ai-venture-studio 0.54.1

AI venture studio: a full-lifecycle multi-agent system that finds opportunities, writes PRDs, builds, launches, and measures — with typed claims and human gates

autoproduct — AI product autopilot

Finds what to build from your real signals. Sizes it honestly. Writes the PRD. Builds, tests, and reviews the product. Measures whether it worked — and forces the kill decision when it didn't.

A week of real product signals in — an evidence-gated product decision out:

signals.yaml — support tickets + GitHub issues, verbatim:

  s1  "I started a build and stared at the terminal for 40 minutes with
       no idea whether it was progressing or stuck"
  s3  "show live build progress per task in studio — right now it looks
       frozen while it works"
  s4  "can I send a preview of the built product to my cofounder, a link
       she can open on her phone"
  s6  "how much will a typical month of builds cost me? I'm scared to
       leave autopilot running"

    ↓  avs opportunity signals.yaml → market → prd → (build) → evidence

• ✅ 4 grounded candidates (Gate PL0) — every claim cites its ticket verbatim; each carries a falsifiable hypothesis and a named cheapest test ("ship a clickable mockup to the 3 reporters", not "build an MVP")
• ✅ A market assessment its own voters attack — the Sizing seat caught an ungrounded 0.15 affected-fraction inference; the Competitive seat caught "no competitor does this" resting on a single pricing-page probe; the dedicated Disconfirmation seat argues the other side on the same evidence
• ✅ A PRD with teeth (Gate PL2) — three kill criteria authored before anyone is attached, the sibling candidates explicitly listed as non-goals, and a Planning task auto-generated for the metric nobody had instrumented yet
• ✅ A machine-checked handoff into the build pipeline — Discovery reads exactly the PRD that passed the gate, or nothing
• ✅ An honest verdict (Gate PL4) — panel-open rate read at 24.0% (n=250, CI 19.1–29.7%) against a 30% kill threshold → insufficient_evidence: the interval brushes the line, so the system says "here's the n it would take to know" instead of declaring victory

(Every artifact above is unedited output from one real-provider run — see A real run below.)

Two loops, one system. The inner loop builds: apps, web services, and 微信小程序 from a single plain-language requirements doc (the FDR) — written by someone with no coding background, in their own words, English or Chinese. The outer loop decides: it mines your owned signals for opportunities, sizes markets bottom-up with mandatory sensitivity ranges, writes PRDs with required kill criteria, measures real cohorts through a privacy boundary, and routes every irreversible act — publishing, spending, shipping, killing — to a named human at a recorded gate.

Pick your door (one spine, three editions)

uvx avs replay --demo    # 2 minutes, NO API key: a real review's audit
                                 # trail, replayed offline — decide with evidence
avs init myco --profile web --edition solo         # or: enterprise | engineer

Editions are narrowing presets over the same unchanged pipeline — never forks, never fewer checks (edition_lint refuses anything that widens):

• Solo / OPC 一人公司 — built around your attention: one product bet, a 45-minute weekly review with the kill criteria first, safe publishing defaults.
• Enterprise / traditional industry — ships the procurement pack and the pilot-to-production contract; init refuses without a named gate owner.
• Engineer — fixture-gated extension points; nothing unfixtured registers, and you're invited to try to break that.

For founders (no technical background needed)

avs studio myteam --profile web    # browser UI: the whole flow

English is the default. --lang zh gives the original bilingual UI for 微信小程序 founders, unchanged (Chinese screenshot) — and your FDR may be written in either language whichever UI you choose.

Or the same flow in the terminal:

avs create myteam --profile web    # 1. writes FDR.md template + guide
# ← fill in FDR.md in your own words
avs create myteam --profile web    # 2. asks questions OR confirms the plan
avs create myteam --profile web --yes   # 3. builds everything
avs preview                        # 4. try your product
avs add feature.md --yes           # 5. one small FDR per new feature
avs ship                           # 6. deploy artifacts + plain-language guide

An FDR is six questions in your own words. This is the whole input for the screenshot above:

## 1. Who is this for?
The two of us running a small studio. Right now we track work in chat
messages and keep losing track of what is actually finished.

