Halo – open-source, tamper-evident runtime evidence for AI agents
Hi HN, I'm Brian, I spent the last few years at Vanta (YC W18), helping startups and enterprises become compliant and I recently started exploring what that might look like in a post-agentic world.The problem Halo solves is: when a company buys an AI agent from a vendor and gives it access to their data, they have no way to check what the agent did with that data. Vendors may have built observability dashboards and audit logs, but those are editable and partisan. SOC 2 and ISO 27001 audit a company's controls, but controls are less predictive when the software is agentic. TLDR: give an agent the same prompt 50 times, and you get 50 slightly different actions/answers - so the only thing worth auditing in a post-agentic world is what happened at runtime.Halo is an open-source project that produces agent runtime evidence. It's a small recorder that records every action an agent takes (eg. tool calls, model calls, data access, etc), and becomes a record in an append-only log. It's hash-chained, so anyone can re-verify.Run the following command to see a fictional example: uvx --from halo-record halo demo --serve Then, delete a line from one of the .jsonl files and reload, and the report will catch that it's been tampered with.To wire up your own agent, run this line of Python: agent = trace(run_my_agent, profile="my-agent", log="audit.jsonl") Then use this to generate a real report and give it to your customers: halo report audit.jsonl -o report.html Disclaimer: this proves integrity, not completeness (as a self-held chain proves nothing was edited but does NOT prove that nothing was omitted). Catching this requires a witness outside the vendor and is what I'm working on next.Halo is Apache-2.0, contains zero runtime dependencies, and is about 4,300 lines of Python with 125 tests (if you prefer TypeScript, here's that repo: https://github.com/bkuan001/halo-record-ts).Give it a
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Verdict
high confidence
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Open-source tamper-evident audit logs for AI agents that prove what happened at runtime, not what vendors claim happened.
The pain
The gap
Build angle
Strengths
- Solves a real, specific problem that gets worse as agents proliferate, vendors can't self-audit their way out of this
- Technical execution is clean: append-only logs, hash-chaining, zero dependencies, open-source removes trust barrier
- Founder has direct compliance expertise from Vanta, understands what auditors actually care about
- Low friction to adopt: single Python decorator, generates HTML reports customers can share
- Honest about limitations (integrity vs. completeness) shows credibility
Risks
- Market timing: enterprises aren't yet deploying enough third-party agents to feel urgent pain. This solves a problem that matters in 18-24 months, not today
- Completeness problem is unsolved and non-trivial. Hash-chaining proves nothing was edited but doesn't prove nothing was hidden. Without external witnesses, the tool is incomplete for real compliance use
- Monetization unclear. Open-source + compliance tools = hard to charge. Halo could become infrastructure everyone uses but nobody pays for
- Competitive moat is weak. Once the problem is obvious, any compliance vendor (Vanta, Drata, etc.) can build this in 2 weeks
- Adoption requires vendors to instrument their agents. If vendors resist (to hide behavior), Halo only works for open-source or customer-built agents
- Regulatory uncertainty. Unclear if hash-chained logs actually satisfy compliance requirements or if regulators will demand something else
Fly Labs Method
Is the pain real, is there a gap, is it the right time, can one person build it.
Value Equation
Dream outcome and how likely it feels, against the time and effort it costs.
One-Person Business
Curiosity pull, identity fit, and a path from free value to paid for a solo creator.
Viral Frameworks
Hook strength, shareability, and how cheaply it can be tested.
Builder Lens
Evidence the problem exists, timing, defensibility, and a model that fits on a napkin.
Five lenses, one composite. How scoring works
The angle
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Semble – Code search for agents that uses 98% fewer tokens than grep
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