JB_5000

Hey - small Aussie team here. It's 1am and we just open sourced ContextUI.

It's a local-first desktop app for building and running visual AI workflows. TSX-based UI modules, full filesystem/CLI/GPU access, works offline with no cloud required.

Workflows can be published to the Exchange - others install and run them locally with deps resolved automatically.

Agents can create workflows and immediately test/run them in the same runtime.

Desktop app is Apache 2.0. ~300 users, ~230 workflows published.

Tell us what's awesome and what's terrible

Ubuntu. Its great. So much cleaner and userfrienly then Microsoft. Definitely don't need to be a dev to work in Ubuntu anymore. Honestly, I don't know how microsoft is holding its base.

ai doesnt replace engineering. it compresses execution. abstraction always moves up. assembly to compilers to frameworks to cloud. same pattern.

real risk isnt ai taking jobs. its people becoming prompt approvers who dont understand systems or failure modes.

fundamentals still win.

cool idea and nice execution. highlights how far browser-native tools have come. curious how deep the DSP actually goes though — is this more a creative sketchpad or something you could realistically build full tracks with long term.

good breakdown of the tradeoffs but it kinda stops at critique. explains why age verification becomes invasive but doesnt really propose what a workable alternative looks like. feels like we need concrete models or architectures not just pointing out the trap.

i think everything is shifting, not dying.

local-first tools make sense and new patterns/protocols will emerge from that. but convenience always wins, so web utilities won’t disappear — they’ll just evolve.

actually respect this.

feels like more solo builders are realising agents arent about intelligence, they’re about constraints — DSLs, deterministic layers, boring hybrid architectures.

you stop writing code and start designing guardrails. curious how this scales though.

AI can also be a massive democratiser. Lowering the barrier to building means more people can create accessible tools, not just large teams.

GPU simulation isn’t just speed, it changes what’s possible to design. Whoever iterates fastest wins, not whoever starts smartest.

Interesting benchmark, but worth noting the methodology: skills are generated before the task, with no feedback loop. In practice, useful skills tend to emerge from doing — you attempt, observe what failed, then codify what worked. Generate → execute → observe → refine. The paper tests cold generation, which is a different (and less realistic) setup.