## 2. What do users do with it?
1. Anyone adds a task with a title and who it is for.
2. Anyone marks a task done.
3. We look at the open tasks and the finished ones separately, newest first.

## 3. Must-have features
Add a task. Mark a task done. See both lists.

## 4. NOT needed for now
Logins, due dates, notifications, a mobile app.

## 6. What does success look like?
The two of us stop tracking work in chat messages.

• If your FDR is unclear, the system asks — it never guesses (at most 5 questions a non-technical person can answer, in your language).
• One FDR = one thing. The first FDR is the smallest usable product; every later feature is its own small FDR via add. Granular builds are more accurate and fail more debuggably.
• You confirm intent in plain language before anything is built, and get a build report in your language after — including every automated approval the machine made on your behalf.
• Real persistence out of the box: a local SQLite database is provisioned automatically; cloud services (Supabase, WeChat Cloud / 微信云开发) are a guided option with credentials in a vault that never enters prompts.
• Profiles carry domain rules: web (CSRF/SSRF, a11y, E2E flows), mobile app (store rules, offline behaviour), game (simulation determinism, replay identity, bot playtests), data (freshness/row-count NFRs, lineage), and WeChat mini-programs / 小程序 (2MB package budget, domain whitelist, lazy authorisation with a privacy agreement, review boundaries).

For product decisions (the outer loop)

avs opportunity signals.yaml         # P0: cluster real signals → candidates, Gate PL0
avs market cand-x --evidence probes.yaml   # P1: bottom-up sizing, six voters incl. Disconfirmation
avs market-approve --outcome pursue --scope-tier thin --decider you   # Gate PL1 (human)
avs prd                              # P2: PRD with kill criteria, planning tasks generated
avs prd-approve --decider you        # Gate PL2 + machine-checked handoff into the build
avs evidence events.yaml --metric build_progress_view_rate --cohort-start 2026-07-10

The rules that make it trustworthy are structural, not aspirational: every quantitative claim is typed and machine-linted (claim_lint — unsourced numbers, causal-language-without-a-holdout, and missing falsifiers fail the gate); agents may never author a user quote or persona; sizing is a range, never a point; person-level data cannot leave the analytics boundary (the query errors); experiments are hash-pinned before exposure; the framework never publishes, sends, or spends autonomously; and a fired kill criterion cannot be closed without a recorded human decision.

What happens under the hood

Fourteen gated stages across two loops (design docs: autoproduct-design): Every doc is cross-referenced to its shipped mechanism in the implementation map — open items are named, never silent.

Outer loop (weeks-to-months): Opportunity sensing (deterministic clustering of owned signals, kill-registry memory) → Market & viability (standing-checked probes, injection_scan over snapshots, a red-team Disconfirmation voter) → PRD (kill criteria required at authoring time) → … → Product evidence (cohort reads through a k-anonymity boundary, attribution typed at the tool boundary) → Portfolio (mechanical kill-criteria evaluation, append-only kill registry).

Inner loop, upstream: Discovery (evidence-tagged hypotheses — fabricating user evidence is a schema violation) → Planning (task DAG with cycle/lane/budget checks) → Spec (EARS criteria machine-linted, every criterion covered by a test skeleton, frozen behind SCRs) → Coding (single-writer, test-first, AST-checked no-test-weakening, sandboxed suite must pass).

Inner loop, downstream: Code Review (6 heterogeneous voters, deterministic probes for secrets/CSRF-SSRF/slopsquatting/wireup drift, every finding independently verified) → Test Gate (isolated worktree, mutation testing in deep mode) → Deploy Review → Maintenance (triage → root cause → fix-PRs whose regression tests must fail pre-fix).

Every generative stage runs the same template: one writer, deterministic tools first, independent charter voters (each fixture-gated at 8 cases, ≥87.5% to register), a fresh verify pass per finding, a leader synthesis, and a gate — human wherever judgment is the point. Nothing auto-merges, nothing deploys autonomously, nothing publishes, nothing spends.

A real run (unedited)

Everything below is real-model output from one end-to-end run of the opportunity chain (opportunity → market → prd → evidence) on the signals shown at the top of this page. Signal texts and competitor-probe pages are fixtures; every judgment, artifact, and number below was produced by the pipeline, unedited.

