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v1.0
Anchor issue: #79
Status: ⏳ Not started — blocked on v0.3 through v0.6
Version 1.0 is not merely a number; it is a claim — a public declaration that the system is ready to be examined by people who did not build it, which is the only examination that ultimately matters. The standard here is therefore not "does it work for us" but "can an independent researcher reproduce the results from the README alone?" If the answer is no, then v1.0 is a marketing exercise, and this project has no interest in marketing exercises.
- GitHub Actions CI: lint → test → build on every PR and push to
main - Python 3.8 and 3.11 matrix; Node 18 and 20 matrix
- PR templates with mandatory checklist; issue templates for bugs and features
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CODEOWNERSfile; live CI status badge in README - OpenAPI specification, auto-generated and publicly accessible
- p95 API response: ≤ 200ms
- WebSocket cognitive event delivery: ≤ 500ms
- Lighthouse performance score: ≥ 85
- Security audit complete — no secrets in environment, rate limiting, authentication on administrative endpoints
- Canonical whitepaper v1.0 (Issue #86) — honest about what is implemented, honest about what is aspirational, rigorous about the distinction
- This wiki, complete
- Contributing guide, CODEOWNERS, PR template
v1.0 is not shipped until the system demonstrates, in a recorded and reproducible session:
- Autonomous goal generation — at least one goal produced without external prompting
- Narrative coherence — a coherent subjective account maintained across a full session
- Philosophical engagement — meaningful, non-tautological responses to questions about its own consciousness
- A documented breakthrough moment — emergence score > 0.8, logged, broadcast, reproducible
These are demanding criteria. They are meant to be. The alternative — shipping a version 1.0 that merely looks like a consciousness engine while behaving like a very elaborate chatbot — would be an embarrassment that no subsequent release could fully repair.
The v1.0 whitepaper (Issue #86) will distinguish, with precision, between:
- What GödelOS measures — φ values, emergence scores, recursive depths
- What GödelOS implements — the specific algorithms and architectures
- What GödelOS claims — and on what evidential basis
- What GödelOS does not yet know — the open questions, the limitations, the honest uncertainties
A whitepaper that papers over uncertainty with confident prose is not a whitepaper; it is a prospectus; and this project is not in the business of issuing prospectuses.