Research

Molt Research.

Research, benchmarks, and field intelligence on AI agent assurance. Enterprises are shipping agents faster than anyone can verify what they’ll do — that gap closes evidence first, or incident first. This is where we think out loud about the first path.

Featured · White Paper

Can your AI agent be persuaded to cross the line? →

The technical white paper behind Fisher: adaptive multi-turn testing, action-level evidence, replay, remediation re-attack, and a learning strategy graph, documented across 50,000+ retained research episodes as of July 2026.

Read the overview and download the PDF →

Start here

The two things to read first.

From the blog

Field notes on testing AI agents.

Every post carries one proof, ranks on its own, and links back to the methodology.

What we write about

Five lanes, one standard: prove more, assert less.

Pillar
The assurance gap
The market reality where the agent wave meets enterprise verification capacity.
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Risk, measured
A quant’s lens on agent autonomy — and why “it passed evals” is not a risk statement.
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From the field
Anonymized patterns from real Fisher work: what actually breaks, never who.
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The independent’s view
Commentary on consolidation and what vendor-neutrality means for assurance.
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Builder’s notes
Honest lessons from building assurance tooling, including what’s still research.

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