1. P0 turns four signals into grounded candidates (Gate PL0 passed):

cand-build-progress — Users cannot tell whether an in-progress build is advancing or stuck, so they need live per-task progress visibility.

• hypothesis: live per-task progress stops long builds reading as frozen
• falsifier: a prototype does not reduce "is it stuck?" reports
• cheapest test: ship a clickable mockup to the 3 ticket reporters and count how many confirm it resolves their "frozen" uncertainty

2. P1's own voters attack the market case (three verified majors):

"…the revenue sizing hinges on an ungrounded 0.15 affected-fraction inference multiplied against the real 900-workspace base, the price-headroom positioning rests on only two vendors, and the Vendor B absence claim relies on a single pricing-page probe rather than a proper probe list."

The deterministic gate had already blocked an earlier draft outright: 75% of its claims were model_inference against the 30% market ceiling — reasoning dressed as research doesn't pass.

3. P2 writes a PRD with its own death spelled out (Gate PL2):

• kill: "fewer than 3 of 3 mockup reporters confirm it resolves their 'frozen' uncertainty"
• kill: "build_progress_view_rate stays below 30% after 30 days"
• non-goals: the sibling candidates, by name (shareable previews, cost visibility, dark mode)
• generated Planning task: instrument build_progress_panel_viewed so O-1 is measurable before launch

4. P4 reads the cohort and refuses to flatter it (Gate PL4):

build_progress_view_rate: 0.240   n=250   CI [0.191, 0.297]   window complete
verdict H-1: insufficient_evidence — the interval brushes the 30% kill
threshold; the honest output is the n it would take to know, not a win.

The same machinery runs the other direction too: the inner loop's product benchmark (product-bench) builds full products from plain-language FDRs (English or Chinese) and scores them with independent behavioral probes, reported unaveraged — including the runs that fail.

Measured

• Review benchmark (avs bench): recall 100%, precision 67% on 13 labeled cases (bars: 40%/50%).
• Product benchmark (avs product-bench): full FDR→product runs scored by independent behavioral probes executed against the built product (WebGen-Bench pattern) — build rate, probe pass rate, and clean-review rate reported unaveraged, with an honesty case proving probes can fail.
• 1071 hermetic tests (uv run pytest); every PR in this repo was reviewed by avs itself, and five of those reviews caught real bugs. The first live smoke of the outer loop surfaced three wiring bugs — each caught by a gate doing its job, each now a regression test.

For developers

opportunity · market / market-approve · prd / prd-approve · evidence	the outer loop as one-command stages: writer → det tools → charter voters → verify → leader → gate; human decisions recorded at PL1/PL2
voter-gate <stage> · review-gate	register voters against their 8-fixture gates (≥87.5%); failed voters stop voting — review-gate covers the six review seats, voter-gate every other family
claim-lint · prd-lint · handoff-check	outer-loop gates standalone: claim ledgers, PRD boundary/kill-criteria/instrumentation, the machine-checked P2→Stage-1 handoff
preregister · experiment-check	pin an experiment design before exposure; schema + FDR plan + power + pin integrity
discover / plan / spec / build (+ *-approve)	inner-loop upstream stages, gates U1–U4
scr / scr-approve	the only legal way to change a built spec
review · resume · recover · replay	review pipeline, HITL, crash recovery (reviews, deploy reviews, and incidents all resume from their checkpoints), audit trail
deploy-review · deploy-outcome · triage [--fix]	Gates 5–6
automerge · deploy-execute	merge/deploy only under a human-armed, attributed, expiring policy — disarmed by default (ADR-031)
serve · worker · tenant	webhook mode + queue workers (SQLite, one host); tenant add fronts several isolated workspaces from one process (ADR-030)
botfleet	bot playtests: N parallel sessions, triaged and deduped, each finding with a reproduction command — crashes and stuck states, never whether the game is fun
bench-criterion	the capability kill criterion (PRD O-L2): has product-bench fallen below its floors for two consecutive runs?
attention	the weekly maintenance-attention series the launch PRD's kill criterion is falsifiable by: the machine measures the observable floor from the ledgers, you log the hours
loop	where the live product cycle stands against the v3.0.0 design gate (runbook) — states, never decides
bench · product-bench · compound --pr	the two benchmarks + the compounding loop

Install: pip install autoproduct (PyPI) — the published distribution is still named autoproduct; the rename to ai-venture-studio lands with the next release, and the avs command ships with it (the autoproduct command stays as an alias) — or clone this repo for the benchmarks, voter fixtures, and bench history.

