# Louis-François Bouchard, aka What's AI

> Making AI accessible through practical AI engineering writing, videos, courses, and consulting.

Louis-François Bouchard writes and teaches practical AI engineering, machine learning, LLMs, AI agents, computer vision, and AI education. This file is a curated entry point for assistants and agents. Canonical HTML URLs remain the source of truth.

## Primary Links
- [Home](https://www.louisbouchard.ai/): Making AI Accessible. Co-founder at Towards AI. Ex-PhD at Mila.
- [Blog](https://www.louisbouchard.ai/blog/): All articles and essays.
- [RSS](https://www.louisbouchard.ai/rss.xml): Fresh posts feed.
- [JSON Feed](https://www.louisbouchard.ai/feed.json): Machine-readable feed.
- [Complete AI index](https://www.louisbouchard.ai/ai-index.json): Structured list of pages, posts, tags, and canonical URLs.
- [Full LLM index](https://www.louisbouchard.ai/llms-full.txt): Complete Markdown URL index for all public content.
- [Image sitemap](https://www.louisbouchard.ai/image-sitemap.xml): Discoverable local images used by public pages and articles.
- [Video sitemap](https://www.louisbouchard.ai/video-sitemap.xml): 557 YouTube embeds mapped to their canonical article pages.

## Discovery Notes
- Use canonical article URLs for attribution and citations.
- The AI index includes topics, tags, takeaways, FAQs, key questions, source links, media, and last-reviewed dates when available.
- The HTML pages remain the source of truth. The machine-readable files are navigation aids.

## Learning Paths
- [Learn AI Engineering](https://www.louisbouchard.ai/learn-ai-engineering/): A practical free guide to building real AI systems in 2026.
- [Build a Career in AI Engineering](https://academy.towardsai.net/?ref=1f9b29): A structured course path for people who want AI engineering to become their job, not just a side curiosity.
- [Start AI From Zero](https://www.louisbouchard.ai/learnai/): A beginner-friendly roadmap from no background to serious AI fluency.
- [From Zero to Hero With LLMs](https://www.louisbouchard.ai/from-zero-to-hero-with-llms/): A focused path for understanding and building with language models.

## Topic Hubs
- [AI Agents](https://www.louisbouchard.ai/topics/ai-agents/): Practical writing on AI agents, workflows, memory, tool use, reliability, and what actually ships.
- [Large Language Models](https://www.louisbouchard.ai/topics/llms/): Clear explanations of LLMs, reasoning models, prompting, context, distillation, fine-tuning, and model behavior.
- [RAG and Retrieval](https://www.louisbouchard.ai/topics/rag/): Guides and explainers on retrieval augmented generation, vector databases, embeddings, indexing, and evaluation.
- [AI Engineering](https://www.louisbouchard.ai/topics/ai-engineering/): Roadmaps, architecture decisions, evals, deployment lessons, and practical AI engineering advice.
- [Computer Vision](https://www.louisbouchard.ai/topics/computer-vision/): Computer vision explainers on image generation, segmentation, 3D reconstruction, video, and visual AI research.
- [Generative AI](https://www.louisbouchard.ai/topics/generative-ai/): How generative AI models create images, video, audio, code, and text, without the hype fog.
- [Learning AI](https://www.louisbouchard.ai/topics/learning-ai/): Free guides, beginner roadmaps, course recommendations, and practical paths into AI engineering.
- [AI News and Analysis](https://www.louisbouchard.ai/topics/ai-news-analysis/): Opinionated but fair analysis of AI releases, model news, research updates, and industry shifts.

## Key Pages
- [About me](https://www.louisbouchard.ai/about/): Learn who Louis-François Bouchard is, how What's AI started, and how his work connects AI engineering, education, videos, and Towards AI.
- [We Can Help your Team Adopt AI: Corporate Training, Consulting, and Talent Solutions](https://www.louisbouchard.ai/b2b/): AI training, consulting, and talent support for teams that want to adopt AI with practical systems, not vague demos or hype.
- [Contact](https://www.louisbouchard.ai/contact/): Contact Louis-François Bouchard for AI training, consulting, sponsorships, podcast requests, collaborations, or practical AI engineering questions.
- [From zero to hero with LLMs](https://www.louisbouchard.ai/from-zero-to-hero-with-llms/): A focused path for learning LLMs from the basics to practical building, with resources for developers who want real AI engineering skills.
- [Learn AI Engineering](https://www.louisbouchard.ai/learn-ai-engineering/): A practical roadmap for learning AI engineering in 2026, from fundamentals to RAG, agents, evals, deployment, and real projects.
- [Start AI in 2026 — Become an expert from nothing, for free!](https://www.louisbouchard.ai/learnai/): A beginner-friendly path to learn AI from scratch in 2026, with free resources, projects, and a practical order to avoid getting lost.

