Promtable guides

Long-form, authoritative guides to prompt engineering, AI image generation, AI video, AI agents, and RAG — written for engineers and product teams shipping with AI.

• Prompt engineering in 2026: the complete working reference

  What prompt engineering actually is in 2026, the patterns that ship, the techniques to skip, model-by-model tactics, and the eval discipline that separates good prompts from production prompts.

• AI image generation in 2026: the working reference

  The complete production reference for AI image generation in 2026: the model landscape, prompt anatomy, tool selection by use case, cost reality, failure modes, and the workflows that actually ship.

• AI agents in 2026: the working reference

  How to actually build, evaluate, and ship LLM agents in 2026 — planner-executor patterns, tool design, context engineering, budget caps, evals, and the failure modes that bite in production.

• AI video generation in 2026: the working reference

  Production reference for AI video generation in 2026: the model landscape (Sora 2, Veo 3, Runway Gen-4, Kling 2, Luma 1.6), prompt anatomy for motion, audio strategy, cost reality, and the workflows that ship.

• RAG in production 2026: the working reference

  Production RAG in 2026 — chunking strategy, embedding model selection, hybrid + re-rank retrieval, evaluation, observability, and the architectures that survive 1M+ documents at scale.

• AI voice production in 2026: the working reference

  Production reference for AI voice in 2026 — model landscape (ElevenLabs, Cartesia, Play.ht, OpenAI TTS, Hume), voice cloning ethics, latency targets for realtime agents, audiobook workflow, and the failure modes that bite.

• AI app building in 2026: the working reference

  Production reference for AI app builders in 2026 — Lovable, v0, Bolt, Replit Agents, Cursor, Claude Code. Which one to use for what, prompt patterns that ship, deployment, and where the abstractions still break.

• AI evals and observability in 2026: the working reference

  How to actually evaluate and observe LLM systems in 2026 — golden sets, rubrics, LLM-as-judge, A/B testing in production, regression catching, the tracing stack, and the antipatterns that quietly ship broken AI.

• AI search & SEO in 2026: the working reference

  How to actually rank in AI search engines in 2026 — Perplexity, ChatGPT Search, Claude with web, Gemini AI Overviews — and how traditional SEO has changed. Crawler policy, schema, citation patterns, llms.txt, and what to skip.