MakersClaw 2.0 turns a goal into the apps, agents and automations needed to get it done. We originally launched MakersClaw as AI employees that lived in Slack, Teams and Telegram. We rebuilt it around a different idea: instead of hiring an agent for a role, tell MakersClaw what you want done. It builds the tools for the job, runs them continuously, remembers the work and operates within a budget you set. Today it starts with go-to-market
Hey Product Hunt 👋 Shreyans here, maker of MakersClaw.
We first launched MakersClaw here in June as AI employees you could hire into Slack, Teams and Telegram.
Today we're relaunching as part of Astra Day, after rebuilding the product around a different idea.
MakersClaw is no longer primarily a chatbot you give a role to. You give it a goal.
MakersClaw figures out what needs to exist to pursue that goal — an app, an agent, automations, or some combination of them — builds those things into your workspace, connects them to your tools and runs the work.
Sometimes that means a research agent. Sometimes it needs a lead inbox, CRM, approval queue or recurring workflow. Instead of forcing every job through chat, MakersClaw can build the interface appropriate for the work.
Why we rebuilt it
AI made building software dramatically cheaper. A founder can ship a product in a weekend. But selling it is still weekly, repetitive, tool-heavy work.
We thought agents should be able to do much more of that work.
The problem with the agents we were using was that they were still session-based. They'd complete a task, lose context, ask to be restarted and wait for another prompt.
MakersClaw 2.0 is built around work that continues.
Tell it something like:
"Help me find and reach our first 50 customers."
You can watch the first run, inspect what it built, approve the important decisions and set a budget. After that, it can keep running and come back when it needs you.
Company files, decisions and results live in shared workspace memory, so agents can pick up where previous work left off rather than starting from scratch.
Today we're starting with go-to-market: research, content, outbound, follow-ups and the surrounding workflows. The App Store is still small and there are integrations we haven't tested deeply yet.
That's part of why we're launching now.
Try giving MakersClaw one real growth job you need done this week. If it gets stuck, builds the wrong thing or asks you to do something it should have handled itself, tell me here.
How mny new users did you manage to bring to your product today, and how much feedback did you get?
The idea of giving an agent a goal instead of just a task is really interesting. The part about it continuously running and building the workflows it needs around that goal is especially compelling.
Curious to see how this evolves as more real-world workflows get added. 🚀
Congrats on 2.0!
As a solo founder, selling is the part that never gets cheaper, so this looks very interesting. How does it adapt over time: does it tune its own outreach based on what gets replies, or does it surface that to me for my ultimate approval? Good luck today!
Really liked the shift from 'hire an ai role' to tell it the goal and let it build what's needed. Interesting direction
Seems like kind of the level of automation we have at grm.sh for feature delivery setup. So I wonder, did you manage to automate the whole tool lifecycle, with no human-in-the-loop?
How do you decide which runtime the agent should use?
Do you guys plan to have a broader agent runtime ecosystem?
Hey Product Hunt, Sachin here, the other half of MakersClaw 👋
Shreyans covered what it does, so I'll cover why it looks the way it does now.
Our first launch here in June looked like a pure win from the outside: #3 Product of the Day. Then the feedback came in. People loved the promise, opened the app, and got lost. We had built power before we built a path. The most useful lesson of my year: a leaderboard cannot tell you why users leave. People telling you to your face can.
So v2 started from one question: what is the smallest thing a founder should have to give us? The answer we landed on is a goal. Not prompt engineering, not workflow builders, not agent configs. You write "help us reach our first 100 customers" and the system works out what that needs: the research, the briefs, the apps, the automations, and it keeps them running inside a budget you set.
What we're still honest about: it plans and executes, but it won't close your deals, and the first runs deserve your review while it learns your company. We'd rather tell you that here than have you find out annoyed.
Two things I'd genuinely love from this community:
1. If you get lost anywhere in the product, say exactly where. That kind of comment is what rebuilt v1 into v2.
2. What's the first goal you'd hand to a system like this? Your answers here genuinely shape what we build next quarter.
Thanks for having us back.
About Makersclaw 2.0 on Product Hunt
“The operating system for a company run by agents”
Makersclaw 2.0 launched on Product Hunt on September 18th, 2026 and earned 149 upvotes and 28 comments, placing #10 on the daily leaderboard. MakersClaw 2.0 turns a goal into the apps, agents and automations needed to get it done. We originally launched MakersClaw as AI employees that lived in Slack, Teams and Telegram. We rebuilt it around a different idea: instead of hiring an agent for a role, tell MakersClaw what you want done. It builds the tools for the job, runs them continuously, remembers the work and operates within a budget you set. Today it starts with go-to-market
Makersclaw 2.0 was featured in Marketing (468.4k followers), Artificial Intelligence (478.9k followers) and OpenAI Day (38 followers) on Product Hunt. Together, these topics include over 205.4k products, making this a competitive space to launch in.
Who hunted Makersclaw 2.0?
Makersclaw 2.0 was hunted by Rohan Chaubey. 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.
Want to see how Makersclaw 2.0 stacked up against nearby launches in real time? Check out the live launch dashboard for upvote speed charts, proximity comparisons, and more analytics.
Rohan Chaubey
Hey Product Hunt 👋 Shreyans here, maker of MakersClaw.
We first launched MakersClaw here in June as AI employees you could hire into Slack, Teams and Telegram.
Today we're relaunching as part of Astra Day, after rebuilding the product around a different idea.
MakersClaw is no longer primarily a chatbot you give a role to. You give it a goal.
MakersClaw figures out what needs to exist to pursue that goal — an app, an agent, automations, or some combination of them — builds those things into your workspace, connects them to your tools and runs the work.
Sometimes that means a research agent. Sometimes it needs a lead inbox, CRM, approval queue or recurring workflow. Instead of forcing every job through chat, MakersClaw can build the interface appropriate for the work.
Why we rebuilt it
AI made building software dramatically cheaper. A founder can ship a product in a weekend. But selling it is still weekly, repetitive, tool-heavy work.
We thought agents should be able to do much more of that work.
The problem with the agents we were using was that they were still session-based. They'd complete a task, lose context, ask to be restarted and wait for another prompt.
MakersClaw 2.0 is built around work that continues.
Tell it something like:
"Help me find and reach our first 50 customers."
You can watch the first run, inspect what it built, approve the important decisions and set a budget. After that, it can keep running and come back when it needs you.
Company files, decisions and results live in shared workspace memory, so agents can pick up where previous work left off rather than starting from scratch.
Today we're starting with go-to-market: research, content, outbound, follow-ups and the surrounding workflows. The App Store is still small and there are integrations we haven't tested deeply yet.
That's part of why we're launching now.
Try giving MakersClaw one real growth job you need done this week. If it gets stuck, builds the wrong thing or asks you to do something it should have handled itself, tell me here.
I'll be around all day.