#intermediate
Every post tagged "intermediate".
222 posts · showing 161–170
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Retry Semantics: Which Tools Are Safe to Call Twice
Agents repeat tool calls for at least five ordinary reasons — none of them bugs. Whether that's harmless or a duplicate charge is a property of the tool, and usually one nobody wrote down.
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Progressive Disclosure: Give the Agent Tools As It Needs Them
The tool list is a per-call parameter, not a fixed property. Withhold the write tools until acting is authorized and a compromised context has nothing dangerous to reach for — enforcement, not instruction.
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Graceful Degradation When the Model Provider Is Down
A fallback exercised only during incidents is exercised for the first time during an incident. Six degradation rungs, and the three cheapest ones cover most of the value.
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The Sales-Research Agent and the Problem of Stale Facts
Every fact in the brief had been true. None was labelled with when — so someone opened a call congratulating a person on a role they'd left a year ago.
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Least Privilege for Agent Credentials
Since injection isn't fully preventable, the credential decides whether a compromise is an inconvenience or an incident. Four scoping dimensions — and the one nobody uses is usually the highest-value.
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When Memory Makes an Agent Worse
Every retrieved memory is content injected into the context, relevant or not. Three ways that degrades the agent — including the one where it argues with a user about their own stated preference.
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Designing Tools for Agents vs Designing APIs for Developers
One endpoint, one tool is the obvious mapping and the wrong one. APIs assume a consumer who reads docs once and writes a loop — an agent re-decides everything from a paragraph, every call.
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Getting an Agent to Say How Sure It Is
Ask a model how confident it is and you get a plausible number that doesn't move with difficulty. Five signals that actually correlate with being right — and the calibration check that tells you if yours is noise.
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Latency Budgets for Agents: Where the Seconds Actually Go
"Try a faster model" addresses maybe a third of the time in a typical run. Split the twelve seconds five ways and the real culprits — turn count and tool latency — are usually the ones nobody measured.
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Local Models for Agent Work: Where They Actually Fit
"Can a local model replace the frontier one?" is the wrong question. Which steps can move is the right one — and the comparison people skip is against a small hosted model, where most of the saving already lives.