Hamel Husain argues that ROUGE/BLEU string-similarity scores and 1-to-10 rating scales are holdovers from traditional NLP that make evals harder to act on — nobody knows what a 4.2 means, and binary pass/fail evals are what actually let you ship.
Hamel Husain explains why he converts every 1-to-5 rating scale eval into binary pass/fail checks, scoping each failure into a specific, actionable criterion instead of hiding noise behind middle values.
Sean Kochel demos five relatively new GitHub tools for AI-assisted coding: an architecture-diagramming draw.io skill, an anti-over-engineering auditor, a free speech-to-text dictation app, shadcn's codebase audit skill, and NVIDIA's skill security scanner.
Maddy Zhang demonstrates skills for interface design, requirements, test-first development, code review and turning repeated engineering work into reusable instructions.
Jane Street's Ron Minsky on strong types, readable tests, and code review that preserves human understanding as agents write more software.
Wolfe builds a linked Markdown wiki, then adds journal responses, contact records and scheduled ingestion while correcting the agent’s filing rules.
Hamel Husain on evals for non-experts: why generic metric dashboards actively hurt you, how error analysis beats top-down guesswork, what guardrails and MCPs actually are, and the argument that AI competency can never be outsourced.
Martin Keen weighs whole-document reasoning against retrieval costs, missed evidence, attention limits, and the scale of an enterprise knowledge base.
Wolfe tests Locally AI with Qwen 3.5 on an iPhone, showing an airplane-mode response alongside reasoning failures, heat and slower long chats.
Anna Gutowska and Martin Keen explain agent discovery, task updates, and tool interfaces, then combine A2A and MCP in a retail inventory example.
Martin Keen explains how prompt caching saves a model's computed input state, why stable prefixes matter, and where provider-specific rules limit reuse.
Paul Ford (former Harper's editor, co-founder of Abort) and Dan Shipper process the week Opus 4.5 landed in Claude Code — the step change, the grief, the discourse, and what actually matters.
Wolfe turns his own writing into a training set, tunes a model in Nebius, and shows how messy transcripts and reply-heavy data distort the results.
Claire Vo builds reusable Claude Skills in Cursor, validates their files, tests a changelog newsletter, and fixes a naming error during web upload.
Colin Matthews turns screenshots and browser elements into reusable components, preserves a baseline, and forks prototypes before exploring new ideas.
Ryan Carson uses a product brief, a task list, and approval checkpoints in Cursor, then adds database tools, browser control, and explicit context selection.