The presenter describes a collection of reusable instructionsAn AI agent skill is a reusable package of instructions, resources, and tool guidance for performing a bounded kind of work. intended to help coding agents plan, check changes and stop when a fix repeatedly fails. The walkthrough groups the skills into planning and verification loops, design tasks, reviews and pull request workflows.
Examples include testing a real changeAgent completion verification checks evidence that an agent achieved the requested outcome rather than merely producing intermediate work., reviewing a plan in fresh contextContext engineering designs how relevant instructions, evidence, state and tool information are assembled for a model's task. and comparing independent attempts. The presenter discusses using a cheaper model for additional checksModel selection chooses the AI model whose capability, quality, cost, speed, safety, and operating constraints best fit a task. while noting that hard debugging and creative problems can still favor stronger models.
The claimed performance comparison is a personal impression rather than a benchmark. The presenter also notes token use and that prompts sent to a hosted model leave the local machine.
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