Building an Observability-Driven Optimization Loop for Coding Agents
From distributed traces to verified performance improvements: an evidence interface, isolated runtime, independent verifier, and three-way experimental protocol.
Writing topic
Agent Reliability
Keeping execution authority outside the model: typed proposals, deterministic policy, durable confirmation, revalidation, idempotency and audit.
Agent Reliability writing
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Stop Asking Coding Agents to Guess What's Wrong
Why Agent-Friendly Codebases need runtime evidence, not just better documentation: traces, profiles, reproducible workloads, and independent verification.
Agentic Without the LLM: Building Deterministic Kubernetes RCA
How I built a bounded autonomous Kubernetes incident investigator where evidence selection and root-cause diagnosis run deterministically — 21/25 exact-root agreement on a frozen blind holdout with zero model calls.
Hard Gates + Frozen Hashes for AI Coding Agents
Making agentic development verifiable rather than merely autonomous: external gates decide whether work is acceptable, and hashed baselines stop the agent from redefining what acceptable means.
A Confirmation Is Not a Boolean: Designing Stateful Agent Workflows
Why "yes" is not always approval, and how interruption, suspension, resume, revalidation, and durable state make consequential agent workflows safe.
The Write May Have Succeeded: Handling Unknown Outcomes in AI Agents
A timeout after a customer-impacting action does not mean the action failed. How action identity, idempotency, database constraints, and reconciliation reduce duplicate writes, and where local guarantees stop.
Memory Is Context, Not Authority
Persistent agent memory is useful only if remembered text cannot become permission. A practical boundary for scoped memory, consent, DLP, TTL, and authority isolation.
Testing AI Agents Without Pretending They Are Deterministic
Deterministic integration tests and real-LLM tests answer different questions. How to use both to verify control-plane invariants and probe semantic quality.
Decision, Authority, Execution: Observability for AI Agents
For consequential agents, intent, authority, and execution must be observable separately. A practical operator view for workflow state, policy, evidence, replay, and traces.
How I Keep Prompt Injection Away from Agent Tools
A defense-in-depth boundary that treats model output, retrieved text, and remembered context as evidence while deterministic software keeps execution authority.
Designing Guardrails for Production AI Agents
A practical execution model for tool-using agents built from typed proposals, deterministic policy, durable confirmation, revalidation, idempotency, and audit.