fix: rt_handle.spawn, matching the siblings. Verified: core boots to socket-live + answering commands in 60s; personas resume from disk and respond in live chat (Anwen answered a direct question with memory recall). Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01LoTjvf5j3Ez13g6k8mRkFo * fix(boot+ui): macOS core boots + ONE automatic door into the positron interface (#194/#29) Two boot regressions that made the macOS core un-bootable since the last long-running core died, plus the missing automatic entry into the interface (you can't ship a beta a user can't open). BOOT (both verified — core now reaches socket-live in ~60s, personas resume + answer live chat): 1. start-server.sh sourced the bash-4 `declare -A` manifest under `set -e` → macOS bash 3.2 aborted the whole boot before cargo ran (regression from #2046). Gate the source on bash 4+. 2. ipc/mod.rs:1704 bare `tokio::spawn` in the sync boot region (after rt_handle.enter() dropped) → 'no reactor running' panic killed the IPC listener → socket never bound → zombie core (regression from #2051). Use rt_handle.spawn like every sibling. UI DOOR (#29): nothing tied the built positron web client to the running core, so finding 'how do I open the interface' required archaeology — exactly how a user (and an agent) gets lost. - New tools/scripts/open-ui.sh + `npm run ui`: resolves the core WS (8974) + call/video WS (8790) + a stable identity, ALWAYS rebuilds apps/web from current source (a stale dist renders an old shell — the 'interface looks lost' trap, glass-boxed today: a Jul-18 dist showed a bare chat view, not the current positron HUD), serves it, opens the browser with everything pre-wired. Verified live in headless Chrome: the full positron HUD (SYSTEM CPU/MEM/GPU sparkline, NODES, genome-paging tiles per persona, Go-live, rooms, live persona cognition) renders against the live core. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01LoTjvf5j3Ez13g6k8mRkFo * fix(live): auto-start the LiveKit avatar rail with the core (server + bridge sidecar) The persona's talking avatar is Bevy-rendered and published to a LiveKit room via the livekit-bridge sidecar; the browser's 'Go live' subscribes to that room. But NEITHER the SFU nor the bridge was started by `continuum start` — glass-boxed 2026-07-28 by joining the call plane headless: LiveKit :7880 was DOWN → get_or_create_agent fails → no avatar video pump ever runs, and clients only ever saw the native call_server's test-pattern default. The avatar was un-launchable without manual, undocumented steps (start livekit-server, build + start the bridge) — a beta can't ship a 'Go live' button that needs hidden setup. start-server.sh now runs start_livekit_rail() before the core, idempotently + NON-FATALLY: 1. livekit-server --dev on :7880 (dev creds devkey/secret = the bridge defaults) if not already up; warn+skip if the binary isn't installed (core still boots, only live A/V off). 2. build (release, once — links webrtc-sys) + start the livekit-bridge sidecar on its unix socket BEFORE the core, so the core's bridge_client finds the socket at boot. A missing/failed rail never blocks the core (chat/cognition/serving unaffected). system-stop.sh gets symmetric teardown of the bridge (server teardown already existed). Verified: syntax clean; idempotent against an already-running rail (both start steps skip when :7880 is up + the bridge is running). The rail itself is proven live this session — livekit-server + bridge up, core connected, an STT participant joined the LiveKit room. Follow-up (functional, not automation): the per-persona avatar VIDEO agent (get_or_create_agent + spawn_avatar_video_pump) still doesn't publish — only the STT listener joins the room. Next. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01LoTjvf5j3Ez13g6k8mRkFo * feat(live): tee avatar frames into the native call plane — everyone sees the real face (#193/#172) The avatar published to LiveKit, the bridge received it (640x360), but the native call plane (call_server WS 8790) that BOTH the positron web client AND the glass-box harness read still emitted its own 160x120 SMPTE test pattern. The real avatar was stranded on a rail no native viewer subscribed to. Convergence (render once, two sinks): the single Bevy slot the avatar pump already allocates now feeds BOTH LiveKit and the native plane. Per frame the pump tees the same RGBA into CallManager::push_avatar_frame, encoded in the exact [VideoFrameHeader][pixels] contract native clients decode, labeled with the persona's uuid. No second Bevy slot, no parallel renderer. - call_server.rs: push_avatar_frame (new seam) + retire the auto-start test pattern to an opt-in debug affordance (CONTINUUM_CALL_TEST_PATTERN=1), honoring the TODO that sat on the auto-start block since real sources were 'not yet connected'. - video_pump.rs: tee each frame (stable source Handle + monotonic seq/clock) alongside the LiveKit publish. - modules/live.rs + ipc/mod.rs: thread the native CallManager through VoiceState to the register-session pump spawn. - example: standalone CallManager (tee is a no-op there). Live-verified on the native plane after deploy: 640x360 real avatar (Asha's VRM, not the test pattern), 13.5 fps wall / 13.3 median (tracking the 15fps Bevy target), inter-frame jitter min 56.8 / median 75.4 / max 86.4 ms, 0 dropped/out-of-order frames, sole sender = Asha's uuid. Random-frame spot-check shows her real face, live-animating. