Deep dives into artificial intelligence tools, practical guides, and expert perspectives on the technologies shaping tomorrow.
86 articles found in Guides & Tutorials
Learn to run AI locally on your own PC or Mac. Compare LM Studio, Ollama, and llama.cpp, master GGUF quantization, and match local AI models to your RAM and VRAM for private, offline AI in about ten minutes.
Generic AI proposal prompts produce fluff. Use a six-section scope skeleton (outcome, exclusions, assumptions, revisions, timeline, payment) and let Claude or ChatGPT fill it from your call notes, with a prompt that forbids invention.
Which PDF chat tool to open, and which to skip, per job: one quick document, a research notebook, or a contract where the page citation is the deliverable. Tested framing with 2026 pricing and limits.
Stop regex-ing prose into data and retrying failed parses. Learn the full ladder of LLM structured output, from prompting and JSON mode to schema-enforced structured outputs and tool calling, with vendor-by-vendor limits, latency gotchas, and when not to force a schema.
Turn plain English into a working Excel or Google Sheets formula with Better Analyst, Copilot in Excel, ChatGPT, or Claude, then run the sixty-second three-row test (normal row, blank row, zero row) that catches the wrong ones before they touch your data.
Understand vector databases from the ground up: what embeddings are, how similarity metrics work, why HNSW makes search fast, and how to choose between Chroma, Pinecone, Qdrant, and pgvector - plus the honest cases where you do not need one at all.
Three free apps can run a real AI chatbot on your own laptop. This is the decision guide: which one fits the no-terminal person, the tinkerer, and the privacy maximalist, plus the one model to load first and what local still does worse than Claude.
A plain-English guide to what you should never paste into ChatGPT, Claude, or Gemini: the consumer vs business plan split, what opt-out really does, meeting-bot consent, and a rule of thumb for client work.
A hands-on guide to ChatGPT Projects: setting up instructions, files, and project memory, the sharing rules that surprise people, and the September 2026 limits by plan.
OpenAI is retiring custom GPTs, with December 11, 2026 scheduled as the day they stop running. Here is which dates are actually confirmed, what transfers, and how to rebuild a GPT as a ChatGPT Project step by step.
Function calling (tool use) is the loop where an LLM proposes a structured tool call, your app executes it, and the model answers with the result. Learn schemas, parallel calls, RAG vs agents, and safety defaults.
Learn how to evaluate AI agents the practical way: the four dimensions to measure, how to build an eval set from real traces, how LLM-as-a-judge scoring works, and a copy-paste harness with a no-regression loop to run before every change.
