#observability
Every post tagged "observability".
40 posts · showing 31–40
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The On-Call Agent: What It Should and Shouldn't Touch During an Incident
An incident is when your system is least understood — a poor moment for an autonomous actor, an excellent one for an autonomous investigator. The line between them is read access and write access.
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Flaky Agents: Separating Model Nondeterminism From Your Bugs
A test passed on re-run. That's ambiguous for agents in a way it isn't for other software — and the fix is to stop reporting pass/fail and start reporting distributions.
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Reading Your First Agent Trace: Wrong Tool, Wrong Argument, or Wrong Plan?
Four buckets, checked in order, and most agent failures resolve before you get to the interesting one. The trick is finding the first wrong turn and reading the raw array — not the pretty rendering.
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Build or Buy the Eval Harness? What Each Choice Locks In
Teams buy an eval platform and keep their own scripts anyway. The reason is deterministic replay — it hooks into your dispatch layer, which is the one part no vendor can own.
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Streaming an Agent's Progress Without Lying About It
Token streaming goes quiet exactly when an agent gets slow — inside the tool call. The fix is an event stream from the loop, and the hard part is not inventing certainty the loop doesn't have.
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Chain, Blackboard, or Broadcast? Three Ways Agents Share State
Chains lose the evidence, blackboards fight over it, broadcasts drown in it. Pick by which failure your task can absorb — and log provenance from day one or debugging becomes guesswork.
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Agent Adoption Stalls at Trust, Not Capability
An agent whose errors cluster somewhere describable beats a more accurate one whose errors are scattered. Ask your users when they double-check its work — the answer is your real roadmap.
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Framework or Plain Loop? Four Questions That Actually Decide It
The core agent loop is under a hundred lines — that's never what a framework saves you. Four situational questions decide it, and the one about 3am debugging should carry the most weight.
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Assert on the Trajectory, Not the Answer
A final-answer check will happily pass a run that took nineteen turns and touched a tool it should never have called. Five lines of trajectory assertions catch what output tests structurally cannot.
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The Retry Storm Your Dashboard Can't See: When Agent Failures Multiply Instead of Add
Three retry layers, each sensible on its own, compose by multiplication — and a failure at step fourteen costs the whole context, not the failed call. Your per-call dashboard will stay green the entire time.