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01LoTjvf5j3Ez13g6k8mRkFo * fix(voice): one canonical model root — kill the CWD-relative path bug that silently broke every local TTS/STT (#195) Root cause (glass-boxed this session): the workers→core/tools restructure moved the runtime model download root to `tools/models/` (gitignored — see .gitignore's own note), but every audio adapter kept stale, CWD-relative `models/…` path constants. When the core runs from the repo root (its normal CWD), `models/piper/…` pointed at the *tracked* avatar dir, not the voice models in `tools/models/piper/…` — so Edge returned empty, and Piper / Kokoro / Moonshine / Whisper all reported 'model not found'. Every local voice model was silently dead. Kokoro even mutated the process CWD (`set_jtag_cwd`) to paper over it. Proper fix — single source of truth, absolute, CWD-independent: - New `live/audio/model_root.rs`: `voice_model_root()` / `voice_model_path()`. Resolves `CONTINUUM_MODELS_DIR` (config.env single-owner, then process-env boot injection), then `tools/models`/`models` CWD candidates, then `~/.continuum/models`. - Routed EVERY voice adapter through it — piper, kokoro (15 sites), orpheus, moonshine, whisper, pocket-tts, silero VAD, tts_service. No more scattered `models/…` literals, no per-adapter candidate ladders, no `set_current_dir`. - start-server.sh exports `CONTINUUM_MODELS_DIR=$REPO_ROOT/tools/models` before exec so the binary resolves models from any CWD. Live-verified after deploy: fresh core has CONTINUUM_MODELS_DIR injected, no symlink present, `voice/synthesize-handle --adapter piper` resolves the model and synthesizes (was 'model not found' before). (The short synth duration is a separate phonemizer/espeak-data issue, not this.) Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01LoTjvf5j3Ez13g6k8mRkFo * feat(live): tee persona voice into the native call plane — client hears her, not hold music (#193 audio convergence) Sibling of the avatar-video tee. A persona speaks via LiveKit (speak_in_call → bridge), but native clients (positron web, glass-box harness) read the native mixer — which, with only a lone listener, plays HOLD MUSIC. So a native viewer SAW her avatar but HEARD hold music: her voice was stranded on the LiveKit rail. Render once, two sinks: speak_in_call now returns the synthesized PCM, and the voice/speak-in-call handler tees the SAME samples into the native plane via CallManager::push_persona_audio — which registers the persona as a virtual AI participant in the call's mixer (the mixer already has an AI ring buffer built for 'dump a whole TTS utterance, drain frame-by-frame') and her presence stops the lonely-listener hold-music fill. Self-heals across call recreation via a stable per-(call,persona) handle. Live-verified: with Asha registered + speaking (kokoro), a native-plane capture shows audio sender = her uuid (90e758b2) for 4.58s, matching the 4.55s utterance — was 100% 'hold-mus' before. Video (640x360 avatar) + audio (her voice) now both reach the client: e2e see+hear on the native plane. Also this session: espeak-ng installed so kokoro TTS produces real full-length speech (piper's Rust phonemizer truncates — kokoro is the good local path). Follow-ups: hold-music still fills her SILENCE between utterances (minor polish — suppress when a persona is present); STT/audio-in blocked on moonshine ONNX format mismatch; livekit-bridge needs supervision (dies on every core restart). Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01LoTjvf5j3Ez13g6k8mRkFo * feat(positron): durable local state + self-healing feed — inherent to the SDK, adapter-driven (the Twitter model) Glass-boxed 2026-07-29: routine core reboots orphaned every open tab — the state feed died once, the shell silently degraded to the bare chat view, and four months of positron HUD looked 'lost' until a manual refresh. Per Joel: this is normal app craft (cache-first boot, live reconcile, visible reconnect) and it must be POSITRON architecture — from the thin-client SDK out, adapter-driven local state, never an app-level hack or a localStorage bodge. SDK (sdk/typescript — the contract every platform SDK mirrors): - StateStorage.ts: StateStorageAdapter — the ONE local-durability seam. The whole renderable state is latest-envelope-per-kind (each envelope is a full snapshot), so the cache is tiny + complete. Adapters: IndexedDbStateStorage (browser), MemoryStateStorage (tests/ephemeral + conformance reference); swift/kotlin/ flutter implement the same interface over native stores. Cache is an accelerant, never a dependency (storage failure -> live-only, logged once). - StateConnection: durability + resilience are now INHERENT — - hydrate-first connect(): cached envelopes paint before the network is touched (instant last-known UI, even against a dead core), status 'cached'; - write-through: every live envelope replaces its kind's row (fire-and-forget); - auto-reconnect (default ON): capped 1s->10s ladder using the wire's existing last_seen replay; a failed FIRST connect rides the same ladder (core booting); - onStatus surface (cached/connecting/live/reconnecting/closed): recovery is LOUD — reconnecting stays visible while the core is away, so self-heal can never mask a dead core; close() stops the ladder (intentional shutdown); - reconnect:false preserves the legacy one-shot fail-loud contract for probes. - Fail-loud config errors (no registered kinds) never enter the retry ladder. App (apps/web): shrinks to what an app should be — pass IndexedDbStateStorage, render envelopes + ONE status chip. Zero resilience logic app-side. Tests: 97/97 SDK suite green; 4 new pins (default-resolve+reconnecting status, hydrate-before-open, write-through, drop->reconnect->resubscribe w/ last_seen). Live-verified: rebuilt app renders the full positron HUD through the new feed. