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Updated monthly (last updated in January 2026)
Trusted by 100K+ learners building production-grade systems
Are You Making These Costly AI Architecture Mistakes?
This cheat sheet helps you stay as simple as possible, because each step toward multi-agent can multiply tokens, latency, and debugging overhead!
Inside This Cheatsheet & Webinar
📊 You’ll stop guessing the architecture.
Instead of defaulting to “agent + tools,” you’ll make a clean decision using constraints: when a workflow is enough, when a single agent is justified, and when multi-agent is truly worth the complexity.
🔧 You’ll stop discovering requirements late.
You’ll learn the kickoff questions that force clarity upfront, so cost blowups, tool sprawl, and untestable autonomy don’t show up after you’ve already built half the system.
✅ You’ll build in reliability from day one.
You’ll leave with practical rules for making agents production-safe: validate outputs, instrument runs, route edge cases to humans, and keep the agent thin so the system is debuggable.
Trusted by Industry Leaders
& 100,000+ Learners
Contains thorough explanations for you to start using and deploying LLMs. Very highly recommended!
PhD, Founder of Serrano Academy
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Helps learners understand everything from fundamentals to the simple-to-advanced building blocks of constructing LLM applications.
CEO of LlamaIndex
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A truly wonderful resource that develops understanding of LLMs from the ground up, from theory to code.
Co-founder of The Neuron
This will be valuable to anyone looking to dive into the field quickly and efficiently.
Senior Applied Research Scientist at Mila
Contains thorough explanations for you to start using and deploying LLMs. Very highly recommended!
PhD, Founder of Serrano Academy
A truly wonderful resource that develops understanding of LLMs from the ground up, from theory to code.
Co-founder of The Neuron
Helps learners understand everything from fundamentals to the simple-to-advanced building blocks of constructing LLM applications.
CEO of LlamaIndex
This will be valuable to anyone looking to dive into the field quickly and efficiently.
Senior Applied Research Scientist at Mila
About the Agents Cheatsheet and webinar
1-hour Webinar: Global context behind workflows and agents + how we view them and implement them with clients at Towards AI. Cheatsheet: Page 1: Make the architecture call quickly using the spectrum + autonomy test, so you don’t pay multi-agent costs for workflow problems. Page 2: Know when multi-agent works, when it fails, and what reliable systems always include. Page 3: Run a better kickoff with a repeatable 7-step sequence that prevents rework. Pages 4-5: Use the 12 questions to translate “requirements” into an architecture + system design plan with concrete build outputs. Page 6: Turn the framework into next steps (what to learn next / where to go deeper).
FAQ
✓ Completely free: no credit card, no hidden costs, no upsell required ✓ Webinar you can watch at anytime ✓ Instant PDF delivery: download immediately, read offline, print for your team ✓ Created by Towards AI: 100K+ students, real production experience ✓ Decision-ready format: use it in your next project kickoff this week ✓ Updated January 2026: reflects current best practices and latest thinking ✓ Want to go deeper? Explore our in-depth AI engineering courses: https://academy.towardsai.net/
Get the Framework Top AI Teams Use Daily
Stop building impressive demos that collapse under real users. Use a repeatable framework to choose the right architecture and the reliability patterns that keep it stable.
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Meet the Experts
Hi there! I'm Louis-François! My AI journey began in 2019 during my systems engineering degree. In 2020, I pursued a Master’s in AI, became Head of AI at a startup, and launched a YouTube channel to teach AI concepts. These experiences revealed a gap between academia and industry, inspiring me to co-found Towards AI in 2022 to bridge that divide. In 2024, I left my PhD in medical AI to focus on building real-world AI solutions. This is why the TAI team of experts and I have identified the essential tech stack for adapting LLMs to a specific use case and achieving a sufficient threshold of accuracy and reliability for scalable use by paying customers. With Towards AI Academy and some key projects in our pipeline, like our full-stack AI engineering course and our book, we aim to help you develop this toolkit.
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