Dig Better Things by Comparison

Build a 50-100 example eval set from your real worst-case inputs, score each model on it, and look at variance not just mean. Don't trust benchmarks — they're not your workload.

For 'where did we decide X' or 'what did the meeting about Y say', Notion AI Q&A is genuinely useful. For complex reasoning across many pages, it's hit-or-miss.

Linear is great for 5 people, but you can also use GitHub Projects at that size. The right time to pay for Linear is when the friction of GitHub Projects starts costing you real time.

Make the right thing the easy thing: link the Figma components to a code library (shadcn, Radix, etc.), document variants with code snippets, and add design tokens to the codebase.

Redis stores the working set in RAM. If your working set is bigger than your memory, you need either more memory or to evict old data with an LRU policy.

Yes, Neon is production-ready. The architecture (separated storage and compute, branching, serverless) is a real advantage for modern workloads, and their SLA is real.

For a simple RAG over one document type with one embedding model, raw API calls are simpler. Use LangChain when you have multiple data sources, models, or want a real agent.

GPT-4o is good enough for most production workloads today. Wait only if you have a specific capability the new model unlocks.

Raycast for the launcher layer, Things 3 for personal task management, Notion for team docs. They don't overlap.

Many serious teams run both and route by task. Pick the primary based on your top workload.

Use both. Figma for design, Linear for engineering. The integration between them is the real win.

Obsidian for local-first durability, Notion for team collaboration, Logseq for an outliner model.

Choose Next.js for ecosystem and team familiarity, SvelteKit for productivity and bundle size, Astro for content-heavy sites.

The utility-first CSS framework that changed how frontend developers write styles — fast to learn, fast to use, and now a major force in design systems.

The GitHub of machine learning — model hub, dataset hub, Spaces for demos, and a hosted inference API for production deployments.

The most beloved personal task manager for Apple platforms — calm, beautiful, and built around Getting Things Done without forcing it on you.

The launcher and productivity layer for Mac that replaced Spotlight for developers — extendable, scriptable, and genuinely fun to use.

The full-stack framework for Svelte — file-based routing, server functions, and form actions, with a build that ships zero runtime by default.

A low-overhead, schema-driven Node.js HTTP framework that's measurably faster than Express — built for serious production APIs.

The React framework for production — file-based routing, server components, image optimization, ISR, and zero-config deployment baked in.