Tell Codi what you want to build. It writes the plan, runs AI agents in parallel across all your projects, and picks the cheapest model that can do each task, so you ship more and spend less. When you add a project it writes the charter and task list itself, and only pulls you in when a decision needs you, through one inbox.
Hi, I'm Shreyans, one of the makers.
I built AskCodi because I got tired of babysitting AI. Every tool I tried turned building software into a second job. Pick the model, paste the context, wire up the agents, then sit there watching a run and hoping it didn't go sideways. I was spending more time operating the tool than shipping with it.
So we made the opposite of that. You hire Codi, an AI CTO that lives on your Mac, and you talk to it the way you'd talk to a real one. You don't manage a fleet of agents. You manage one person, and that person runs the team.
You've probably seen tools that give you a control center for your agents: terminals, panes, worktrees, all of it yours to drive. This is the opposite. I didn't want a bigger cockpit. I wanted to hand the work to someone and step away.
A few things I'm proud of, and would love you to poke holes in.
Before Codi writes a single line, it sits down and learns the project. It asks what you're building, who it's for, and what it should never touch without checking, then drafts a plan from your answers. So it builds the thing you meant, not the literal words you typed.
You never choose a model again. Codi decides task by task. Cheap models for the boring parts, the expensive ones only where they earn it. In our own use, a week of work came out around a dollar, instead of the fifteen-ish it costs to run a frontier model on everything.
And it doesn't need you sitting over it. Codi already knows what's next from talking to you, so it keeps working in your off-hours when tokens are cheaper. You close the laptop, it keeps going, and the calls that are actually yours are waiting in an inbox the next morning. That's really the whole product: a chat and an inbox.
It also isn't one thing at a time. Codi runs sessions in parallel across every project you have, so you can kick off work on three repos before your coffee is ready and let them all move together. It's the closest I've felt to running a studio on my own.
Honest caveat, since I'd rather you hear it from me: it's early. The memory gets sharper the more you use it, and there are rough edges we're still filing down. If you try it, I most want to hear where it annoyed you.
One aside: AskCodi also has an OpenAI-compatible API, if you'd rather build on the orchestration than talk to it. The app is what I'm here to show you today, but the same brains are a call away.
It's on Mac(Windows coming soon), free to start on your own Claude subscription. Ask me anything, I'll be here all day.
Running in my off-hours is the feature I'd want most and trust least. If a run goes sideways at 3am across three repos, what does the damage look like in the morning? Branches I can just delete, or does it touch main? Would help to know what the blast radius is before I close the laptop on it.
This is sweet, congratulations on the launch. “I didn’t want a bigger cockpit” is probably the best way to explain this. A lot of AI coding tools still make the user responsible for managing the machinery. The part I’d want to test is where Codi draws the line between moving ahead and stopping for approval. On a real project, that judgement matters more than model selection. How does it handle changes that look small technically but carry business risk, like touching billing, auth, production data, or a core workflow? That feels like the point where an AI CTO either earns trust or creates more work.
the /standup mode starting sessions "based on need and token usage left" is the detail I keep coming back to. when the budget is getting tight and you've got three projects going at once, who's actually making the call on which one gets the remaining tokens - do you set priority ahead of time, or is that Codi's own judgment in the moment based on what it thinks matters most?
The "ran your off-hours, we stopped hedging" point is the interesting one. Once Codi runs unattended overnight across several projects, what happens when one of those runs goes wrong, like a bad migration or a broken deploy, before a human sees it in the morning? Is there a rollback path per project, or does the human review catch it after the fact the next morning?
I have a small question for the dev team:
What kind of tasks has it been best at for you so far? Trying to figure out where it'd fit in my workflow.
@Sachin Sharma that answers it well, pausing and surfacing in the inbox instead of plowing ahead is the right failure mode. one follow-up: when validation keeps failing on the same branch, does Codi ever try a different approach on its own before giving up, or is a repeated failure always a hard stop that waits for you to redirect it?
Does it work with the Claude subscription I ready pay for, or is it a separate cost?
The Mac app plus API combo is interesting. Is AskCodi meant mainly for individual developers working locally on their own machine, or for teams that want to build AI workflow automation into existing engineering processes? The topic mix includes Productivity, AI Agents, and Vibe Coding Tools, so I’m curious where you see the primary use case landing first.
Thats a nice concept. How do you handle cases where you may need to use multiple models?
The inbox model for agent blockers is a smart way to cut the noise compared to watching a chat thread spiral. Curious how AskCodi scopes context between projects — does each project get its own isolated context window, or do the agents share ambient workspace state across the whole account? Also wondering if there is a mode where sensitive code stays local and only higher-level summaries go to the cloud.
@shreyans_assistiv Congratulations for your launch. Does Codi work across multiple projects simultaneously, or is it limited to one repo at a time like other AI coding tools? The description mentions "parallel across all your projects", just wanting to confirm if that means true multi-project orchestration from a single inbox.
the overnight autonomy part is what I keep coming back to. if Codi picks a wrong approach at 2am and just keeps going since nothing hit the "needs a decision" bar, do you find out in the morning after it burned hours down a bad path, or is there some checkpoint that catches a run going sideways before it eats your whole night's budget on the wrong thing
@shreyans_assistiv congrats on the launch. Which models do you find are being used most often?
congratulations on the launch! What is the differentiation here between AskCodi and me instructing my agents to run in parallel while using the most optimized models for a given task in Cursor or Conductor? In my mind I just create a skill about this but I could be missing something.
Congrats on the launch. The routing question is already well covered above, so a different one.
The part I would poke is memory over long unattended runs. "Remembers your whole codebase" plus "keeps working in your off-hours" is the exact case where drift bites. On a long run the working context gets summarised to stay affordable, and a summary of the codebase slowly stops matching the codebase. Nobody is watching, so the agent keeps building confidently against a picture that has gone stale.
So my question, does Codi re-read the actual files as ground truth during a run, or does it work from its remembered version of them? Because for a supervisor running for hours with no human in the loop, what it remembers about the code and what the code actually says drift apart, and that gap is invisible until the mroning.
Not a gotcha, it is the thing I get wrong most on long agent runs myself.
This is a great product, I was skeptical at first. I use co-work right now, but this really work done
@shreyans_assistiv I tried new version, What happens if I update the feature board while the agent is running on the task?
About AskCodi on Product Hunt
“Orchestrate agents at scale while reducing cost”
AskCodi launched on Product Hunt on July 23rd, 2026 and earned 263 upvotes and 74 comments, placing #5 on the daily leaderboard. Tell Codi what you want to build. It writes the plan, runs AI agents in parallel across all your projects, and picks the cheapest model that can do each task, so you ship more and spend less. When you add a project it writes the charter and task list itself, and only pulls you in when a decision needs you, through one inbox.
AskCodi was featured in Mac (103.6k followers), Productivity (656.8k followers), Artificial Intelligence (474.3k followers) and OpenAI Day (9 followers) on Product Hunt. Together, these topics include over 266.5k products, making this a competitive space to launch in.
Who hunted AskCodi?
AskCodi was hunted by Shreyans Bhansali. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
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Shreyans Bhansali