Noah Labhart

It writes clear specification, maps UX flows, asks the clarifying questions you forgot to ask, and breaks big ideas into engineering-grade tasks that AI coding tools can build reliably.

It guides Cursor, Clog Code, Replit, WinSurf, and others so they deliver features that work and keep working.

Founders use BrainGrid to build real AI-native SaaS products without a technical background.

If you want reliable features instead of fragile prototypes, try BrainGrid for free at braingrid.ai.

That's braingrid.ai.

So then you've got the MVP, it's working, you've made the trade-offs, and you're moving forward, getting some traction that you want.

How did you progress and mature the product from that point?

I think to wrap in a box a little bit, what I'm looking for is how you built your roadmap, how you went about deciding that, okay, this is the next most important thing to build or to address with Docey.

How did you build your team?

What did you look for in those people to indicate that they were the winning horses to join you?

This episode is sponsored by Mesmo.

If you're responsible for reliability, performance, or platform architecture, you already know the problem.

Telemetry volume is growing faster than teams can manage it.

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The result is cleaner data, reduced ingestion costs, and faster root cause analysis using the tools you already rely on.

Mesmo integrates with platforms like Datadog, Dynatrace, and Open Source Stacks, giving teams more control without adding operational overhead.

This is especially useful for platform engineers and SREs supporting complex, distributed systems where context and speed matter.

To see how active telemetry works in practice, get a demo at mezmo.com slash codestory.

That's M-E-Z-M-O dot com slash codestory.