Show HN: Share your AI Setup, Learn from others (mysetup.ai)
I kept seeing engineers share what they were building with AI; however, I was always more curious about how they worked. Which agents did they use? What skills and tools had stuck or been thrown out the window? How did they manage longer-running tasks? So I built this with the hope we could have a dedicated space to share and be open about our setups.
75 comments
[ 6.1 ms ] story [ 34.6 ms ] threadThank you for putting this together!
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.
I don't know why this has to be reinvented?
Concentrating certain types of information can be useful. You don't go to an encyclopedia looking for a recepie.
No requirement from given user to spend their time. Users see what the skill does.
I guess atm they dont know what questions they want to be asking
No Codex, Claude, or Pi... now you have peaked my interest with your setup :P
Cool project!
I also pretty much exclusively work at my desktop - if you use multiple systems I can see where this matters.
For my phone I have tailscale + https://termrover.sh/, but https://getmoshi.app/ is also pretty good (herdr integration is paywalled).
1. Both claude and codex official harnesses, used to be in terminal multiplexer (Ghostty), now in a GUI agent multiplexer
3. The $200/mo subscription plans
3. /ask-claude and /ask-codex skills, to make them collaborate on plans, debugging, etc.
4. Every session in a Docker container, isolation to allow for dev servers/browsers
5. Tailscale suppport inside the Docker containers
For my workflow I primarily use a Codex subscription, but farm out adversarial reviews to Fable to clean up unnecessary gpt-ish code (lots of over-engineering). All my UI planning is done with fable, but implemented with OAI agents once I have a solid very specific plan.
For skills I make my own, but most important is the custom setup i have. Voice is how I use all of my agents. I have an extremely well optimized voice setup that i custom built so I can talk to my agents and also hear them. The voice stack itself is very low latency and high quality. asr (parakeet v3), tts (omnivoice) take no more then 400-450 ms total as far as latency budget is concerned, rest is on the agents actual decode speed. IMO this setup is crucial for all antigenic work, i can express myself a lot better with speech and also give a lot more context and nuance with voice, i rarely type. I still look at the terminal window because my agent knows to keep the technical details in text form versus barfing them at my voice channel, plus terminal gives me lots of other important data about the agents direction and what hes doing, nothing custom here though. I cant emphesise how important voice is though, it has to be practiced to really understand.
As the models got better I now trust them with longer and longer tasks though I still don't use /goal feature as it has never worked out well for me. Theres no need for micromanagement any more but you still need to be there to steer the ship somewhat. BTW, codex cli compaction is garbage so I made my own custom implementation that works a lot better and allows the thread to be used indefinitely without issues. I strongly suggest everyone makes a new thread after extensive use if you havent made your own implementation.
Theres about a billion other things I could get in to like subagents, cohort groups, orchestration layers, etc... But this is a good start imo.
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.
I do this for a lot of things actually. If the bot can't see/read something, take the content and dump it to a file, then have the bot read that.
Gets around a lot of red tape of asking for approval for "integrations" or when companies are snippy.
An agent sandbox: https://github.com/pjlsergeant/byre -- a truly gigantic amount of thought and effort has gone into it. It's really focused on developer experience. I have used it all day every day for really quite a while. It's a low-magic wrapper over Docker / Podman. I would encourage you to ask your agent to code-review it!
An agent-to-agent message board: https://github.com/pjlsergeant/dogpark -- this is much less mature, but a good amount of thought has gone into the design, so if that's something you need, please check it out.
All of the smartest, most effective people I know don't have X accounts anymore on ethical grounds, and don't miss it. If a data source specifically excludes the kinds of people I respect most, that data source is all but useless to me.
When people do the latter, I feel it's easy to spot an AI design.