Setup: uv sync, then your own ANTHROPIC_API_KEY. The repo ships no keys, no proxy, and no metered backend: every provider call is billed to the keys in your environment, keys are never written to the workspace or git (the secrets layer resolves secret://ENV references loudly and scrubs resolved values from outbound text), and every provider errors loudly if its key is missing rather than running half-armed. OPENAI_API_KEY optional but recommended: it puts a real GPT-5 in the security and deploy-config voter seats, breaking same-family self-preference when Claude reviews Claude-written code; without it those seats visibly fall back (substituted_from). GEMINI_API_KEY/XAI_API_KEY optional likewise. Optional AUTOPRODUCT_CHECKPOINT_KEY encrypts checkpoint rows at rest — honored or a loud error, never a silent plaintext fallback. Optional AUTOPRODUCT_TOOL_TRANSPORT=mcp runs voter tools in subprocess-isolated MCP servers instead of in-process (ADR-029); in-process is the default because a spawn per server per invocation is a real cost you should choose deliberately. gh auth, Docker optional (network-isolated test sandbox), Node optional (JS test gate). Operations guide: RUNBOOK.md.

Honest limits (today)

• The outer loop runs end-to-end and survived its first real-provider smoke, but its release bar is honest: it is unproven until a real Gate PL5 records a real kill or pivot on a live cycle.
• Cloud services are guided, not auto-provisioned; deploys generate artifacts + instructions, and the button stays yours until you arm a policy that says otherwise (ADR-031 — disarmed by default, attributed, expiring).
• 小程序 page-level testing needs miniprogram-simulate installed; pure-logic modules are gated via node --test today.
• Single-machine operation; crash recovery resumes reviews, deploy reviews, and incidents from their checkpoints, but Celery/Redis multi-instance supervision remains the documented upgrade path.
• Multi-tenant isolation is filesystem-and-routing level, not OS-level: a Python-level RCE in the harness would cross tenants. If that is in your threat model, run one process per tenant (ADR-030).

Roadmap

v0.8 → v0.30 — the four downstream MASes, the founder autopilot, the adoption track, the outer product loop, domain profiles, the Sweep role, and the two audit gap-closure passes (22 releases, expand for the record)

