The $0 download that saves a $5k pivot.
Our free Agent Architecture Cheatsheet and Webinar is now live!
We just released something that will save you a painful amount of time, tokens, and “why is this system doing that?” debugging.
It’s a free Agent Architecture Cheatsheet + a 1-hour webinar that tells you whether you need a workflow, a single agent, or a multi-agent before you commit to the wrong build. The cheatsheet contains all the information you need to make architectural decisions in AI projects in the most condensed format. The webinar adds context and examples.
It is built from months of production trial-and-error (plus a few expensive “well… that was a pivot” moments). It turns everything we learned deploying real systems into a decision framework you can use to design agents in any niche, any industry, at any level of complexity.
If you’ve built even one “agent” recently, you’ve seen the plot twists:
Day 1: “It works!”
Day 7: “Why is it calling seven tools?”
Day 14: “Why did costs triple?”
Day 21: “We’ll add evals and monitoring after launch.”
(We love your optimism. We really do.)
And here’s the part nobody warns you about: once you pick the wrong architecture, it’s not a quick refactor. It becomes a slow-motion rewrite: tool chaos, state bugs, brittle loops, unpredictable latency, until you’re stuck answering the hardest question in the whole project way too late: should this have been a workflow, a single agent, or multi-agent in the first place?
That’s what this cheatsheet and webinar make easy.
You get a fast, practical method to make the call: Workflow vs. Single Agent + Tools vs. Multi-Agent with enough structure that you can defend it in a design review, not just “it felt right.” You run a quick autonomy test, answer 12 high-signal questions, and suddenly you’re not guessing anymore. Decisions that used to take a week of Slack debate become boringly clear. You’ll know when to keep things deterministic, when to allow autonomy, when multi-agent is actually justified, and when it’s just adding cost and failure modes without adding capability. The result is simple: fewer pivots, fewer surprises, tighter latency, cleaner debugging, and systems that behave on purpose.
And the questions inside are the ones that actually decide whether your build ships. You’ll pressure-test tool complexity (including the point where tool selection quality starts collapsing), define where validation must be hard checks vs judge-based, decide what state needs to persist (and where it lives), place human-in-the-loop gates when failure is expensive, lock in your latency budget before your agent blows it up, and set up the minimum eval + tracing instrumentation so you can iterate with signal instead of vibes.
It’s the same framework style we use to design and deploy systems under real constraints, work associated with teams at Thinkific and Europol, because in production, architecture decisions are cost decisions. And it’s been used in architecture reviews for one reason: it’s faster to run this framework than to argue yourself into an overbuilt system.
Run it once with your current agent idea, and you’ll know exactly what to build next, without the expensive detour.
PS: My favorite debate-killer from the cheatsheet: one model calling 10 APIs is still one agent with tools, not “multi-agent.” If you’ve ever lost 45 minutes to that argument, you’ve already earned this download.
What a fantastic read! I love how you highlighted the cost-saving potential of https://dashmetry.com
I’m curious if you think smaller businesses could benefit even more from this tool?
Excellent framework on the architecture decision process! The PS about one model calling 10 APIs still being a single agent really clarifies the semantic confusion—I've seen teams debate this for way too long when it dosnt matter for the build. The point about tool selection quality collapsing is critical; we hit exactly that around 70 tools and had to restructure into categories to maintian reliability. This kind of upfront thinking saves months of rewrites.