Systems that use models to plan or execute multi-step tasks through tools, memory, or other agents, including their design, evaluation, and deployment.
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30 articles in this tag.
A protocol standardizes the shape of a call. It does not standardize what the call means, who is allowed to make it, or what happens when it fails.
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An agent with legitimate access to a folder can still write four thousand files somewhere it should not, and every access check will pass.
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That is the uncomfortable lesson from AutoJack, a chain Microsoft's security team disclosed in June 2026. The individual bugs were ordinary — the kind of…
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The agent that answered cleanly for ten minutes starts contradicting a decision it made at turn twelve. It asks again for a fact you supplied in the…
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A failed response is not a failed operation. A successful response is not a successful operation either. Everything hard about AI agent reliability lives…
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An audit trail is a reconstruction contract. If a reviewer cannot explain a consequential action from the record alone, you have activity logs, not…
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The attacker's cost curve is falling faster than the defender's learning curve. That single asymmetry explains most of what is actually changing.
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The demo passed. The patch was clean. Three weeks later, your team spends more time reviewing agent output than it would have spent writing the code by…
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The diff counter climbs every sprint. The release cadence does not move. That gap is not a tooling problem — it is a measurement problem, and most teams…
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The unit of work is shifting. Autocomplete suggested a line; a coding agent takes a goal, touches the file system, runs a command, reads the error, and…
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A deflected contact is a closed conversation. A resolved issue is a problem that stayed solved.
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Your pager fires at 2:14 a.m. A customer has posted a screenshot: your assistant told someone to adjust a medication dose. You open the trace, find the…
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The hard part was never the model call. It is everything you have to build around it.
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Your application code can be perfect and your AI system can still be compromised before it ever runs. The model weights, the fine-tuning dataset, the MCP…
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A five-step task at 85% per-step accuracy finishes correctly about 44% of the time. That arithmetic, not the model, is what decides whether your workflow…
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The cluster is provisioned, the dashboards are green, and the inference bill is still climbing while latency drifts. That combination — healthy…
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Writing code stopped being the bottleneck. Reviewing and integrating it became one.
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The prompt was precise. The model was capable. The change still came back wrong.
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A coding agent is not a smarter autocomplete. It is a shell with your credentials, your network, and your filesystem — and it runs all three before you…
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The agent returns a 900-line diff across eleven files. Tests pass locally. The reviewer opens the pull request, scrolls twice, and still cannot say whether…
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A computer-use agent is a model that reads a screen and drives a mouse and keyboard. The demo looks like magic. The second run looks like a different…
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The demo proves what a model can do. Deployment proves what a system will let it do. An autonomous agent can plan, call tools, and act toward a goal on its…
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Agentic AI systems—autonomous agents that plan, call tools, and adapt as they work—are moving out of research demos and into business-critical workflows.…
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A benchmark score is a result under agreed test conditions. Reliability is what remains when ordinary inputs, missing data, delays, and recoverable failure…
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You built an agent. It worked once. Then you changed the input slightly and it fell apart, and you could not tell which part of the system failed.
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The real question is not whether to use many agents. It is what workflow constraint justifies adding another agent, and what coordination contract makes…
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An AI agent is software that uses an AI model to choose actions, call tools, and work toward a goal. Agentic AI describes systems built from these agents,…
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The attacker never talks to your model. They leave a sentence in a document it will read later.
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A voice agent that transcribes every word correctly can still feel broken. The transcript is not the conversation.
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A working demo and a working workflow are different artifacts. One proves the model can do the task. The other proves the organization can repeat it.
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