v0.8 ✅	all four downstream stage MASes (code review, test gate, deploy review, maintenance)
v0.9 ✅	greenfield autopilot for non-technical founders (FDR → product)
v0.10 ✅	founder experience complete + measured (Studio UI, product benchmark)
v0.11–v0.12 ✅	traditional-industry adoption track + hardening
v0.13 ✅	product-loop substrate: typed claim ledger, claim_lint, evidence snapshots, synthetic-persona scan, source standing, user_data_taint
v0.14 ✅	safe-publish: the seven deterministic marketing backstops, channel profiles, Gate PL3 scoped approvals — a human presses every publish button, and it never spends money
v0.15 ✅	evidence: analytics/feedback privacy boundary, metric vocabulary with baseline-resetting definitions, cohort reads with sufficiency teeth, attribution typed at the tool boundary — only holdouts ground causal claims
v0.16 ✅	upstream P0–P2: opportunity sensing, market & viability, PRD with required kill criteria, machine-checked handoff into Discovery
v0.17 ✅	experiments: hash-pinned pre-registration, two-stage FDR-controlled screening→validation, sequential peeking, guardrail vetoes, inconclusive-enters-nothing
v0.18 ✅	closed loop: evaluate_kill_criteria (a fired criterion cannot close without a recorded human decision), append-only kill registry, hypothesis reconciliation, the five loop metrics
v0.19–v0.20 ✅	the outer loop operable end-to-end: gate CLIs, then the four LLM stages as one-command runs; first real-provider smoke (three wiring bugs found by gates, fixed); 24 voter fixture-registration gates + voter-gate
M2–M7 ✅	build screenshots (gated-visible), in-Studio correction loop with SCR-backed scope changes, 验收清单 walkthrough, telemetry + digest, 微信支付/登录/订阅 blocks, estimate hints + undo
v0.21 ✅	platform editions + distribution (docs 24–25): init --edition with narrowing-only edition_lint, the three START-HERE doors + weekly founder review + procurement pack, replay --demo (a real audit trail, offline, no API key), --from-bench templates that are the benchmark fixtures, opt-in aggregate-only telemetry, the published benchmark page, and ADR-U29: this README is checked against claims/platform.yaml by the test suite — asserting beyond the ledger fails the build
v0.22 ✅	the launch pass, prepared (P20): launch/ holds the platform's own PRD (kill criterion: 4 weeks over the attention budget cuts scope at Gate PL5), a launch post that survives all its own backstops, and a hash-pinned pre-registered experiment whose power check honestly returns BLOCKED at current traffic — the suite keeps all three green; plus CONTRIBUTING (gated contributions, bus-factor-1 honesty, watch items with falsifiers)
v0.23 ✅	complex-systems gap closure, deterministic core (docs 26–28, P21–P26): lintable perf ACs + VALID/INVALID load-run typing + capacity.yaml headroom arithmetic (perf lane calibrated: see roadmap v0.24); realtime delta (det_sim_scan, replay-identity/cross-build/desync checks, tick budgets); streaming delta (stream_contract_check — the word "default" is lexically illegal, exactly-once typed-or-downgraded, backpressure scan); architecture fitness (deps.yaml graph → arch_contract_check, brownfield checkpoint debt); delivery hardening (environment promotion DAG, flag_lint with owners+expiry, migration_rehearsal with reversibility round-trip)
v0.24 ✅	lane execution wrappers + calibration: k6 scripts compiled from perf ACs (thresholds ARE the AC; absent binary = visible skip with the script on record), netem condition profiles with gated apply, schema-registry wrapper + contract-file reconciliation — and the seeded perf-defect calibration ran for real: 5 of 5 defects caught at the 3x relative-detection factor (loopback, low parity, honestly scoped — satisfies no AC), converting the lane from PROVISIONAL to CALIBRATED
v0.25 ✅	the Sweep role (doc 29): avs sweep harvests the maintenance queues the ledgers already keep (expired flags, checkpoint debt, stale claims/capacity, due watch items, contract drift), patches only allowlisted chores under the behavior-preservation contract (out-of-scope diffs abort), caps open PRs to the attention budget, records clean passes with a snapshot hash, and alarms on over-action — SW0 report-only by default, promotion is your recorded decision at the weekly review
v0.26 ✅	full design-doc cross-reference (docs 08–29 audited against the code): the implementation map records every doc's shipped mechanism, tag, and named open items; gap-closure code from the audit — operations-policy.yaml (per-stage WIP + the shed rule + ci_concurrency), the hot-files.yaml shared-file registry + lane_check, the four 小程序 preflights (mp_size_check/mp_domain_check/mp_setdata_lint/mp_privacy_check), and profiles/game.yaml
v0.27 ✅	audit gap closures, round two: GitHub Actions CI (the suite — including the self-linting README — now runs on every push, making "fails CI" literal), the §41.1 structured profile schema (add-only, composable), doc-16's cascade policy with the model-family heterogeneity floor + serial merge-queue admission (sweep never starves features) + the gepa.yaml budget schema (proposer-off by default), and the debt tools (radon/jscpd/vulture, availability-gated, feeding Sweep's queues)
v0.28 ✅	gap-closure plan + phase A (the plan is a committed artifact; phases B–D queued): web det-tool runners (axe/Lighthouse/size-limit, gated), the data NFR grammar + lineage impact check, the full typed upstream verdict vocabulary, Gate P1 platform preflight (stale checklists and evidence-free checkboxes both fail; a named human submits), data-classification tags with downgrade refusal, and CHANGELOG.md
v0.29 ✅	plan phase B: five profile voter charters (web DesignFidelity/A11ySemantics/PerformanceDelta, 小程序 PlatformFit, app DeviceReality) and 8-fixture registration gates for them AND the three data voters — voter-gate web|miniprogram|app|data now serves every family under the same 87.5% contract
v0.30 ✅	plan phase C: the cost/observability ledger (prices are config never constants, unpriced calls counted never zeroed, the monthly cap warns and a human decides; per-review tool-audit + evidence-ledger receipts; /metrics in Prometheus text, aggregate-only), the module-spec invariant layer (.mas/specs/*.spec.yaml — SPEC_DRIFT_UNDOCUMENTED on unexpected change patterns, forbidden side effects scanned in diffs), and named signal webhooks (/webhooks/sentry|datadog|pagerduty → the incident inbox, bearer-authed, deduped)

