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EPIC E5 0.73: Train What You Serve  #4000

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Description

@noahgift

owner: aprender-w5382 (set 2026-10-19 by aprender-triage-worker at the cop's word; picks up children only as batch constituents after its current timed task)

Spec: APR-EPIC-001 §2 · Epic: E5 · Train: 0.72 · Successor at cut: E6

Theme

Train What You Serve (was: Agent Ready; operator ruling 2026-09-27, APR-LOOKAHEAD-001 §2a)

done_when

Current exit criteria (APR-LOOKAHEAD-001 §2a): T1 apr finetune (QLoRA), apr distill, apr merge, apr quantize complete end to end on Qwen 3.5 with 0 refusals (the qwen35 refusals are removed) · T2 fine-tune throughput ≥ 0.8× Unsloth on the same GPU and model, with a committed measurement command · T3 Prometheus B2: one challenger (local Qwen3.5-27B teacher → 4B student, gold labels only, 0 sealed-test hashes in training data) judged by PRM-001 §5.4 · T4 first improved dogfood model published to Hugging Face as an rc with receipts (EXT-001) · T5 trained weights round-trip gguf ↔ safetensors ↔ .apr at cosine ≥ 0.98

Rows from the old theme that do not fit move to milestone backlog (cop 2026-09-27).

Superseded done_when (old theme): /v1/chat/completions and /v1/messages pass one conformance suite; tool calls; --json-schema; used_gpu provenance on every response.

Budget

At most 5 open children (docs/roadmaps/epics.yaml). Repo-wide cap 100 open issues; andon at 95.

Absorbs

—

Prior body

Theme: Agent Ready (operator 2026-09-23): one gateway serves all agents

apr serve is the single gateway every agent talks to: OpenAI-compatible (/v1/chat/completions: tools, streaming, seeds) plus an Anthropic Messages adapter (/v1/messages), which the operator approved ("yes to 1"). It is one per host and pinned by binary sha. Fleet consumers (quorum local lane, arbiter ask/decide, cookbook recipes, external harnesses) use ONE client contract, never CLI invocations. CRUX measurement uses a dedicated instance, never the shared gateway.

Exit bar. One conformance suite (OpenAI + Anthropic shapes, tool calls, streaming finish/[DONE], seeded reproducibility) passes on every model × backend that 0.71 certifies. An agent harness (Claude Code via /v1/messages; Alfredo's via OpenAI) completes a tool-calling task end to end against it.

Must-carry

Area Items
Tool calling #3825
Reproducible sampling #3760, #3786, #3754
Honest telemetry #3718, #3981, #3598 row 1
Serve surface #3979 (.apr routes, SSE [DONE]/finish_reason), #3978 (apr code), qwen3moe verbs (#3987) if not closed earlier
Anthropic adapter /v1/messages in apr serve, with its conformance rows
Protocols OpenAI + Anthropic conformance suite in CI; MCP server (#2794)
Ratchet slice 3 of 5 #3997

Open decision

  • Consumer migration (infra quorum lane, arbiter, paiml-implement) in 0.72, or aprender ships the gateway and conformance suite and the other repos migrate after?

Members not listed above (62, every other open 0.72.0 issue)

Rule (operator 2026-09-24, applied by the cop aprender-cf): a milestone is an epic only if this issue lists its members, and tickets without an epic go to backlog. This list was derived from the milestone's open issues on 2026-09-24 by aprender-dd (#4159).

Parked

Closed over budget (APR-EPIC-001 rule 5). Reopen = pull (rule 7).

0.7x schedule (release-schedule-07x, 2026-10-08)

Train 0.72.0: plan cut 2026-10-26, tag 2026-10-27 (plan dates, not measured). Report: docs/reports/0.7x-epic-reports.md.

Open children kept in 0.72.0 (owners are proposals; the cop assigns):

Children tracked here (REDUCE-1022)

Activity

  1. added this to the 0.72.0 milestone on Sep 23, 2026
  2. noahgift commented on Sep 23, 2026

    @noahgift
    MemberAuthor

    Plan posted: PR #4012

    Measured today: 0 /v1/messages server routes and no conformance suite. The OpenAI contract has 57 entries. Quorum: 3 lanes, all gemini (the gpt pool is 429 until about 09-27), so the result is advisory. Nothing is applied: no child issues and no milestone moves. The PR is not armed.

    • Consumer migration was decided 3/3: the gateway and suite ship in 0.72; exactly one consumer, the infra quorum local lane, migrates in 0.72; the others migrate after 0.72, gated by the same suite.
    • Also decided: one internal event stream with OpenAI and Anthropic encoders at the edge, and qwen3-1.7b-q4km as the CPU CI model.
    • Ratchet slice 3 is included.
  3. noahgift commented on Sep 24, 2026

    @noahgift
    MemberAuthor

    Folded into this epic by issue triage (evidence /mnt/nvme-raid0/cop-inbox/evidence/triage-1623.md). Each row was a separate issue, now closed as folded; reopen any if it needs its own thread:

  4. changed the title [-]EPIC 0.72.0: Agent Ready — apr serve is the one gateway for all agents (OpenAI + Anthropic /v1/messages), one conformance suite[/-] [+]EPIC E5 0.72: Agent Ready[/+] on Sep 25, 2026
  5. changed the title [-]EPIC E5 0.72: Agent Ready[/-] [+]EPIC E5 0.72: Train What You Serve[/+] on Sep 27, 2026
  6. noahgift commented on Sep 27, 2026

    @noahgift
    MemberAuthor

    Re-themed by operator ruling 2026-09-27 (APR-LOOKAHEAD-001 v1.1 §2a). Old theme was "Agent Ready"; the L2 worker re-homes its rows (move, never copy) and proposes the result to the cop. 0.72 exit criteria:

    • T1 apr finetune (QLoRA), distill, merge, quantize run end to end on Qwen 3.5 with 0 refusals
    • T2 fine-tune throughput ≥ 0.8× Unsloth on the same GPU and model, with a committed measurement command
    • T3 Prometheus B2: local Qwen3.5-27B teacher → 4B student, gold labels only, 0 sealed-test hashes in training data, judged by PRM-001 §5.4
    • T4 first improved dogfood model published to HF as an rc with receipts (EXT-001)
    • T5 trained weights round-trip gguf ↔ safetensors ↔ .apr at cosine ≥ 0.98
      L2 look-ahead worker: la-72.
  7. 69 remaining items

  8. noahgift commented on Oct 14, 2026

    @noahgift
    MemberAuthor

    Agent Ready moved to 0.73.0 and is tracked in #5348. The R-3/4/5/7/8/9 state and the unowned rows are posted there. Agent: aprender-w4664

  9. modified the milestones: 0.72.0, 0.73.0 on Oct 14, 2026
  10. changed the title [-]EPIC E5 0.72: Train What You Serve[/-] [+]EPIC E5 0.73: Train What You Serve [/+] on Oct 22, 2026
  11. modified the milestones: 0.73.0, 0.74.0 on Oct 30, 2026
  12. modified the milestones: 0.74.0, 0.75.0 on Oct 30, 2026
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