r/airesearch

I built JoeBro, a native macOS AI workspace that bundles its own Python backend inside the `.app` file. Standard library only. Zero third-party packages. You can grab it from the .dmg in the repo releases, or clone the repo, open the Xcode project, and hit Build. Either way works.

The new Tools tab has three tiers, all surfaced to the model in Agent mode as callable functions.

API Tools give any JSON endpoint straight to the model. You give it a URL, a name, a description, and optionally an API key and a method. Put `{query}` anywhere in the URL and the model input gets dropped in right there. The description tells the model when to call it. A weather API gets called when someone asks about the weather. A HackerNews search when the topic is tech. It just works.

MCP Servers are the Model Context Protocol over stdio. The app launches the server, discovers its tools, and offers them to the model. The connection is stateless. Spawn, initialize, call, kill. No long-running processes. No zombie children. There is a hard wall clock timeout on every interaction so a broken server never hangs a turn. The git MCP server returns real diffs. The model calls it, the server spawns, it runs, it dies, the diff comes back.

Plugins are the third tier. They are folders on disk that can ship their own tools, memory, and agent logic. They can be foreground (active tools the model can invoke) or background (guardrails that shape every turn). The bundled one is the macOS Use plugin. Dependency free. It controls the Mac through osascript and screencapture. No node module, no Python package, no Docker image. It calls System Events directly and the model can use it to open apps, click buttons, and take screenshots.

The agent calls memory, tasks, calendar, and plugins in one conversation. Looks like any other chat.

Search any public database right in chat. LinkedIn, Crunchbase, GitHub, you name it. Point API Tools at any JSON endpoint and the model calls it like a native function. No curated list — anything with a URL works.

Chats themselves can now be sorted into folders. Keep your side projects separate from work, or separate by topic. Just drag and drop.

The backend is still zero dependencies. But, based on some great advice from people on here, it is not one file anymore though. It grew to the point where that stopped making sense. So I split it into sibling modules. `jb_core.py` is the shared library. `jb_tools.py` handles every tool path including the custom ones. `jb_chat.py` has the agent loop. `jb_assistant.py` has memory, skills, tasks, and deep research. `jb_email.py`, `jb_calendar.py`, `jb_docs.py`, `jb_files.py`, `jb_models.py`. Still standard library only. Still zero pip install commands. Still one Xcode project, one Build, and it runs.

The tool dispatch in `jb_tools.py` routes every path in one place. Native function calls, XML tool blocks, custom API tools, MCP servers, plugins, macOS use. It is all there. The MCP client is stateless with a background reader thread so a hanging subprocess can never block a request. Every server interaction has a hard deadline. If it does not reply in time, the process gets killed and reaped and the turn continues.

Full repo: https://github.com/joexk1/JoeBro

Still open source. Still GPLv3. Still no telemetry, no account, no phoning home.

What we are doing on the Reserve is far more complex than anything the major technology companies are attempting today.
While they continue to train ever-larger models and optimise for clean benchmarks in controlled environments, our founder and team are running frontier systems through an entirely different standard.
On the Reserve, finding 500 errors a day is considered the bare minimum. Every single day, our founder and team relentlessly hunt for flaws, hallucinations, inconsistencies, and dangerous advice across AI, VR, AR, robotics, drones, lateral programming, systems architecture, sandbox environments, operational capacity, and especially AI-integrated robotic autonomy.
This is only part of the picture.
We are conducting advanced genetic experiments and cross-pollination trials to create highly potent, nutrient-dense versions of food, medicinal, and utilitarian plants. The entire Reserve is being engineered as a fully livable, edible, human-centric biome — a complete living system designed around human needs.
The Reserve is not just a polyculture farm in Queensland.
It is also home to the Saga Water System — a high-impact navigational array program designed to deliver purified water across the city limits of Paragraj. We are actively developing real-world solutions for large-scale water purification and distribution.
By August, Node 0.5 will become the first ever optimised field testing scenario for robotics in truly off-grid settings. While the world has been creating flashy videos of coffee robots at food stalls, we are preparing to test a robot that must grind out 500 coffees a day with no internet and no reliable power grid.
We are also open to other farms, technology groups, and serious crucibles — including Jeddah Barber, where we’re ready to test real barber bots in actual working conditions with real customers.
This is not a simulation. This is not a benchmark. This is sustained, real-world pressure where biology, technology, water systems, and human survival all collide.
The major labs and corporations are still focused on making their systems look impressive in controlled settings.
We are doing something far more difficult.
And here’s the invitation:
We’re open.
Whether you’re a university student who’s built something in their backyard, or a tinkerer working out of your mum’s basement — if you’ve built something real, we want to hear from you. You don’t need to spend thousands of dollars. We’ll adjust to your budget. We’ll test your technology under real conditions.
The Shed Challenge is active.
Come and see if your tech can survive the Reserve.