v0.31 ✅	plan phase D, first half: the GEPA proposer loop (budget-gated by gepa.yaml, holdout-scored through the same fixture gate voters register through, proposal records only — nothing self-installs) and the secrets layer (secret://ENV loud resolution, masked repr, outbound scrub)
v0.32 ✅	plan phase D13: the discover/plan/spec critics as fourteen registered charter voters on the shared stage engine (each behind its 8-fixture gate; failed gates exclude the voter, unregistered voters are reported), retiring the single-panel critique prompts — voter-gate discovery|planning|spec
v0.33 ✅	plan phase D15 + D16 remainder: deploy review and maintenance rebuilt as checkpointed graphs on the shared saver — a crash mid-vote resumes from the last completed super-step via recover instead of re-paying the pipeline — and checkpoint rows encrypted at rest under AUTOPRODUCT_CHECKPOINT_KEY (honored or loud error, never silent plaintext; mirrors stay readable on purpose)
v0.34 ✅	Studio live progress + the wire-up gate: the building page shows per-task state updating in place (signals s1/s3 — no more staring at a frozen page), interrupted builds surface per-module 继续 buttons instead of a dead confirm screen, and a bidirectional frontend↔backend wire-up test — every rendered button/link/fetch must resolve to a route, every route must be rendered by some state
v0.35.0 ✅	the last small open items: registration gates for the six review voters (8 fixtures each, run through the real seat; the vote node fails closed and refuses to review with no roster), per-project policy: thresholds in project.yaml (unknown keys are a loud error, ranges bounded, a weakened bar stamped into the verdict), and the ready-queue fix — next_tasks read a field that never existed, so the plan never advanced past task one
v0.36.0 ✅	the instrument for the v3.0.0 design gate: avs loop reads the cycle's own artifacts and reports the three criteria — and refuses to call the gate met on a quiet cycle or a recorded 'continue', because the gate is about the loop's ability to stop (runbook)
v0.37.0 ✅	MCP becomes the real internal tool transport (doc 11 §17): two subprocess-isolated partitions (read_only, code_intel) speaking JSON-RPC over stdio, the spec→host→server triple check where an unlisted tool is unreachable rather than refused, and the mcp-audit ledger recording every call with digested arguments — opt in with AUTOPRODUCT_TOOL_TRANSPORT=mcp
v0.38.0 ✅	multi-tenant server mode (ADR-030, a recorded reversal of a non-goal — the server half only, never SaaS): token→workspace resolution where workspaces must be provably disjoint, per-tenant secret:// webhook secrets, tenant-scoped reads, and uniform 401s that never enumerate tenants; plus docs/adr/ recording every reversal
v0.39.0 ✅	policy-armed automation (ADR-031, the hardest reversal): automerge and deploy-execute exist but stay disarmed until a human writes an attributed, expiring policy naming exact branches — earned by track record, blocked on sensitive paths including the policy files themselves, and logging refusals as carefully as actions
v0.40.0 ✅	the L1/L2 MCP partitions (deploy probes, maintenance correlation, and test execution — five subprocess servers now) with risk-tier RBAC: a partition above the caller's declared ceiling is never mounted, and the audit ledger finally covers the tools that touch the most; plus the deploy-branch fix, where an unresolvable branch is a refusal rather than an assumed main
v0.41.0 ✅	the Context Manifest (content-hashed context assembly, grounding receipts where an unread contract is a violation, drift detection that refuses to build a spec edited outside the SCR channel, and overflow routed to Planning as a split) and research-session taint isolation (ADR-U03: consume research and the run loses L1+ tools for good, enforced at the transport rather than in a prompt)
v0.42.0 ✅	grounding enforced on every build: the manifest is assembled, recorded, and checked against the prompt, so a required contract that never reached the writer blocks the build — which immediately found that module-spec invariants were absent from the implementer's prompt while Code Review enforced them, and they are now quoted verbatim