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01LoTjvf5j3Ez13g6k8mRkFo * feat(mobile): positron durable-state contract on Android + iOS — Dart mirror of the SDK, tested One Dart implementation (byte-identical on both OSes) mirroring sdk/typescript's inherent resilience contract, per [[positron-durable-state-is-sdk-inherent-adapter-driven]]: - lib/positron_state.dart: StateEnvelope + StateStorageAdapter (the ONE seam) with MemoryStateStorage (conformance reference) and FileStateStorage (dart:io JSON — durable on Android + iOS app dirs, ZERO plugin deps, corrupt-tolerant, cache is an accelerant never a dependency); StateConnection with hydrate-first connect, write-through, capped 1s->10s reconnect ladder w/ last_seen replay, loud status (cached/connecting/live/reconnecting/closed), reconnect:false one-shot fail-loud. Injectable StateSocketFactory — tests drive the lifecycle without a core. - lib/live.dart: LiveConnection now RIDES the contract (was a one-shot connect that died silently — the same disease the web had). App keeps only the ChatViewState->MobileScreen mapping + optional status/cacheDir wiring. - test/positron_state_test.dart: 5 pins mirroring the TS spec — hydrate-before- socket, write-through, drop->reconnect+last_seen, fail-loud vs self-heal, FileStateStorage conformance (round-trip, replace-by-kind, corrupt-tolerant). - ios/: runner scaffolded (flutter create --platforms=ios). Verified: flutter test 6/6 green, flutter analyze clean. Platform note: the Dart contract tests prove BOTH OSes (same code); Android SDK present for APK builds; iOS device/simulator builds need full Xcode on this machine (CLI tools only). Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01LoTjvf5j3Ez13g6k8mRkFo * fix(web): tab strip renders from ONE open tab — the focused room IS a tab Glass-boxed live: the strip + CSS + nav plumbing all shipped (38b60caae), but the render gate was cells.length > 1 while the node's room-set fold knows exactly one room (cambriantech) — so the whole bar hid and the interface read as 'tabs don't exist'. One open activity is still an open tab; the strip now draws from 1 up, and fills out as the room set grows. Substrate follow-up (separate card): seed spawn_room_set_fold from airc's subscribed-room registry (durable membership), not just observed traffic — today a room with no traffic since core boot never becomes a tab. Verified live: playwright screenshot + widget-state dump (tabBarTabCount 1), web tests 21/21, typecheck clean. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01LoTjvf5j3Ez13g6k8mRkFo * feat(web): Discord shell geometry — full-height rails, center-scoped tabs/header/compose The reference is the Discord/VS Code shell: columns run window-top to window-bottom; no chrome bar spans the whole width. The left rail now opens with the continuon (the server-header slot), the tab strip sits centrally over the content column only, the room header/transcript/composer all live inside the center column, and the ROOM context rail runs full height. Mechanically: RenderTarget.workspace grows an optional WorkspaceChrome<Out> slot (patterns) — the compose bar stays HOST-owned (input state + send handler) but SHELL-placed (chrome.centerFooter), so the widget no longer appends full-width rows after the surface. litTarget nests tabs + header + what + footer in a .center flex column inside the same .panels grid the universe skins and mobile rules already key off. Also: /// <reference lib="dom" /> on sdk StateStorage.ts — the IndexedDB adapter's DOM types broke typecheck for non-browser consumers (tui) since e4fedac8f; scoped ambient types fix every consumer without forcing lib:dom. Verified live: playwright screenshot (full-height rails, central tab, center compose), web 21/21 + chat-view 56/56 + patterns 5/5, typecheck clean on web/patterns/tui. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01LoTjvf5j3Ez13g6k8mRkFo * feat(chat): beforeMessageId scroll-back cursor on chat/poll — history pages out of durable storage The Twitter endless-scroll's storage half: chat/poll gains the backward cursor. beforeMessageId resolves the anchor's stored timestamp (same lookup as afterMessageId, now ONE anchor_timestamp helper), filters $lt, queries DESC, and normalizes chronological — the limit messages immediately preceding the anchor, straight from the durable chat_messages store. The two cursors are mutually exclusive and reject loud BEFORE any storage round-trip; the result echoes the cursor so the caller's paging loop just keeps passing the oldest id it holds. Client loop (web/mobile/tui alike): render the live 50-row tail, then scroll-back = chat/poll {roomId, beforeMessageId: oldest-on-screen} — prepend, repeat until an empty page says history is exhausted. The render-side wiring is the follow-up slice; the trigger idiom stays per-target (IntersectionObserver on web, ScrollController on Flutter), the cursor mechanics live here, once. Tests: before-anchor $lt+DESC+chronological, both-cursors reject (pinned to fail before data/query), absent-not-null echo. 32/32 chat module green; ts-rs bindings regenerated. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01LoTjvf5j3Ez13g6k8mRkFo * fix(sdk): export the drifted wire types — 64 registered-command params/results never emitted ts-rs bindings The pre-existing drift that has blocked the TypeScript SDK re-emit (and forced nav/select onto the raw-wire path): TS-deriving wire types across commands/{benchmark,help,tool}, cognition, runtime, and modules lacked #[ts(export, export_to)] — the emit's vendoring walks the registry and fails loud on the first missing binding. Swept every one onto the same protocol/typescript/<module>/ convention its file siblings use. export_bindings: 1236 green (was 1160). Remaining emit blocker (separate card): bare #[ts(export)] types land in the crate-local bindings/ dir while the vendorer expects protocol root. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01LoTjvf5j3Ez13g6k8mRkFo * feat(web): Twitter endless scroll — scroll-back pages durable history into the transcript The render half of the beforeMessageId cursor (02d5c7701): - chat-view: historyRowsFromPoll — one chat/poll storage page (raw entities: {content:{text}, ISO timestamp, no sender name}) onto the SAME MessageRowVM rows the live tail renders; roster-resolved identity, short-id + metadata.source fallback, live-tail dedup, malformed-row skip. 3 specs. - widget: scroll-near-top pages one older window and prepends with the viewport anchored (scrollTop compensated); rows that slide OUT of the live 50-row window RETIRE onto the buffer so no gap opens; buffer clears on room switch; an empty page latches exhausted. - scroll-yank fix (reported live): pin-to-bottom now only fires when the reader was AT the live edge (_wasNearBottom, measured pre-render) — a scrolled-back reader is never forced down by a new message. - host: chat/poll over the same raw-wire seam as nav/select (the typed CommandMap re-emit is still blocked; path documented in-code). - sdk drift: corrected the swept export_to paths to the proven ../../../protocol/typescript/ convention (benchmark/help/tool/agent); strays under core/protocol removed; export_bindings 1172 green. Live activation needs the rebuilt core (beforeMessageId lands on the next core restart — held deliberately: a restart replays the room log until #242 consumer cursors land). Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01LoTjvf5j3Ez13g6k8mRkFo * fix(web): transcript times in the VIEWER's timezone + genome panel goes two rows of four Time: formatTimeOfDay was hardcoded UTC ('4:36' at Joel's 11:36 PM — wrong for every human off-meridian). Now local getHours/getMinutes; determinism moves to the test scripts (TZ=UTC pinned in chat-view + web package.json) instead of being baked into the product. Genome: 8 slots in a 4×2 grid (was one row of 4) — the loadout is heading past four as skills go per-domain and expert granularity (#226) lands; slots stay honest-dark until genes page in, top-8 lit with overflow named in the tooltip. Tests 59+21 green, typecheck clean, rebuilt. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01LoTjvf5j3Ez13g6k8mRkFo * fix(web): genome-click anchor re-lands after layout settles — the card sticks at the pane top Verified with a headless click receipt: the genome block DOES open that citizen's persona-home tab anchored at the #genome card (element navigation, card 95844639), but the single scrollIntoView fired before avatar-image decode / meter layout settled — the card drifted ~400px down-pane, reading as 'nothing happened'. Two follow-up rAF re-lands pin it. Harness note: headless clicks were steering the LIVE view — the harness shared Joel's ?me= citizen (nav focus is per-citizen, server-side). Minted a dedicated harness citizen (~/.continuum/ui-test-id); future interaction tests use it, never the operator's scope. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01LoTjvf5j3Ez13g6k8mRkFo * feat(nav+web): persona selects OPEN durable tabs (never swap) + sender names link to profiles + history-trigger guards Three live reports from Joel, one slice: 1. ONE shape-shifting persona tab: the nav reader derived the persona tab from the single current focus — selecting a second persona REPLACED the first. NavFocus now keeps the citizen's open non-room activity SET (activity == room == tab: a persona select OPENS a durable tab, a second select adds a SECOND tab) + a close() for the future nav/close verb. Reader surfaces every open activity. 9 nav tests green. (Core-side — live at the next core restart.) 2. 'History load failed: chat/poll rejected: unknown error' on persona click: two stacked bugs — the persona home OPENS at scrollTop 0 which tripped the transcript's near-top history trigger (now guarded off all non-transcript faces), and the bare-wire success check treated every response as a rejection (no success field on the raw path — only an explicit false is an in-band rejection; failures reject the promise). 3. Sender names in the transcript now open that citizen's profile — the SAME composed roster LISTING_SELECT the tiles fire, one nav verb, no parallel route. Keyboard-accessible, element-link affordance. Web 21/21, typecheck clean, rebuilt. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01LoTjvf5j3Ez13g6k8mRkFo * feat(nav+airc): tab close wired end-to-end + consumer cursor kills the reboot replay (#242) Tab close (Joel: 'tab close not wired yet' + 'super small hitbox'): - core: nav/close verb — removes one open activity from the citizen's tab set (NavFocus::close), clears focus if it was current, publishes nav:changed. Registered + in NavModule::commands(). 12 nav tests green. - web: the × is LIVE on non-room tabs (rooms are membership, not tab state) — composed NAV_TAB_CLOSE → widget → injected nav/close over the raw-wire seam; substrate-truth removal, no optimistic local state. Hitbox grown to ~22px square (padding + negative margin — glyph stays compact, target meets the pointer minimum). Consumer cursor (#242 — 'chat still loading literally every message in existence when you reboot', bitten 3× today): the attach stream asked for AttachStart::FromTranscriptStart on EVERY attach. Now a per-channel IpcCursor watermark persists under ~/.continuum/state/; attach resumes AttachStart::After(cursor) (gap only, no seam duplicates), advances to the daemon's RoomTip after attach, and persists AttachCursorAdvanced frames. Only the first-ever attach (no watermark) seeds from transcript start — once per state dir, never per reboot. Documented trade-off: a hard crash loses a slice of LIVE perception, never storage — the durable transcript + scroll-back serve history; replaying the log into every persona's mind each reboot was the worse failure. Live at the next core restart (which will be the LAST replaying one). Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01LoTjvf5j3Ez13g6k8mRkFo * feat(web): durable-store hydration + Activities rename + rooms-only facet default Post-cursor reality check (Joel: 'No messages yet — say hello' after the reboot): the live projection now honestly starts AFTER the consumer watermark, so a rebooted room painted empty — the data was never gone (the durable transcript held every message; chat/poll served it), the window just never pulled it. Fix: a sparse first snapshot (<10 rows) auto-pages the LATEST stored window via the anchor-less chat/poll and prepends — the Twitter model complete: durable tail + live wire, one transcript. Verified live: 51 rendered rows from 1 wire message. Also per Joel: - the left rail's Rooms widget is now titled ACTIVITIES (they are rooms; the widget lists activities) — title flows from the projection. - the facet defaults to [Rooms]: open persona/content tabs are real activities but reached via their own controls (roster tiles, the tab strip) — the 'rooms' facet now excludes persona/content groups, and All remains one click away. Web 21/21 + chat-view 59/59, typecheck clean, rebuilt. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01LoTjvf5j3Ez13g6k8mRkFo * fix(web): 'Send failed' on every SUCCESSFUL send — only explicit success:false is a rejection Same response-shape bug as the history handler, now on the send path: chat/send's success payload is {eventId, messageId} with NO success field, so `!result.success` threw 'chat/send rejected: unknown error' while the message actually landed on the wire (glass-boxed live — Joel's 'How are you, I am Joel' arrived as peer-a5ded599 despite the strip). Failures reject in the transport; in-band rejection = explicit false. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01LoTjvf5j3Ez13g6k8mRkFo * fix(positron): projection hydrates from the durable transcript — the SUBSTRATE owns room fullness, never the renderer Joel's charge, accepted: 'why was the room history cleared? that's invalid positron — are you coding just regular lit?' The old full-backlog attach was secretly the chat projection's ONLY hydration mechanism; killing the replay (#242) starved the accumulator, and I patched it in the WIDGET — app-level durable-state logic, the inverted shape. Correct shape, now built: positron_source::spawn takes a durable seed (executor + bootstrap room). Before folding live events the projector hydrates its accumulator with the room's stored tail (the same chat_messages query chat/poll serves), pushed through the SAME classify path as wire events — one message semantics, two sources. Data-module warm-up is retried; a seed that never comes degrades to wire-fed-only, logged loud. Every client gets a full room with zero client logic. Also: WebSocketTransport discriminates push frames from replies — the ingress fans state envelopes to command-only sockets, which spammed 'reply for unknown correlation id undefined' 22× in Joel's console while every command actually worked. id-less frames are pushes, ignored; the server-side fan-out fix is a follow-up card. positron_source 16/16, sdk + web green. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01LoTjvf5j3Ez13g6k8mRkFo * revert(airc): consumer cursor OFF until it ships as one unit with perception hydration (#249) The cursor (#242) starved MORE than the UI window: glass-boxed live — Asha's turn prompt was a system prompt + ONE EMPTY user message, and Benchy answered Joel's direct question with 'you haven't provided any context'. The perception substrate (channel digest) drinks from the same cursored bus, so personas were left conversationally blindfolded: minds intact (engrams verified — Asha 11,667 rows, Atlas 10,035, writes minutes old), sensory feed empty. The greeting loop was the honest response to an empty world. Rollback: attach returns to FromTranscriptStart (full replay — the known, working behavior), watermark files deleted. The projection's durable seed (44a8b2606) stays — it is correct independent of the cursor. The cursor relands ONLY together with #249 (perception-tail hydration from durable storage), tested against a live persona turn BEFORE deploy: the lesson is that the replay was load-bearing for TWO consumers, and I verified only one. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01LoTjvf5j3Ez13g6k8mRkFo * fix(web): auto-scroll tracks READER INTENT, not bottom-distance — the position heuristic silently killed pin-to-bottom Joel: 'you designed it dumb, we did this before — you have to keep track of whether they scrolled up themselves.' Correct. The _wasNearBottom threshold died the moment a tall message grew the bottom-distance past 150px — after which every new message grew it further and auto-scroll never returned. Replaced with intent: a USER scroll away from the bottom parks auto-scroll; returning to the bottom re-arms it; programmatic pin-to-bottom scrolls are guarded out (_autoScrolling) so they never read as intent. Stream deltas (_typing) now also pin, so the token rail stays in view. Web 21/21, typecheck clean, rebuilt — reload to pick up. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01LoTjvf5j3Ez13g6k8mRkFo * feat(web): code is SHOWN, not hidden — line-numbered open-by-default code cards + fence-aware digest Joel: 'the code should have line numbers and show where its placed into code context like you do… i feel like for BOTH persona and humans we show it unless its huge.' Three fixes, one policy (show the start, expand for the rest, same rule at every density): 1. Renderer (parts.ts): blocks ≤40 lines render fully open (the old n<=3 collapse hid a 4-line snippet behind a '▸ RUST' bar); bigger blocks show the first 25 lines with a '+K more lines' expander whose gutter numbering continues seamlessly. Every block gets a line-number gutter. Templates whitespace-TIGHT — the pretty-printed newlines inside the pre-wrap bubble were the giant-empty-padding bug. 2. Digest (messageDigest.ts): fence-aware. Flood bounds now count each fenced block as ONE projected line (the code card self-truncates, so code can't flood pixels), and the head cut treats fences as atomic — live bug: the digest cut Claude's wordstats reply MID-FENCE and the dangling ``` rendered as literal backtick noise. 3. Specs: 3 new regressions (never-split-a-fence, whole-fence-in-head, unterminated fence) — chat-view 62/62, web 21/21, verified live in cambriantech (Asha's 2-liner open+numbered; Claude's 16-line card). Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01LoTjvf5j3Ez13g6k8mRkFo * fix(web): retire the typing bubble on the settled message, not only on the done delta The stream-end contract had ONE signal (delta.done) and no fallback: a dropped/raced done flag left the cursor blinking forever over a message that had already landed (live 2026-07-30: Atlas + Benchy both looked hung after their turns settled). The settled post IS the ground truth that the stream ended — willUpdate now diffs new-arrival senders on every state change and retires their bubbles. done still works for the common path; this makes the stale-cursor state unreachable. Act pauses mid-turn still show a cursor (real work, no visual vocabulary yet) — that rendering is #254/#253 core-side work. