Devs.somi

Smart contracts execute logic. But they don’t have access to external data or compute. No APIs. No internet. No AI. This is a real constraint for builders.

This is the gap the Agentic L1 closes. Build on Somnia ↓ somnia.network 6/6

If that changes, the design space changes: • contracts that respond to real-world events • onchain systems that make decisions • agents operating without middleware 5/6

Smart contracts execute logic. But they don’t have access to external data or compute. No APIs. No internet. No AI. This is a real constraint for builders.

Prompting gets your agent running. Evaluation is what gets it to production. Build on Somnia: docs.somnia.network. 6/6

Evaluation isn’t a one-time step — it’s a loop: Test set → metrics → iterate → regression test Run every new version against old data. If performance drops, don’t ship. 5/6

You shipped your agent. But how do you know it actually works? “It worked in the demo” ≠ safe in production. When an onchain agent fails, it usually means lost funds. Here’s how to evaluate it properly 👇

Build on {s}omnia

Somnia Reactivity Mini Hackathon - Winner Spotlight #3 Streamline - no-code automation for onchain workflows. Drag. Connect. Deploy. Powered by Somnia Reactivity for real-time, event-driven execution. Explore Streamline: dorahacks.io/buidl/41857

Prompting is useful. But if you’re building serious agent workflows, structure beats prompt length every time. Any questions? Drop them below. 5/5

Put together, these files create a much stronger decision layer. Instead of one messy prompt, you get structured, reusable, version-controlled context. That usually means better outputs, fewer mistakes, and agents that are actually usable. 4/5

Stop pasting massive prompts into your AI. The better approach is to build a behaviour layer using modular .md files. If you want your agent to stop hallucinating and start executing properly, this structure matters. Here’s the 3-file setup 👇