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Building Great Agent Skills: The Missing Manual
Jun 29, 2026 · 20:43
Matt Pocock presents a 'skill checklist' framework to help developers escape 'skill hell' by systematically evaluating and improving agent skills, covering trigger, structure, steering, and pruning. He explains the trade-offs between user-invoked and model-invoked skills: model-invoked increase context load and unpredictability, user-invoked increase pilot cognitive load. Structure divides skills into steps and reference, with branching material hidden behind context pointers to minimize skill.md. Steering uses 'leading words' like 'vertical slice' that appear in reasoning traces; to boost leg work, he splits skills so agents only see one step at a time. Pruning removes duplication, sediment, and no-ops that don't affect behavior. The framework is in the 'writing-great-skills' skill in his repository.

Full Walkthrough: Writing & Using Skills — Nick Nisi and Zack Proser
May 6, 2026 · 1:21:03
Zack Proser and Nick Nisi, Developer Experience Engineers at WorkOS, teach how to write portable, composable skills — single markdown files with optional scripts — that train AI tools like Claude, Codex, and Cursor to perform specific tasks consistently. They demonstrate building a repo roast skill that uses deterministic Git commands via script interpolation and progressive disclosure to load targeted references only when needed. The workshop covers structuring skills with front matter (name, description for LLM routing), adding confidence scoring and constraints to improve output, and sharing skills as .skill files or through marketplaces. Advanced topics include using skills in non-coding workflows (e.g., Slack–Linear automation) and composing skills in the WorkOS CLI, which uses the Claude Agent SDK to install auth. Attendees learn to iterate skills by reflecting on past conversations and leveraging Claude's built-in skill builder for evaluation.

Ralph Loops: Build Dumb AI Loops That Ship — Chris Parsons, Cherrypick
May 4, 2026 · 1:48:26
Chris Parsons argues that dumb loops—simple while loops where an AI agent repeatedly executes the same task, evaluates its output, and iterates—outperform complex multi-agent orchestration and planning graphs. In this hands-on workshop, he builds a Pomodoro timer using Claude Code, implementing tickets one by one in a loop that self-corrects with each pass. He demonstrates the 'loop' command in Claude Code for scheduled, continuous execution and shows how to use sub-agents for adversarial validation to avoid self-confirmation bias. The talk covers real-world applications such as a worker loop that processes project steps overnight and a morning loop that generates daily briefings, all designed to offload routine work while keeping human oversight for irreversible decisions. Parsons emphasizes that the bottleneck in AI-augmented teams is often the review process, not coding speed, urging teams to identify and fix their biggest constraint first.
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