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Slaine

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Show HN: I built a tamper-evident evidence system for AI agents

guardianreplay.pages.dev
2 points·by Slaine·4 maanden geleden·2 comments

Show HN: Deterministic NDJSON audit logs – v1.2 update (structural gaps)

github.com
1 points·by Slaine·5 maanden geleden·0 comments

Show HN: Deterministic event logs with explicit gap markers (NDJSON proof)

github.com
1 points·by Slaine·5 maanden geleden·1 comments

Show HN: A small reference demo for separating UI stalls from network delays

deterministic-stream-demo1.pages.dev
1 points·by Slaine·6 maanden geleden·1 comments

comments

Slaine
·4 maanden geleden·discuss
Yeah, totally agree. Integrity mostly answers the “what happened” part.

The idea is that once the sequence of events is provably intact, you can attach the decision context to it — things like policy snapshots, inputs/prompts (or hashes of them), and state transitions.

Then the evidence layer proves the history wasn’t altered, and analysis tools can reconstruct why the system made a particular decision from that preserved context.

The demo focuses on the integrity layer because without that everything else turns into “trust our dashboard.” Interpretability tools can sit on top of the same evidence
Slaine
·5 maanden geleden·discuss
To be clear: this repo is proof-only.

The idea was to see whether the artifacts themselves (two NDJSON logs) are convincing without explanation. If they’re not, I’d really like to know why.
Slaine
·6 maanden geleden·discuss
Small clarification: the demo is intentionally boring and minimal. The point isn’t the UI — it’s the exported trace.

I’ve been running the same test multiple times with the same seed and network profile and diffing the JSON. The timings move, but the event structure doesn’t, which helped me reason about cause vs effect more clearly.

If there are existing tools or workflows that already give you this kind of repeatable structure, I’d genuinely love pointers.