#agentic-ai
Every post tagged "agentic-ai".
27 posts · showing 11–20
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One 300-Second Timeout Tells You Nothing. Agents Need a Deadline Budget.
A run that dies at its ceiling with no attribution tells you nothing about which part was slow — and pushes you toward the laziest fix, raising the ceiling. Three nested clocks, an inherited remainder, and a reserved tail slice turn timeouts into a signal you can actually read.
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Untrusted Text Doesn't Stay Untrusted: Where Provenance Gets Lost in an Agent Pipeline
An injection scanner that fires on the raw email won't fire on the tidy summary of it. Untrusted content gets laundered clean every time an agent rewrites it — here's where the taint disappears, and how to make it survive.
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Append or Supersede? What to Do When New Information Contradicts Agent Memory
Most agent memory systems only know how to add. The moment a fact changes, the store holds both versions and the retriever picks whichever one scores higher — which is why a scheduling agent keeps booking a room that was decommissioned last month.
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Retry, Repair, or Replan? A Recovery Ladder for When an Agent's Step Fails
Blind retry burns money on a call that will never succeed; premature replanning throws away correct work and produces a worse plan. The deciding signal isn't how bad the error looks — it's what the error proves false.
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Your First Production Agent Should Be Invoice Reconciliation — Because the Ledger Grades It for You
The best first agent isn't the most impressive one — it's the one whose environment tells you when it's wrong. Here's how to score candidate tasks for a built-in oracle, and the two ways that oracle quietly lies to you.
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Framework or Raw SDK? The Test Is Whether You Can Print the Exact Prompt
The framework debate is usually argued on taste. There's a faster test: build a two-tool agent and try to dump the exact request it sends on turn four. How hard that is predicts your next six months of debugging.
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Agent or Just a Script? Count the Branches That Depend on Reading Something
There is a ten-minute test that settles whether your automation needs an agent loop or just a script with a couple of model calls in the middle — and the two ways of guessing wrong are not equally recoverable.
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Cached or Re-Called? Giving Every Agent Tool a Staleness Budget
An agent that reads a value once and acts on it four minutes later isn't reasoning badly — nobody told it how long that value stays true. Per-tool staleness budgets, and the one rule that matters most before a write.
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Your Retriever Returned 12 Chunks. The Agent Only Really Read 3 of Them.
The correct passage was in the prompt and the agent wrote around it anyway. That's not a retrieval bug — it's a placement bug, and there's a one-minute test that tells the two apart before you touch your embeddings.
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Draining a Data Backlog: Should the Agent Batch Rows or Take Them One at a Time?
The ratio of preamble tokens to row tokens decides whether chunking a backlog saves an order of magnitude or nothing at all — and it's the alignment, retry amplification and blast radius that decide whether you should anyway.