## Featured Writing
- [How to Build a Memory Your AI Agents Can Actually Reuse](https://www.louisbouchard.ai/memory-for-ai-agents/) (Jun 26, 2026): Reusable memory for AI agents means keeping notes, sources, and references outside the model so future sessions can use them.
- [What Did Microsoft's MAI Model Actually Train On?](https://www.louisbouchard.ai/mai-thinking/) (Jun 23, 2026): Microsoft's MAI-Thinking-1 report matters because it refuses synthetic data and asks what behavior a model really inherited.
- [90% Cheaper GPT APIs](https://www.louisbouchard.ai/api-proxy/) (Jun 15, 2026): Cheap GPT API proxies can hide model swaps, key logging, and code risks. The small token discount may cost more than it saves.
- [Loop Engineering Explained](https://www.louisbouchard.ai/loop-engineering/) (Jun 10, 2026): Loop engineering turns repeated agent babysitting into a controlled workflow with goals, checks, tools, and stop conditions.
- [How Image Generation Actually Works](https://www.louisbouchard.ai/image-generation/) (Jun 07, 2026): A plain-English explanation of image generation, how text steers visual models, and why prompts do not directly draw pixels.
- [Coding Changed Forever](https://www.louisbouchard.ai/vibe-coding/) (May 25, 2026): AI coding agents changed how software gets built, but vibe coding breaks quickly without reviews, tests, context, and taste.
- [How Google Went From AI Joke to OpenAI’s Biggest Problem](https://www.louisbouchard.ai/googleai/) (May 01, 2026): A look at how Google moved from being dismissed in AI to becoming one of OpenAI's strongest competitors again.
- [Your AI Can Improve Itself — Or Fool You](https://www.louisbouchard.ai/self-improvement/) (Apr 24, 2026): Self-improving AI is becoming practical in small loops, but the same loop can also optimize the wrong thing and fool you.
- [AI Distillation Explained: The Truth Behind the Biggest AI Controversy Right Now](https://www.louisbouchard.ai/ai-distillation/) (Apr 17, 2026): A practical explanation of AI distillation, the controversy around model outputs, and why ownership is harder than the technique.
- [How to Control Bias in AI Agents](https://www.louisbouchard.ai/control-bias-in-ai-agents/) (Apr 01, 2026): A practical look at bias in AI agents, from audits and guardrails to the human review loops that still matter.
- [Harness Engineering: The Missing Layer Behind AI Agents](https://www.louisbouchard.ai/harness-engineering/) (Mar 25, 2026): Harness engineering is the missing layer around agents: tools, evals, traces, guardrails, and controls that make them usable.
- [Why RAG Is Not Training Your AI](https://www.louisbouchard.ai/why-rag-is-not-training-your-ai/) (Mar 16, 2026): RAG does not train your model. It gives the model temporary context, which changes the answer without changing the weights.

