# Why the most reliable AI agents will be built by design-obsessed engineers

I just saw Zeno Rocha’s post about the Resend CLI launch (53 commands, fully open source, pristine DX). It’s a reminder that in 2026, **Developer Experience is the product.**

But here’s the thing: we’re currently in the "ugly phase" of AI infrastructure. 

Most agentic workflows are held together by messy Python scripts, unorganized vector stores, and "dumb" RAG that hallucinates at the first sign of complexity. It feels like 2005-era email—functional, but painful to scale and impossible to trust.

We’re trying to change that with the **ThumbGate.**

Inspired by the precision of tools like Resend and Vercel, we’ve built a Design-Driven Context Layer for AI agents. We realized that an agent's memory isn't just a database problem—it's a **Ranking and Reliability** problem.

### What "Design-Driven AI Memory" looks like:

*   **Pristine CLI First:** We just overhauled our CLI to be as dense and functional as a high-end DevOps tool. Because if you can't manage your agent's brain from the terminal, you can't automate it.
*   **Outcome-Based Ranking:** We moved beyond "similarity search." Using Thompson Sampling (the same logic used in world-class feed algorithms), our gateway ranks memories based on whether they actually *worked* in the past.
*   **Experience Packs:** We’re now packaging these "agent brains." Want a brand-manager agent that follows minimalist enterprise constraints? We created an Experience Pack for that (`TW-MINIMAL-01`).

The era of "hacky AI" is closing. The next wave belongs to engineers who realize that **Context is the new Code**, and it needs to be managed with the same level of design obsession we give to our frontend components.

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**Are your agents still using "dumb" search?** 
I’d love to hear how you’re handling reliability in your production loops.

Check out the new CLI update on [GitHub].
