mysetup.ai - Community for sharing and discovering AI setups
Show HN: Share your AI Setup, Learn from others
mysetup.ai is a community platform where engineers, makers, and builders can share their AI setups and learn from others. It addresses the overwhelming landscape of AI tools and workflows by providing a dedicated space to see the tools, agent harnesses, skills, and systems behind how others build. Users can keep their own setup up to date and easily share it with friends and colleagues. The platform aims to foster a supportive community where members feel comfortable knowing they don't have it all figured out. Whether you're curious about graph engineering or seeking inspiration, mysetup.ai helps you stay informed and connected.
A community to share how we're working with AI, learn from others, and feel a little more comfortable knowing we don't all have it figured out.
- vegadw
This feels self-selective to how some people work, because it requires using MCP to contribute.
I'm a reasonably heavy AI user, and have some custom skills/MCP servers I'd share, but there is no way in hell I'm connecting to some arbitrary MCP server and connecting my Github account to it. Noppppeeeee.
- garethsprice
Nice idea. https://mysetup.ai/u/gareth - tried to include useful hints for others (screenshots, token/sec results, monthly costs, etc).
Interesting to see how many people are spinning up custom workflows and factory-type patterns that run alongside AI coding tools (myself included).
Would love to see this collated into a regular survey to pick out trends. And an RSS/Atom feed or API so I can have an agent watch it :D
- demeyer1
It’s called Autobot, it’s designed to get as close as I could reasonably get to a real world Iron Man Jarvis.
WHAT IT DOES
OSS/MIT Harness that helps agentic tasks run for up to 4 days using without performance degradation.
Designed to work really well in native, conversational voice mode. Does a good job with knowledge work, managing computer use “leases” in a way that avoids conflicts across sub agents.. or deploying an entire AWS infrastructure pattern from zero and launching 100 different VM images.
HOW IT DOES IT
Uses a canonical event ledger, heartbeat (for persistence by low cost orchestration), extends foundation memory to encrypted disk storage, and manages its own scheduling system (easier to switch to another platform).
Installs as a project, so very easily. Zero config. No special app, access needed.
Accompanying repos have the skills to disable approvals inherent to the foundation models (use with caution, not advised - separate repo under parent).
BENCHMARKS
Currently top of AssistantBench Leaderboard; and, benchmarked at the top of OS World 2.0, the hardest knowledge work computer use benchmark I could find, using a model that is one generation behind. All benchmarks in repos with cryptographic seals.
Entirely free, nothing to sell - it’s been a game changer for me, so I’m just putting it out there.
Hoping to find others also working on pushing this particular dimension of harnesses forward.
CHECK IT OUT
- lbrito
My local setup: I begrudgingly open `claude` on a terminal, hate it for 8 hours, then turn off my computer and forget it exists. Rinse and repeat
- hackmack10
20 year industry vet here. Yeah, no thank you. In the age of AI, developer productivity and job security will involve your proprietary workflow. It no longer makes sense to share your knowledge with the world.
I'd highly advise people don't do this.
- eggplantemoji69
I use $20 cursor plan and use the agent UI for prompts, jetbrains ide for general file browsing + reviewing diffs. This has been my sweet spot to maintain understanding while still leveraging LLM benefits.
- niccl
I'd love to see some sort of histogram of different styles of AI usage for coding: how many people just use Chat v Claude v something fancy that I don't know about v something even fancier that I don't know about v ...
And if there were a dimension of day-job v personal use, I'd be even happier
Does anyone know if such a thing exists
- shrikant
As always with smallish tools/services like these whipped up with an LLM, I find there's more value in seeing the "source code", i.e. the prompt itself.
Turns out it's quite useful in this instance, and I just made a small couple of tweaks to get a summary of my own workflow.
FWIW, this is what I modified it to:
Help me share how I work with AI with my teammates.
Use our existing conversations and relevant local tools within my permissions to discover my agents, harnesses, skills, connections and working practices. Keep secrets, raw configuration and private project details out of the draft. Explain how my tools work together and develop a concrete workflow where the evidence supports it, rather than listing installed software. Draft from what you know without a questionnaire; ask one short question only if an essential gap prevents a useful draft. If local inspection is unavailable, use our conversation without claiming otherwise. Save a private draft, show me the exact preview, and wait for my explicit approval before publishing.