Thoughts on AI workflows for PMs — starting with requirement management.
When shipping gets cheap, iteration stops looking like versioned releases and more like a live experiment loop. The scarce work moves upstream: choosing what to validate, telling directional signal from noise, and reframing MVP as a minimum learning unit.
Inspired and Escaping the Build Trap keep saying the same thing: don't turn product managers into feature-driven PMs. The real problem isn't what feature to build—it's that product thinking gets pushed out when 'pushing features forward' becomes the only goal. We're building to move PM time from feature management back to problem discovery.
If you've worked as a product manager, you've almost certainly come across Aha! or Productboard. They're solid tools. Many great teams use them, and they've shaped how modern product teams think about roadmaps and prioritization. So why build something new?
There are plenty of competitor analysis tools on the market. But tools that are truly built for Product Managers are still very rare. Most competitive intelligence tools are designed with Marketing in mind.
We started with AI writing PRDs and release notes — but quickly learned the real value is continuous signal tracking, insight discovery, and helping PMs decide what to do next.
