Six months ago I started building an AI agent I actually wanted to use.
Not another LangChain wrapper — a single, self-hosted system that gets
measurably better the more I work with it.
This week I cut the v0.1.0 release.
What it is
Hyper Nexus is a self-hosted AI
agent with:
- A 30-minute self-improvement heartbeat that mines your agent's
own logs for successful patterns, clusters failures, and writes
learned heuristics back into the system prompt. - An "ADHD" cross-domain reasoning module — for non-trivial
tasks, the agent fires the problem across 8 knowledge domains
(biology, physics, music, economics, architecture, game theory,
neuroscience, military) in parallel, then synthesises analogies back
into the prompt. - 165 tools, 25 skill packs, ~100 integration connectors in one
pip install. - Dual-layer memory with Ebbinghaus-style forgetting.
- 100% local.** Vision (Florence-2) and embeddings (MiniLM) run
on-device. MIT licensed.
Stack: FastAPI, SQLite, PyTorch, vanilla JS WebUI. ~60K LoC of Python.
Why I built it
When I started this, I thought: why not try to model something close
to how humans actually think? The result isn't fully polished, and
there are real shortcomings — but I'd love feedback so I can keep
improving it. This is going to be an open-source project, and I want
it to grow with the people who use it.
What I learned building it
Lesson 1: The hard part is not the LLM call.** It's everything around
it — tool execution, error recovery, state management, the agent's
"short-term memory" of what it's already tried, the user's long-term
context. The actual prompt is maybe 5% of the code.
Lesson 2: Tests matter even for solo projects.** I shipped v0.1.0
with zero automated tests. I regret this. If you're reading this and
considering the same — don't.
Lesson 3: Don't promise self-improvement you can't measure.** I have
a 30-min heartbeat that does something. Whether it actually makes
the agent better at your task is unmeasured. I'm working on an eval
harness to find out.
What's next
- Build an eval harness (the biggest gap)
- Add a few demo tasks the agent does well, recorded as GIFs
- Get more contributors
If you try it, please open an issue — that's the only way I can
prioritise what actually breaks vs what I think breaks.
Let's make something meaningful.
GitHub: https://github.com/Hsosn/HYPER_NEXUS
MIT licensed. PRs welcome.