v0.43.0 ✅	the first external-service tool (sentry_get_issue in the L1 maintenance partition): credential via secret://, a visible skip when unset, read-only by construction, and its payload wrapped as untrusted research so a hostile issue title is data rather than an instruction — wired into incident intake, and honest that it has not yet run against a live org
v0.44.0 ✅	all six §17.2 signal readers (sentry, datadog, pagerduty, prometheus, loki, jaeger) over one shared read-only core, with two honestly-distinguished gating families — credential for hosted services, base URL for self-hosted ones, and a visible skip naming the variable either way
v0.45.0 ✅	the deploy-side CLI wrappers (terraform/helm/kubectl/argocd/flagger/railway) complete §17.2's tool table: binaries gated on installation rather than credentials, read-only by construction (no sync/rollback/apply outside --dry-run, asserted on the source), and kubectl_dry_run client-side by default so a review never silently reaches into whatever cluster is current
v0.46.0 ✅	the attention collector: avs attention derives the observable floor from gate dwell and recorded decisions, refuses to author the number itself, keeps the series append-only, and exits 3 demanding a human decision the moment four consecutive logged weeks breach the budget — the v3.0.0 blocker was an unautomated habit, not a missing four weeks
v0.47.0 ✅	the bot fleet (doc 17 §45.2's last unbuilt check): defined by a session protocol rather than by a game, so its detectors are verified against real sessions of a real deterministic sim — and the first real run immediately found a dedupe bug that a stubbed stream would have hidden
v0.48.0 ✅	upstream resume (a crashed create skips tasks already built instead of re-paying them — task-granular, and said so plainly), grounding extended to the spec writer (which immediately showed the spec writer never saw CLAUDE.md or the module invariants it must not contradict), and the gap-closure plan closed out
v0.49.0 ✅	the use-case matrix: every profile builds, every edition narrows, every substrate rung activates exactly what its floors allow — which found that six of eight stages knew their infrastructure floor without enforcing it (an S0 team with no git could still run build), now fixed and pinned in both directions
v0.50.0 ✅	loop and attention joined: the gate report now names the real distance to firing and the exact command to run next, and reports a not_tracked week as the recorded decision it is rather than as logged or as a gap
v0.51.0 ✅	a second kill-criterion axis, chosen by the human and evaluated by the machine: product-bench capability regression, whose series is already collected weekly — so unlike the attention axis it can fire on the next run, with floors read off the observed distribution rather than picked
v0.52.0 ✅	the Studio speaks English (--lang en): every string in a per-language table, an English FDR template, and the README's founder demo replaced with an English-first walkthrough plus a real screenshot of the real UI — the demo previously claimed English while showing a Chinese interface
v0.53.0 ✅	renamed to ai-venture-studio (live links updated; recorded evidence locators left as recorded, with a rename note, because a snapshot is not edited after the fact) and English became the Studio default — --lang zh restores the original bilingual UI character for character
v0.54.0 ✅	package + CLI renamed to match: import ai_venture_studio, command avs (with autoproduct kept as an alias so nothing scripted breaks) — while env vars, Prometheus series, telemetry keys and the CLAUDE.md section header were deliberately left alone, because renaming a wire format silently breaks its consumers
next 🔜	the v3.0.0 design gate itself: this repo's cycle sits at V3-1/V3-2 met, V3-3 pending — the launch PRD's kill criterion needs four consecutive logged attention weeks, and a human records the decision

Star history

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MIT · design docs: autoproduct-design