AI & Tech Playbooks for Operators
The AI & Tech desk is for operators who use this stuff in production, not for people who post screenshots of ChatGPT. We cover LLM tooling (GPT-5, Gemini 3, Claude), agentic workflows that don't fall over, AI SEO and AI Overviews strategy, retrieval and embeddings done right, model selection trade-offs, evals, prompt engineering as a real engineering discipline, and the unglamorous infrastructure choices — auth, queues, edge runtimes, observability — that decide whether your AI feature survives contact with real users. If we publish a model recommendation here, it's because we're paying for it ourselves.
5 posts
Schrödinger’s cat was a warning, not a pet trick
Schrödinger’s cat was not a cute paradox about a half-dead pet. It was a complaint about quantum measurement, and that complaint still bites.
Dopamine explained simply: reward, prediction error, and apps
Dopamine is not just the pleasure chemical. Here’s the simple version: it helps your brain learn what to chase, repeat, and expect.
TypeScript and AI-assisted engineering in 2026
A practical TypeScript playbook for using AI coding agents without losing architecture, tests, security, or long-term maintainability.
Prompt engineering fundamentals for builders in 2026
A practical 2026 guide to context design, evals, structured outputs, prompt security, and real workflows for teams building with LLMs.
AI agents for business operations in 2026
AI agents can cut operational drag only when they own narrow workflows, tools, approvals, and KPIs. Use this 2026 playbook before you automate.