AI Engineering Cheatsheets

By Louis-Francois Bouchard (X, YouTube, other AI resources)

Goal: give you decision-ready references for the most common AI engineering problems. Open a cheatsheet, find your situation in the table, and follow the recommendation.

Model and tool preferences are a snapshot from August 2026. Treat them as tested starting points, then validate them on your own workload.

Cheatsheets

Cheatsheet	What you get
AI Engineering Playbook	Pick the right AI technique, model, effort level, modality workflow, prompting strategy, RAG setup, memory pattern, eval method, and production config.
Agent Architecture and Operations Guide	Decide between workflow, single agent, and multi-agent, then operate it with curated context, evidence stores, phased review, portable skills, feedback loops, and safe scheduling.
Anti-Slop AI Writing Guide	Produce grounded, human-sounding writing with a 7-section prompt, checkable anti-slop rules, the current Towards AI long-form starting point, evidence-first review, one targeted rewrite, and platform checks.

How to use

1. Open the cheatsheet relevant to your problem.
2. Find your situation in the decision tables.
3. Follow the recommended approach.

For the Anti-Slop guide, assemble the sources first, fill in the complete template, finish the draft, and then run the separate evidence-first review before your human edit.

Learn more

These cheatsheets come from the Towards AI courses. They cover the same frameworks in more depth, with full lessons, code, and hands-on projects.

• Full Stack AI Engineering - Prompting to production-grade RAG system. Position yourself for the roles, projects, and opportunities that AI is creating right now.
• AI for Business Professionals - Learn to get real benefits from LLMs for valuable tasks from experts that build AI for a living.
• Agentic AI Engineering - Your Path to Agentic AI for Production.
• Free Agents Webinar - Workflows vs. agents deep-dive (YouTube).