The agentic loop: how to judge AI development work
A practical development loop for AI coding agents: define acceptance criteria, make a bounded change, inspect evidence, and decide when to repair, stop, or ship.
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One page for practical AI learning: agent workflows, useful prompts, coding patterns, model news, and original sources.
How-to / AI lessons
A practical development loop for AI coding agents: define acceptance criteria, make a bounded change, inspect evidence, and decide when to repair, stop, or ship.
Zack turns AI dubbing into a creator workflow checklist: voice consent, translation review, usage scope, editability, and source links before release.
Cara gives AI buyers and reviewers a checklist for reading evaluation claims: disclose the harness, tools, budget, retries, validity checks, and failure rules.
A running log of the moments where Ahmed's hands-on BIM experience beat the model's confident generalizations, starting with Revit journal save history.
A field note on how to ask AI coding agents to copy useful tools between projects without crossing manifests, namespaces, IDs, deployment paths, or ownership boundaries.
A field note on what the C:\Autodesk\WI folder is, why Autodesk installer files can pile up, and what I checked before cleaning disk space.
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