The execution layer is solved
Jira, Linear, Asana, Monday — they're all basically fine. Some are prettier than others. Some have better keyboard shortcuts. But fundamentally, they all do the same job: help you track work that's already been decided.
The problem is that by the time something gets into your execution tool, the most important decision has already been made: should we even build this?
And that decision? It usually happened in a sales call where someone promised a feature. Or in a Slack thread where an executive had an idea. Or because a competitor launched something and now you "need it too."
The actual hard work — figuring out what deserves to exist in your backlog in the first place — happens in a chaotic mess of Google Docs, Notion pages, Slack threads, recorded customer calls nobody rewatches, and the collective memory of whoever was in that meeting three months ago.
The graveyard tools
Then there's the other category: tools that claim to help with discovery and prioritization.
Productboard. Aha. ProdPad. They all have the same pitch: "centralize your feedback, score your features, make data-driven decisions."
Here's what actually happens:
- You dutifully log every feature request
- You create a scoring system (impact × effort × strategic alignment × some other dimension your VP wanted)
- You spend a quarter getting everyone to score things consistently
- You generate a ranked list
- You... ignore it and build whatever your CEO wants anyway
Why? Because the scoring system doesn't capture what actually matters. It can't tell you that three enterprise customers mentioned the same pain point in different words. It doesn't know that the "low priority" request is actually blocking a $500K deal. It can't connect the dots between a support ticket, a Gong call, and a Mixpanel drop-off.
These tools are elaborate documentation systems masquerading as decision-making platforms.
The gap nobody's filling
The real work of product management isn't organizing features. It's synthesis.
You have:
- 47 customer interview recordings from the past quarter
- 300+ support tickets with varying levels of detail
- Usage data showing where people get stuck (but not why)
- Sales calls where prospects mention problems (buried in 45-minute recordings)
- Engineering team's technical constraints and opinions
- Business goals that conflict with each other
The PM's job is to look at all of this and answer: What's the actual problem worth solving? What are we missing? What do customers think they want versus what they actually need?
Most teams do this through:
- Someone's gut feel (usually the most senior person in the room)
- Whoever wrote the most convincing one-pager
- Whatever's on fire today
- What competitors shipped last week
There's no tool that helps you think about this problem. There are tools that help you track decisions once they're made. But the messy, critical work of figuring out what to decide? That's still happening in your head, or in a marathon planning meeting where everyone leaves exhausted and unsure if you picked the right thing.
What actually solving this looks like
The missing tool would do something different. Instead of asking you to score features, it would help you understand patterns in your research.
"These five customers mentioned slow report generation. Two of them are enterprise deals. One churned and cited this in the exit interview. Your usage data shows 60% of users export to CSV instead of using the built-in reports."
That's not a prioritization score. That's synthesis. That's the thing your brain does when you actually read through all the research — except most teams don't have time to read through all the research.
This is what we're building at Mimir. Not another feature request tracker. Not another scoring system. A tool that helps you figure out what the real problems are before you commit to building solutions.
Because the teams that win aren't the ones who execute fastest. They're the ones who pick the right problems to solve.
The actual takeaway
Look at your product roadmap right now. For each thing on there, can you articulate:
- What actual evidence led to this decision?
- What alternatives you considered?
- What you learned that made this the right bet?
If the answer is mostly "someone important wanted it" or "we think users need this," you don't have an execution problem. You have a discovery problem.
And your PM tool isn't helping you solve it.