AI Integration

LLMs are good at some things and bad at others. Getting more out of them comes down to matching the tool to the task and running the model in a setup that can actually do work, not just a chat window that talks.

Frontier models are the strongest tools available, and local inference gives you control over your data, your costs, and your jurisdiction. Here is what each one is, the trade-offs between them, and the benchmark numbers the labs themselves report.

A plain map of the AI ecosystem in 2026, from chat assistants to coding agents to work platforms, judged by the three capabilities that decide whether a tool actually helps: a real browser, script execution, and MCP extensibility.

LLMs don't remember you. Every response is a cold start. Understanding context windows, compaction, RAG, and platform memory systems will make you a dramatically better AI user.

A metaprompt is a structured prompt generated by one AI session for use in another. Learn how to bridge stateless LLM tools and eliminate the context ramp-up that wastes your first dozen messages.

A practical guide to integrating LLM APIs into JS apps: SSE streaming, architecture choices, LangChain vs. direct calls, and when you need Python.