AI CPO for founders
Building is cheap now. Product judgment is not.
Talk to an AI CPO in Slack that helps you choose the right first customer, compare opportunities, run the right experiments, and decide whether to build, pivot, defer, or narrow the bet.
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Problem
Founders can ship faster than ever. That still does not tell them what deserves to exist.
Most early products do not fail because nobody could build them. They fail because founders kept building into uncertainty.
Building got cheap
You can ship in days with Cursor, Claude, Lovable, and coding agents. Shipping is no longer the bottleneck.
Judgment did not
The hard part is knowing who to target, what to test, what message to use, and when to stop.
Thrash gets expensive fast
Founders lose weeks on the wrong segment, the wrong pitch, or the wrong feature because the next move is still fuzzy.
What It Is
An AI CPO for founders, not a PM tool with AI bolted on.
You talk to it in Slack like you would talk to a sharp product lead. It helps you think through customer segments, opportunities, experiments, and next moves without making you do fake enterprise product management.
The dashboard is the evidence room. Slack is the working relationship.
Let the agent
- Run experiments autonomously while you keep oversight
- Define budget limits tied to signal, not guesswork
- Suggest ICPs and how to speak to them
- Propose distribution channels you haven't tapped yet
- Implement learnings from experiments and discovery in the next testing loop
What It Does
It compares opportunities, runs the next tests, and pushes toward a decision.
Pick the best first customer
Compare multiple ICP and segment hypotheses before collapsing to one active target.
Surface the next best opportunity
Find the strongest bet to test next, from a new segment to a pricing angle to a feature wedge.
Turn opportunities into experiments
Get concrete tests instead of generic advice and keep moving without building PM ceremony around yourself.
Sharpen positioning and messaging
Pressure-test the promise, not just the product, and adapt the message as evidence changes.
Update confidence over time
Track what was tried, what happened, and what should happen next without losing the thread.
Hand validated work to your agent
When the signal is strong enough, convert the learning into a build brief a coding agent can execute.
How It Works
Start with the problem. Test the demand. Pressure-test the solution. Decide what deserves to become product.
Evidence loop
Slack is where you work. The loop is how the AI CPO keeps the problem, demand, solution, and product call tied to the same evidence.
Start with the problem you think is worth solving. NWB surfaces complaints, workarounds, and demand signals worth paying attention to.
Evidence loop
Slack is where you work. The loop is how the AI CPO keeps the problem, demand, solution, and product call tied to the same evidence.
Problem
Start with the problem you think is worth solving. NWB surfaces complaints, workarounds, and demand signals worth paying attention to.
Demand
Will anyone pay? NWB handles the heavy lifting and brings back the signal you need to make a real decision.
Solution
Does this resonate? Test your positioning and proposed solution against what the market is actually telling you.
Product
What do you do next? Turn the evidence into a call: double down, reposition, narrow, or stop. Then run the same process on the next bet.
Why It's Different
Most tools
Collects feedback and feature requests
AI CPO
Helps decide what is worth building
Most tools
Supports PM workflow
AI CPO
Provides product judgment
Most tools
Creates notes, docs, and summaries
AI CPO
Drives decisions and next actions
| Most tools | AI CPO |
|---|---|
Collects feedback and feature requests | Helps decide what is worth building |
Supports PM workflow | Provides product judgment |
Creates notes, docs, and summaries | Drives decisions and next actions |
Who It's For
Solo founders
You do not need a fake PM process. You need sharper calls on what deserves your time.
Vibe coders
You can build almost anything. This helps you decide what is actually worth building.
Early-stage teams
Before you hire a real CPO, get a product brain that can keep the signal, memory, and next move straight.
Trust And Control
The AI recommends. The founder decides.
This is not an unchecked autonomous agent making product calls behind your back. It can run a lot on autopilot, but the founder stays in control.
You can see the reasoning, the evidence, the tradeoffs, and the recommended next step. Sometimes the right answer is build faster. Sometimes the right answer is stop.
In practice
Autopilot
Can gather evidence, draft experiments, organize follow-ups, and keep the memory straight.
Approval
Founder approval gates the bigger calls. It should feel trustworthy, not magical.
Memory
Every opportunity, experiment, and learning stays visible in the evidence room for later review.
Get Started
You do not need another dashboard full of notes. You need clarity on what to build next.
Get an AI CPO that can hold the context, compare the real bets, and tell you what deserves your next week.
We'll notify you at launch and send occasional updates. Unsubscribe anytime. Privacy policy
FAQ
What does early access cost?
Early access is $49/mo. Joining the waitlist does not charge you today. We'll share details before billing starts.
Is this a product management tool?
Not in the normal sense. It is not a roadmap board, feedback repo, or workflow system. It is an AI CPO for founders who need better decisions.
Do I need users already?
No. It is useful before traction and after. If you are still figuring out the first customer, first wedge, or first credible test, that is the point.
Is this just for vibe coders?
No. It is for any founder or early team that can build quickly and needs clarity on what deserves to be built next.
Does it replace my judgment?
No. It improves your judgment. It recommends, explains the evidence, and pushes toward a decision. The founder still decides.
What does it actually do in Slack?
You can ask who to target, what opportunity looks strongest, what experiment to run next, how the message should change, or whether the current idea is worth more effort.
What happens when something is validated?
It turns the learning into a build brief so you can hand it to a coding agent and move with more confidence.