Posts tagged Verification — AI × software engineering, made practical.
You'll learn how to run and prepare for an interview round where candidates review an agent-generated pull request with planted bugs, and what a strong review looks like.
You'll learn where streaming belongs in an agentic system: buffer complete outputs between agents and verifiers, define an explicit commit point, and stream progress events to users instead of unverified tokens.
You'll learn a three-step method for spotting guesses in an AI answer: strip out the confident tone, tag where each specific detail came from, and push on any detail that has no source.
You'll learn when a reflect or critique step actually improves an agent's correctness, and how to replace the ones that don't with verifiers that use real evidence and can block a change.
You'll learn why plan-act-observe loops stall out at human review and how to design a real verification step that keeps pace with a fast generator.
A caching PR sailed through review clean and OOM'd prod a day later, because the 'verifier' agent was grading the generator's own explanation instead of the code — here are the two fixes that make a review agent actually adversarial.
Same class of agent mistake, same clean-looking diff, two identical-looking review processes — but only one team's safety net was actually built for a world where nobody's watching the code get written.
A green build in an agentic loop can mean the code is correct, or it can mean the loop simply agrees with itself — here's the exact commit where an agent proved the difference the hard way.