Show HN: ADRs for AI – Deliberation records for human–AI work, versioned in Git
ADRs4AI is a method and template for recording human–AI deliberation as versioned Architecture Decision Records in Git. Each record keeps the AI's options, recommendation, rationale, stated confidence, and falsifier, plus the human's ruling. Open questions are findable by grep, and tooling includes a VS Code extension, an MCP server, and an iOS client. The project positions itself as making the reasoning behind decisions persist across sessions and minds, rather than as persistent AI memory.
Open original source adrs.systemsOne primary source; other links are context, not independent corroboration.
- Primary sourceHacker News · AI
- Discovery linkHacker News
A community post points to the original link. Discussion and upvotes do not establish accuracy.
- Community discussion+5
- Fetched source page+30
- No editor link review0
- Community link0
This measures the stored source trail and editorial steps. It does not certify accuracy, peer review, or independent corroboration. Popularity adds no points.
View full scoring →Read the scoring rubric →What the source says
ADRs4AI is a method and template for recording human–AI deliberation as versioned Architecture Decision Records in Git. Each record keeps the AI's options, recommendation, rationale, stated confidence, and falsifier, plus the human's ruling. Open questions are findable by grep, and tooling includes a VS Code extension, an MCP server, and an iOS client. The project positions itself as making the reasoning behind decisions persist across sessions and minds, rather than as persistent AI memory.
A READER'S EVIDENCE CHECKHow to read this signalSix questions about claims, sources, risks, and open checks
This is a signal-level guide until claim-level evidence is available. “Not recorded” means the evidence has not been assessed here; it does not mean a result is false. How we check AI news →
- 01Who is making each claim?
The claimant and whether each claim was measured or asserted are not recorded in this public brief.
- 02What was actually tested?
Not recorded per claim. Check the source for sample size, tasks, model and benchmark versions, and reproducibility.
- 03Where are the sources?
Original link: adrs.systems. Brief basis: fetched source page. Primary page date and quote locations are not established in this panel.
- 04What could mislead?
Source claims not independently checked; the example record and project description are self-reported by the project's own site.
- 05What is at risk if wrong?
Not assessed per claim. Consider safety, privacy, cost, and adoption decisions before relying on the result.
- 06What would change the view?
No claim-specific check is recorded. An inspectable primary method or independent replication could change the assessment.
Key findings from the stored brief
- Each record captures options, a recommendation, rationale, confidence, and a falsifier for a question.
- Open questions can be found with a grep for the '### QST' heading pattern.
- Tooling includes a VS Code extension, an MCP server for agents, and an iOS client.
- The project explicitly does not claim AI systems gain persistent identity or memory.
Source claims not independently checked; the example record and project description are self-reported by the project's own site.
This is a source-based abstract, not independent validation of the source's claims.
Evidence & sources
These links show where the signal came from and what the source page linked to. A linked page is context, not independent corroboration.
A community post points to the original link. Discussion and upvotes do not establish accuracy.
Timeline & updates
- Signal dated by source or discovery feed
This timestamp places the signal in the radar. It may be the discovery post date rather than the primary page's first publication date.
- Shared brief stored
AINewsIQ prepared one abstract from fetched source page.
A publication revision history is not stored for this signal. New engagement snapshots do not mean the source itself changed.
Why this may matter
It offers a concrete practice for preserving the reasoning behind AI-assisted decisions, which usually disappears after sessions end. Versioning deliberations in Git makes the rationale auditable and resumable.
Limits and open questions
Source claims not independently checked; the example record and project description are self-reported by the project's own site.
Organization-specific financial, security, and operational effects require the organization's own context and review.
Discussion
Comments are reviewed before publication. Discuss the evidence, not the person.
No published comments yet.
Reader discussion opens with accounts. You can read the original source and published comments now.