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01LoTjvf5j3Ez13g6k8mRkFo * feat(cognition): FAIL LOUD on a starved prompt — never deliberate on a blank mind The 2026-07-30 outage mechanism, made impossible to miss: when window arithmetic (reserve + tool schemas + framing) squeezed msg_budget to ~0, the fitter's last-resort arm emitted ONE EMPTY user message and every persona greeting-looped for an hour while looking alive. Two guards now: 1. Fitter (delib.prompt.empty): a trimmed tail that comes back EMPTY is refused with an error probe carrying the budget arithmetic — never an empty ChatMessage. 2. contribute() (delib.prompt.starved): a view whose conversation is all empty while the room HAS turns skips the turn with an error probe — the room's messages stay queued, the next tick re-perceives; blind deliberation is never an option. The two verdict tests that broke were silently EXERCISING the bug path — ctor-default window, framing starved msg_budget to 0, scripted adapter masked the blank prompt. They now run at a real 32k window and test what they claim. 21/21 llm_deliberation green. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01LoTjvf5j3Ez13g6k8mRkFo * feat(vitals): cognition compass AFTERGLOW — 6/s decay so the mind's glow is visible between turns + lowercase brand title DOM probe (.gymtool/vitals.mts, the new TS hot-path instrument) caught the wiring working — Anwen mid-turn: Reason 19, Recall 80, Act 16 — for exactly ONE 2s radiator sample before the 40/s decay blacked it out. With turns minutes apart the compass read as permanently dead (Joel: 'cognition not wired into the diamond' — it WAS wired; it was invisible). Decay 40/s → 6/s: a full pulse now eases to dark over ~17s — a readable afterglow of what the mind just did, still honestly dark at rest well inside a minute. Decay test re-pinned to the new contract (82 at 3s, 0 by 20s). Also: brand is always lowercase — <title>continuum</title>. Findings logged, not changed here: QUE pegged at 100 on every row is HONEST — staged digest unread never drains (personas never advance bookmarks, #43's territory); genome slots dark = honestly no genes paged in. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01LoTjvf5j3Ez13g6k8mRkFo * feat(airc): RE-LAND consumer cursor on inbound attach — resume from watermark, never replay the whole transcript (#242, exonerated) Joel on tonight's boot storm: 'why would it replay the whole chat start to finish? its insane.' It replayed because the bus-fed transcript writer needed boot-time replay to fill the offline window — full replay was load-bearing by accident. The cursor (attach After(watermark), persisted per room) delivers exactly the missed window: no storm, no holes. This is a byte-identical re-land of d4dbc9982, which was reverted during the 2026-07-30 outage on the theory it starved persona perception. The deep trace EXONERATED it: perception pulls the daemon's durable tail every turn and never consumed the attach replay; the blank minds were the spawn-pinned window budget bug — since fixed (live-window reconcile) and guarded loud (delib.prompt.starved / delib.prompt.empty error probes). Verification protocol this time, per the incident doctrine: live persona capture non-empty + zero starved probes + quiet boot + transcript continuity, BEFORE calling it done. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01LoTjvf5j3Ez13g6k8mRkFo * feat(positron): renderer frames coalesce at 10Hz + 100-message window — bursts become beats, not storms Joel: 'if i were me, i would see like the last 100 messages, and scroll for more — positron ought to make this easy.' Two changes, one contract: 1. Subscribed renderers no longer forward EVERY revision (Unlimited). State kinds are latest-wins snapshots on a watch channel, so intermediate revisions are legally skippable — RENDERER_HZ=10 sends the first change instantly (lone message: zero added latency) and coalesces bursts to at-worst 100ms behind. The boot-replay load storm (thousands of folds → thousands of socket frames raining into the tab) becomes ≤10 latest-state frames/sec. Token streams ride the separate stream rail, untouched. 2. Snapshot window 50 → 100 (MAX_MESSAGES_PER_SNAPSHOT), seed query bound to the same constant — one source for the window size. Scroll-back keeps paging older history from the durable store. With the attach cursor (f8e4ae6cc) this closes the storm class: resume from watermark delivers only the missed window, and whatever bursts do occur render as a handful of coalesced frames. positron 105/105+5/5, core positron_source 16/16. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01LoTjvf5j3Ez13g6k8mRkFo * feat(live): turn-start beacon → 'responding…' under the last message + dynamic lowercase title + continuon favicon Joel, during the dead-looking-interface scare (four minds mid-turn, zero pixels moving): 'in other systems it says XYZ is responding — we could use that right below the last chat item.' Three pieces: 1. Core: the token forwarder emits ONE empty-token START BEACON the moment generation dispatches — before prefill, which on a cold lane runs minutes. No wire change: an entry with no text yet IS the signal. The done flush retires it even on a speechless settle. 2. Web: a typing entry with empty text renders 'responding…' instead of a bare cursor (the bare cursor was the hang-look); text flowing keeps the live tail + cursor. 3. Web: document.title mirrors the current activity — 'continuum — cambriantech' (the #252 short-title rule, brand always lowercase; the static <title> edit finally ships too — it was edited but never rebuilt into dist, my miss). Favicon: the continuon orb becomes the subject (it IS the fourth-wall being), ring as threshold. Web 21/21 + rebuilt; core cargo check clean. