If you’re building AI agents in 2026,
You need a faster way to make architecture decisions...
95% of agents never hit production.
And it's because teams pick the wrong architecture from day one.
They use workflows when they need an agent.
Multi-agent when a simple pipeline would have worked.
Autonomy where determinism was enough.
So we created something to help with that...
Introducing, Building AI Agents Architecture Cheat Sheet.
It was created by Louis-François Bouchard (@Whats_AI) from Towards AI, Inc. in collaboration with me for our Agentic AI Engineering course that's coming this month.
The idea was to help you make the best architecture decisions.
Specifically, here's what it helps you do:
• Decide Workflow vs Single Agent vs Multi-Agent based on real constraints
• Avoid unnecessary autonomy that explodes cost, latency, and debugging time
• Apply the Autonomy Test to know when you actually need an agent
• Design thin agents + heavy tools for reliability
• Add validation loops, observability, and human in the loop (HITL) by design
• Pick the minimum architecture that works before scaling complexity
It also includes:
• A practical kickoff decision process
• Architecture questions with concrete build outcomes
• Clear signals for when multi-agent systems actually make sense
• Production rules we use when shipping real agentic systems
This is exactly the kind of reference you want before you write any code.
If you want it, here's how to get it:
1. Like this post
2. Comment “CHEATSHEET”
3. Repost so more builders can benefit
And I'll send you a DM.
P.S. Huge credit to Louis-François Bouchard (@Whats_AI) and the Towards AI, Inc. team for putting this cheatsheet together.
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