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.
| Cheatsheet | What you get |
|---|---|
| AI Engineering Playbook | Pick the right AI technique, model, prompting strategy, RAG setup, memory pattern, eval method, and production config. Decision tables for each. |
| Agent Architecture Guide | Decide between workflow, single agent, and multi-agent. Includes the questions to ask, the signals to look for, and the engineering rules to follow. |
| Anti-Slop AI Writing Guide | Get human-sounding output from any LLM. A 7-section prompt template, a banned-word list, style rules, and a two-model write-then-review workflow. |
- Open the cheatsheet relevant to your problem.
- Find your situation in the decision tables.
- Follow the recommended approach.
For the Anti-Slop guide, copy the complete template directly into your LLM of choice, then fill in the variables and edit to best fit your needs.
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).
