Learning from experience01
The Quality Flywheel
How failures become experiments, better decisions, and knowledge that survives the next release.
By Chaitanya · Systems engineering
Engineering the systems that make agents work.
I’m Chaitanya. I build autonomous agents and the infrastructure around them: local context, reliable execution, and reproducible evaluation. Oddly connects the architecture, experiments, and engineering decisions behind that work.
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Agent infrastructureLocal contextObservabilityReproducible evaluation
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Classification & measurement02
Classifiers: When Labels Become Decisions
Ten chapters on designing categories, choosing evidence, measuring errors, and deciding when a label deserves to influence what happens next.
Context, experience & judgment03
How Intelligence Finds Its Way
Five essays on the worlds intelligence can read, the questions it asks, the experience it carries, and the actions it can afford to try.
02
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Recent writing
The Quality FlywheelHow failures become experiments, better decisions, and knowledge that survives the next release.
1 min
Classifiers: When Labels Become DecisionsTen chapters on designing categories, choosing evidence, measuring errors, and deciding when a label deserves to influence what happens next.
3 min
How Intelligence Finds Its WayFive essays on the worlds intelligence can read, the questions it asks, the experience it carries, and the actions it can afford to try.
2 min
Checkpoint Replay for Long-Horizon Agent EvaluationEvaluate a 24-hour soak at recorded checkpoints. Restore the evidence and agent state available at each moment, then test the decisions.
6 min
Local Context for Autonomous AgentsPut telemetry, logs, and topology beside the agent. Use PromQL and files to keep retrieval reliable and model context focused.
6 min
03 / Connecting the work
Make evidence queryable, execution reliable, and decisions reproducible.Explore the focus areas
04
Open notebook
Currently thinking about
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Which decisions should a classifier's labels be allowed to influence?
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