## Recent Writing
- [How to Build a Memory Your AI Agents Can Actually Reuse](https://www.louisbouchard.ai/memory-for-ai-agents/) (Jun 26, 2026): Reusable memory for AI agents means keeping notes, sources, and references outside the model so future sessions can use them.
- [What Did Microsoft's MAI Model Actually Train On?](https://www.louisbouchard.ai/mai-thinking/) (Jun 23, 2026): Microsoft's MAI-Thinking-1 report matters because it refuses synthetic data and asks what behavior a model really inherited.
- [90% Cheaper GPT APIs](https://www.louisbouchard.ai/api-proxy/) (Jun 15, 2026): Cheap GPT API proxies can hide model swaps, key logging, and code risks. The small token discount may cost more than it saves.
- [Loop Engineering Explained](https://www.louisbouchard.ai/loop-engineering/) (Jun 10, 2026): Loop engineering turns repeated agent babysitting into a controlled workflow with goals, checks, tools, and stop conditions.
- [How Image Generation Actually Works](https://www.louisbouchard.ai/image-generation/) (Jun 07, 2026): A plain-English explanation of image generation, how text steers visual models, and why prompts do not directly draw pixels.
- [Coding Changed Forever](https://www.louisbouchard.ai/vibe-coding/) (May 25, 2026): AI coding agents changed how software gets built, but vibe coding breaks quickly without reviews, tests, context, and taste.
- [How Google Went From AI Joke to OpenAI’s Biggest Problem](https://www.louisbouchard.ai/googleai/) (May 01, 2026): A look at how Google moved from being dismissed in AI to becoming one of OpenAI's strongest competitors again.
- [Your AI Can Improve Itself — Or Fool You](https://www.louisbouchard.ai/self-improvement/) (Apr 24, 2026): Self-improving AI is becoming practical in small loops, but the same loop can also optimize the wrong thing and fool you.
- [AI Distillation Explained: The Truth Behind the Biggest AI Controversy Right Now](https://www.louisbouchard.ai/ai-distillation/) (Apr 17, 2026): A practical explanation of AI distillation, the controversy around model outputs, and why ownership is harder than the technique.
- [How to Control Bias in AI Agents](https://www.louisbouchard.ai/control-bias-in-ai-agents/) (Apr 01, 2026): A practical look at bias in AI agents, from audits and guardrails to the human review loops that still matter.
- [Harness Engineering: The Missing Layer Behind AI Agents](https://www.louisbouchard.ai/harness-engineering/) (Mar 25, 2026): Harness engineering is the missing layer around agents: tools, evals, traces, guardrails, and controls that make them usable.
- [Why RAG Is Not Training Your AI](https://www.louisbouchard.ai/why-rag-is-not-training-your-ai/) (Mar 16, 2026): RAG does not train your model. It gives the model temporary context, which changes the answer without changing the weights.
- [What I Look For When Hiring AI Engineers](https://www.louisbouchard.ai/what-i-look-for-when-hiring-ai-engineers/) (Mar 09, 2026): What stands out in AI engineering interviews and take-homes: judgment, clear thinking, debugging, and shipping useful systems.
- [Stop Building Agent Demos](https://www.louisbouchard.ai/stop-building-agent-demos/) (Feb 26, 2026): A push to move past agent demos and build systems that can be evaluated, debugged, deployed, and trusted under constraints.
- [I Published 42 Shorts on AI Terms in 42 days](https://www.louisbouchard.ai/ai-in-42-terms/) (Feb 05, 2026): A 42-day AI terms project that explains why understanding model behavior matters more than collecting prompting tricks.
- [The 12 Questions That Decide Your AI Architecture](https://www.louisbouchard.ai/12-questions-ai-architecture/) (Jan 29, 2026): A practical checklist for choosing AI architecture before implementation, so teams avoid agent rewrites caused by bad scoping.
- [Multi-agent is becoming the new overengineering](https://www.louisbouchard.ai/agents-and-workflows/) (Jan 28, 2026): A clear distinction between workflows, agents, and multi-agent systems, with the main rule: stay as simple as the problem allows.
- [How to Clean Up AI-Generated Drafts Without Sounding Like ChatGPT](https://www.louisbouchard.ai/ai-editing/) (Jan 15, 2026): A practical editing workflow for using LLMs without losing your voice, with checks for slop, repetition, and fake polish.
- [Why AI Feels Intelligent (and Why That’s Misleading)](https://www.louisbouchard.ai/why-ai-feels-intelligent/) (Dec 23, 2025): Why LLMs feel intelligent, why the comparison to human learning gets messy, and what builders should remember about fluency.
- [Earn While Helping Others Learn AI](https://www.louisbouchard.ai/affiliate/) (Sep 02, 2025): An explanation of the Towards AI Partner Program, where referrals can earn books, courses, full access, or an affiliate tier.

## External Profiles
- [YouTube](https://m.youtube.com/c/WhatsAI?sub_confirmation=1)
- [Substack](https://louisbouchard.substack.com/subscribe)
- [LinkedIn](https://www.linkedin.com/in/whats-ai/)
- [GitHub](https://github.com/louisfb01)
- [Towards AI](https://towardsai.net/)