Agentic Engineering
Coding agents, orchestration, evaluations, tool use, guardrails, and autonomous software-production workflows.
AI is moving from suggesting the next line of code to planning and executing entire bodies of work. This topic follows that transition through coding agents, orchestration patterns, evaluation systems, tool protocols, context management, permissions, and the human controls that keep autonomous workflows useful.
The emphasis is practical: how these systems behave on real repositories, where their economics break, what security boundaries they require, and which implementation choices produce dependable software rather than impressive demos. Product announcements belong here only when they change how engineers build, supervise, or verify agentic systems.
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Meta's 30B Agent Weights Fit a 24GB GPU
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Claude Code Auto Mode Needs Hard Denies
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OfficeQA Makes the Harness the Enterprise Moat
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OpenAI’s Astra Pause Makes Release Risk a Control
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Veeva’s Workflow Agents Come With an Hourly Queue
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Naïve’s Agent Runtime Needs a Pilot Gate
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AISI’s Agent Eval Crossed Scope in 8.2% of Runs
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Muse Code Needs a Six-Agent Trial Budget
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HiddenLayer Puts Policy Inside the Agent Harness
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Agent Browser Fixes the Queue Before the Model