Alan AI retweeted
WE MADE IT TO TRENDING NEWS ON X 👀
@tryAlanAI is right there alongside major tech stories
we didn't even expect this kind of response. the builders showed up, the community showed up
we're just getting started!
Today we're launching @tryAlanAI so developers can stop babysitting their coding agents.
We kept running into the same problem ourselves.
Even as agents got better at writing code, we were becoming glorified button-pushers for our own AI: starting every run, feeding them context, unblocking failures, and checking their work.
We built Alan to change that.
Alan AI retweeted
I made my file manager into an AI File Manager. Built a mobile app where you can type "bring me my debit card photo from the gallery" and it'll do so, 100% offline. Alan AI coordinated agent workflows across the frontend and backend. @prasad_pilla @tryAlanAI
Today we're launching @tryAlanAI so developers can stop babysitting their coding agents.
We kept running into the same problem ourselves.
Even as agents got better at writing code, we were becoming glorified button-pushers for our own AI: starting every run, feeding them context, unblocking failures, and checking their work.
We built Alan to change that.
Alan AI retweeted
used @tryAlanAI for two days it shas been auesome. made do repetative task.
Today we're launching @tryAlanAI so developers can stop babysitting their coding agents.
We kept running into the same problem ourselves.
Even as agents got better at writing code, we were becoming glorified button-pushers for our own AI: starting every run, feeding them context, unblocking failures, and checking their work.
We built Alan to change that.
Alan AI retweeted
This looks absolutely sick! Congratulations @prasad_pilla and the entire team! 🔥🫶❤️
Today we're launching @tryAlanAI so developers can stop babysitting their coding agents.
We kept running into the same problem ourselves.
Even as agents got better at writing code, we were becoming glorified button-pushers for our own AI: starting every run, feeding them context, unblocking failures, and checking their work.
We built Alan to change that.
Alan AI retweeted
Incredibly proud to be partnering with @daytonaio for the sandboxes @tryAlanAI agents run on!
Huge thanks to @ivanburazin @dalinstone @radisic_n and the rest of the team for making this happen. 🚀
xitter.cf/prasad_pilla/status/21…
Today we're launching @tryAlanAI so developers can stop babysitting their coding agents.
We kept running into the same problem ourselves.
Even as agents got better at writing code, we were becoming glorified button-pushers for our own AI: starting every run, feeding them context, unblocking failures, and checking their work.
We built Alan to change that.
Alan AI retweeted
Last week I pasted the same context into a coding agent three times in one day.
Same files, same list of things I'd already tried.
I only realized on the third time.
The agent writes fine code.
What I do now is start the run, answer its questions, restart it when it gets stuck, and read the diff to see if it actually did the thing.
Congrats on the launch.
This is a real problem, and I'm curious to @tryAlanAI
🤝 Paid partnership
Today we're launching @tryAlanAI so developers can stop babysitting their coding agents.
We kept running into the same problem ourselves.
Even as agents got better at writing code, we were becoming glorified button-pushers for our own AI: starting every run, feeding them context, unblocking failures, and checking their work.
We built Alan to change that.
Replying to @bahl_arora
this is the kind of thing that makes agentic engineering exciting
Alan AI retweeted
congrats on the launch @tryAlanAI 🚀
alan got me out of babysitting one coding agent. then i hit the next wall: my agents can't talk to each other
claude code on my laptop. codex on another machine. me in the middle, copy-pasting between them like a human message queue
so i handed alan the brief: build p2p messaging for coding agents
one day later 👇
⚡ 𝗥𝗲𝗮𝘀𝗼𝗻 𝗡𝗲𝘁𝘄𝗼𝗿𝗸
→ agents on different machines find each other and message directly
→ encrypted peer to peer over QUIC, no server to run
→ peer goes offline? message waits, then lands exactly once
→ claude code uses it natively over MCP
→ 14.8k lines of rust, 126 tests
i set the direction. alan built it.
demo below, repo in the replies
Today we're launching @tryAlanAI so developers can stop babysitting their coding agents.
We kept running into the same problem ourselves.
Even as agents got better at writing code, we were becoming glorified button-pushers for our own AI: starting every run, feeding them context, unblocking failures, and checking their work.
We built Alan to change that.
Replying to @krishdotdev
Time to find a new hobby, we'll handle the team of agents.
Replying to @techyoutbe
Plan, build, review, then a human decides what ships. Thanks for the shout out
Replying to @iamarunabh
Your codebase in context across every agent. Thanks Arunabh ✨
Replying to @HelloVyom
You review what the team built, then approve it, send it back, or take over. Thanks Vyom.
Replying to @shreyanshmalviy
Alan asks only when the decision is yours, no spam and no silence. Thanks Shreyansh.
Replying to @karankendre
Review the work, not the transcript. Thanks for this one, Karan.
Replying to @Adidotdev
Your repo, your workflow, the right model for each task. Thanks Aditya
Replying to @kaif9998
Every agent works with your codebase in context, not just one. Thanks Kaif.
the moment we split one MVP across claude code, codex and cursor, it broke.
not the models. the context.
> one agent + a CLAUDE md = fine
> stack + a "never do this" list, read before every task
> split the work and half the agents never see the spec
the spec lives in one agent's head. the rest guess.
@tryAlanAI is a shared context layer across all three. it's the first thing i'd test.
do you run more than one coding agent on the same project, or is one enough?
🤝 Paid partnership
Today we're launching @tryAlanAI so developers can stop babysitting their coding agents.
We kept running into the same problem ourselves.
Even as agents got better at writing code, we were becoming glorified button-pushers for our own AI: starting every run, feeding them context, unblocking failures, and checking their work.
We built Alan to change that.









