Task Monki is an open-source desktop app for managing coding agents from task to pull request. Run several tasks at once, follow each agent’s progress, preview every result without manually setting up services or containers, send work to another agent for review and fixes, and bring multiple agents into the same discussion, where they can respond to each other, compare approaches, and challenge assumptions.
I started Task Monki because I was using coding agents for more and more of my work, but managing several agents, previews, reviews, and follow-up fixes still required too much manual work.
The goal is to bring that whole process into one app and automate as much of it as possible. It is open source, and I’d really like to hear how other people are using coding agents and what is still missing from the process.
The full flow looks useful. When one agent reviews another, does it get the exact diff, test results, and original task context, or mostly a summary? That handoff seems like an easy place for important details to disappear.
You asked what's still missing, so — previews for serverless.
Your answer above covers the case where the app is a set of services you can bring up with Compose. Mine isn't. It's Lambda behind API Gateway with DynamoDB, and there is nothing to compose up. My equivalent of your preview is either deploying a throwaway stack per task or emulating locally, and both are slow and lie to you in different ways.
That matters more with parallel agents than with one, because the whole point of running four tasks at once is seeing four previews. Is a deploy-per-task preview backend something preview.yaml could ever express, or is local-services-only the intended scope?
@rojhattoptamus When you run several tasks at once against the same repo, do the agents work in isolated checkouts or worktrees, or is there a chance two tasks touching overlapping files step on each other before either gets reviewed?
Nobody's asked about cost yet, and Discourse mode is the part that worries me on that front. Lead proposes, Skeptic and Verifier challenge, Lead revises - that's already 3x the token spend of one agent, and if it can loop multiple rounds when they disagree, running several of these panels at once across parallel tasks could get expensive fast without you noticing until the bill shows up. Is there a running cost/token counter per task, or a cap on how many back-and-forth rounds Discourse will do before it just hands you the disagreement instead of continuing to argue it out?
Multiple agents reviewing each other is the part I am least sure about. The times I let one check another's work, it mostly agreed. The disagreements I actually need still come from me reading the diff myself, which is slow, and I have not found a way around it yet. You asking what is still missing from the process is the reason I replied at all. Good luck with the launch today!
the multi-agent discussion feature is honestly pretty wild, watching two agents go back and forth on approach is way more useful than i expected for catching blind spots in a refactor
The multi-agent discussion where agents can respond to each other and challenge assumptions is what catches my eye, but I would want to know what happens when two agents land on genuinely conflicting approaches — whether the app surfaces that disagreement for me to resolve, or whether one output just wins by default. The container-free preview is also interesting: is that a local port serving a web preview, or something closer to a sandboxed execution environment? That distinction matters a lot for whether it can handle full-stack apps or mainly covers static output.
the "bring multiple agents into the same discussion so they can challenge assumptions" part is what catches my eye. when two agents actually disagree in there - one says the approach is fine, the other flags a problem with it - what breaks the tie? does it surface as an open disagreement for me to resolve, or does one agent's take win by default (most confident, last word, whichever finished first)? that seems like the moment the whole point of having them argue either pays off or quietly gets lost
About Task Monki on Product Hunt
“Run coding agents through the full development process”
Task Monki launched on Product Hunt on July 29th, 2026 and earned 118 upvotes and 13 comments, placing #9 on the daily leaderboard. Task Monki is an open-source desktop app for managing coding agents from task to pull request. Run several tasks at once, follow each agent’s progress, preview every result without manually setting up services or containers, send work to another agent for review and fixes, and bring multiple agents into the same discussion, where they can respond to each other, compare approaches, and challenge assumptions.
Task Monki was featured in Task Management (84.2k followers), Open Source (68.7k followers), Developer Tools (516.6k followers) and GitHub (41.3k followers) on Product Hunt. Together, these topics include over 128.1k products, making this a competitive space to launch in.
Who hunted Task Monki?
Task Monki was hunted by Rojhat Toptamus. 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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