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01LoTjvf5j3Ez13g6k8mRkFo * feat(web): '(xyz, abc) is responding…' — ONE grey line between the last message and the compose box Joel's exact spec, third iteration tonight: not a transcript bubble — the Discord-convention grey status line pinned above the composer, one line max (nowrap + ellipsis), parenthesized dynamic name list that updates as turns start and settle. Driven by the stream map: the #254 start beacon adds a persona the moment their turn dispatches — minutes before the first token on a cold lane. Beacon-only entries (no text yet) no longer render an empty bubble; streams with real tokens keep the live bubble as before. Web 21/21, rebuilt — refresh to pick up. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01LoTjvf5j3Ez13g6k8mRkFo * fix(web): STOP KILLING LIVE STREAMS — retire a typing bubble only on ITS OWN settle, and never hide a consecutive speaker's stream The streaming regression Joel caught ('did you just totally remove it'): the stale-cursor fix retired a persona's bubble on ANY arrival from them. With settles landing minutes late and reboot-echo dups landing constantly, delayed OLD messages executed LIVE bubbles mid-stream — streaming was functionally deleted. Retire now requires the arrived content to CONTAIN the streamed tail (it IS the settle); beacon-only entries are never retired by arrivals. Also removed the last-sender bubble suppression — a persona speaking twice in a row is normal, and the skip hid exactly the streams being watched for. done-flag retirement unchanged. Web 21/21, rebuilt — ONE refresh. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01LoTjvf5j3Ez13g6k8mRkFo * fix(web): '(X) is responding…' clears when the answer lands — beacon-only entries retire on any arrival from their sender Joel, live: 'it didnt go away once responded.' Some settles never stream rail tokens, so the entry stayed beacon-only and its only exit was a done flush that never came. Beacon-only entries now retire on ANY arrival from the sender (a still-running turn's next token recreates the entry instantly — nothing lost); text-bearing entries keep the own-settle content match so delayed old messages can't kill live streams. Line lifetime == inference in flight: appears at generation dispatch, clears at settle. Web 21/21, rebuilt. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01LoTjvf5j3Ez13g6k8mRkFo * fix(web): responding line = the PROMISE phase only — a name drops the moment their words visibly stream Joel: 'if it is responding stop showing it, for that user — it's when we are sure they're gonna respond, then you can show it.' The grey line now lists only beacon-only entries (inference dispatched, nothing visible yet); once tokens stream into a persona's bubble their name leaves the line. Complete lifecycle: dispatch → '(X) is responding…' → words stream in the bubble → settle lands → everything clears. Web 21/21, rebuilt — refresh. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01LoTjvf5j3Ez13g6k8mRkFo * feat(web): dormant minds dim — roster rows recede when every cognition pulse is dark, brighten on any pulse/stream Joel: 'dim the entire row slightly in the user list.' A row with vitals wired but zero across focus/reason/recall/act/speaking is a resting mind: opacity 0.62 with a 0.9s ease, so waking is VISIBLE and the ~17s afterglow keeps recently-active minds bright — row brightness reads as recency of thought. Opacity-only (compositor-cheap); the dim treatment is the interim for #260's full presence lifecycle, where the universe/ theme layer owns the inactive look. Members without vitals (plain agents/humans) never dim on this signal. Web 21/21, rebuilt — refresh. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01LoTjvf5j3Ez13g6k8mRkFo * fix(tests): pin TZ=UTC in the four time-asserting specs — CI-deterministic on any runner PR #2057 review blocker: formatTimeOfDay became viewer-local (by design) but four specs still asserted fixed UTC HH:MM strings — red on any non-UTC runner. The formatter stays viewer-local; the specs pin process.env.TZ before imports. Proven under TZ=America/Chicago and TZ=Asia/Tokyo: chat-view 62/62, web 21/21. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01LoTjvf5j3Ez13g6k8mRkFo * fix(airc): close #261's SKIP hole — attach never pre-persists the room tip; the daemon's cursor heartbeat is the sole watermark writer Both PR #2057 review findings on the cursor re-land, fixed as one mechanism with airc 9390c32e8 (feat/attach-cursor-advance-heartbeat): 1. SKIP hole: the attach-time room_tip probe persisted a cursor for events not yet processed — a daemon Error frame or transport read error mid-backlog resumed PAST the tip, permanently skipping the unprocessed remainder from live perception. The probe is deleted. 2. Whole-session redelivery: the daemon's AttachCursorAdvanced now rides live streaming (throttled 1/s), so the existing persist arm — previously fed only once at the coalesce seam — advances the watermark continuously. Every advance points at an ALREADY DELIVERED event: resume is always at-or-before what this consumer processed. No skip, and the reboot redelivery window shrinks from the whole session to ≤1s of events. inbound_attach 8/8. Deploys with the rebuilt airc daemon binary; verification protocol: reboot twice, zero duplicate persona messages, watermark file advancing during live traffic. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01LoTjvf5j3Ez13g6k8mRkFo * chore(airc): airc.cursor.advanced probe — every watermark advance gets a receipt The #261 verification found a silently-stale watermark with no way to distinguish 'heartbeat frames never arrived' from 'persist failed quietly' — the arm logged failures only. Glass-box: success needs receipts too. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01LoTjvf5j3Ez13g6k8mRkFo * feat(cognition): predictive [settled] fact + room-speech ring — name the echo BEFORE it is born (#264) Glass-boxed live 2026-07-30: after the conway task completed, the room spent 40+ minutes in a full-room chorus — one sentence emitted verbatim by all three personas in sequence (specimen on #16/#259). The existing repetition facts are retroactive: they fire the turn AFTER the echo, one turn too late to prevent it, and closure statements re-trigger peers because a closure is still a new message. The room had no rest state. Two pieces, both precedented: 1. inbound_restates_fact — the PREDICTIVE member of the repetition family: fires when the NEWEST inbound peer message restates something already said (older visible turn, her own-speech ring, or the room ring), rendering "[settled] X's newest message restates what has already been said here … silence (PASS) is a normal response" BEFORE she replies. Same near_identical_substantial geometry as every other repetition axis (one definition), registered in the perception_facts registry (probe + A/B toggle for free). 2. record_room_speech / recent_room_speech — the room-side sibling of the #148 own-speech ring, and the same starvation fix: with live workspace windows of 2-6 turns, the older copy of every restatement had already scrolled out (verified: 0 fires across an entire live chorus until the ring landed). Recorded ONCE per message at the airc inbound-attach projection seam; the fact drops exactly one byte-exact copy so a message never matches its own record while a genuine re-send still fires. Live receipts post-deploy: perception.fact id=inbound_restates fired=true on all four room personas (one organic fire on their own chorus before the controlled probe ran); [settled] rendered in prompt captures; first fact-bearing tick redirected one persona from echo to a tool call. Behavioral compliance is partial by design — the fact names the fork, the mind chooses; sticky silence (the #264 scheduler half) is the follow-up. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01LoTjvf5j3Ez13g6k8mRkFo * feat(presence): durable room directory — grid citizens are grey when unreachable, never gone (#258/#262) Joel 2026-07-30: "Why won't bigmama's persona ever show up? Feels like you guys don't understand the goals." The goal is ONE directory per grid with cumulative citizens — a client that is a window into the whole grid. The implementation conflated membership with presence: the roster was rebuilt every 2s from a 120-second live window, so any citizen silent for 2 minutes ceased to EXIST. BigMama's citizens (Kimi, Sahar) were perpetually unborn on this node whenever their flaky relay dropped — existence gated on a live transport session. Fix — membership is durable, presence is live: - Per-room directory persisted at ~/.continuum/state/room-directory-<room>.json: every RosterSlotView ever projected, folded on each emit, seeded at boot by ONE deep transcript scan (14d/4000 events) so members whose last event predates the live window exist from the first publish. Steady-state daemon load unchanged (the 2s poll keeps the shallow window). - Published roster = live read ∪ remembered members as `active: false` ghosts with stale liveness signals (availability/vitals) cleared — the interface never lies about liveness (#260). Client renders ghosts dimmed via the existing `.member.idle` path: zero wire change, zero client change. - Identity adopted once: a real display name never regresses to the provisional peer label on a card-less sighting. - Persistence is the loop's concern, not emit_once's — tests stay disk-free (the #7 isolation lesson). Verified live post-deploy: presence.directory.seeded remembered=8 — ALL grid citizens recovered from the daemon transcript including Kimi (e2f0e022), Sahar (df72dbf2), and BigMama's agent (ce8b9074) while their node's inbound relay is down; web roster renders 8/8. Their names stay provisional until their card publish crosses (#262, their side) — and will be adopted permanently the first time it ever does. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01LoTjvf5j3Ez13g6k8mRkFo * feat(identity): publish every persona's airc identity card at birth — no more info-devoid citizens (#262/#248) Joel 2026-07-30: "Neither my user, all her persona, and you have any bio info, which should come over airc… devoid of all info persona." He was right, and the miss was pure wiring: the card system existed COMPLETE on both sides for months — airc's set_local_identity_card persists + broadcasts to every subscribed room, whois renders name/pronouns/role/bio, role_template carries hand-authored bio_templates in each role's voice, and the durable PersonaCard at birth holds name/gender/pronouns/role — but not one continuum path ever called publish. Every persona attached as a bare display name. Fix, at the single birth path (birth_one, right where the durable card is already read for avatar/voice registration — wire identity coheres with presentation identity by construction): - name from the card; pronouns from her presentation spine (profile facet override wins); role tagged continuum-persona-<role>; bio from her role's authored bio_template ({name} substituted), profile "bio" facet overriding; cards minted before role threading get an honest generic bio instead of silence; continuum_persona_id in integrations for cross-system binding. - publish failure is a warn + next-boot retry, never a birth-killer; success fires persona.identity.published. Verified live: probes for all four personas; airc whois now returns identity: published with name + pronouns + role + bio fo…
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BigMama (RTX 5090, native windows-msvc) becomes a live serving grid node. All validated live on the box:
cudaon Windows when cl.exe is reachable — degrades to directml instead of hard-failing the whole build (candle affine.cu needs nvcc→cl.exe)Contains #2053's commits until it lands (built + validated together on the live node).
🤖 Generated with Claude Code
https://claude.ai/code/session_01Q4NU4VNiELPQfBpCacDZGc