🚀 The new Edge Hound website is live. Not Framer this time, but the dev team did a stellar job with the implementation. Most AI fintech sites explain the tech. This one had to explain the category. Decision intelligence for capital markets - agentic AI that replaces the analyst function for brokers, neo banks, and investing platforms.

I think you did the right call by explaining the category here. This whole space is so new and different, and taking advantage of it is definitely the right call from your end.

Mimir — the AI execution layer for software

Build story

I kept hitting the same wall with AI agents: they can tell you what to do, but the moment you let one actually touch a real system — payments, orders, refunds — you're one hallucinated call away from a disaster. The demo is easy. The safety is the whole product. So I built Mimir around that problem instead of around the demo.

The core move is a single conversion: every API endpoint becomes one safe, callable operator. GET /orders becomes get_orders(). You point Mimir at an OpenAPI spec — or just paste the docs — and the model reads it, normalizes it, and commits it as a set of typed, validated tools an agent can run.

Three decisions shaped the build:

Boundaries live in the runtime, not the prompt. Permissions, approval gates, and destructive-write flags are enforced in code. You can't jailbreak a policy that was never a sentence. The agent is able to act, unable to overreach.

The model never sees the key. Credentials are vaulted and injected at execution time. The LLM operates the system without ever holding the secret to it.

Every action is signed and logged. Runs are stamped to an operator and written to an audit trail — so "the AI did it" is always answerable with who, what, and when.

The part I'm most proud of: I engineered it to run on a local 7B model, not a frontier API. That forced real discipline — small-model-first, code-enforces-not-prompts, eval-driven, structured output over brittle parsing, and a rule I made non-negotiable: the AI understands the docs and normalizes them; code only validates against known types. No hard-coding one company's naming conventions, because the next API won't share them. It's a deliberately-engineered system, not a wrapper around a chat box — and it's executed real refunds end-to-end.

Stack: Next.js 16 · React 19 · Tailwind v4 · TypeScript on the front; FastAPI · Postgres · LiteLLM → Ollama on the back. The interface is a custom design system I call "Operations Ledger" — carbon, bone, and one acid accent; Archivo Black; flat brutalist. It's meant to feel like an instrument panel, not a landing page.

Software you can operate by intent — safely. #SoftwareArchitecture #SystemDesign #FullStack #SaaS #AIEngineering #DistributedSystems #React #PostgreSQL #NodeJS #Python #ProductEngineering #WebDevelopment