- Slack if you are going to be >5 minutes late to a meeting
- Focus on our goals, not the means. Stay big picture in meetings!
- Be clear with what expectations are for assignments and delegation
- Communicate early about time concerns. If you have constraints like a test, tell us!
- Disagree often! Be respectful and constructive. It’s okay to not know exactly what your critique is. Just give what context you can and explain that you’re not sure
- No contempt! Voicing concerns helps avoid this
From our round 1 interviews, we noticed that the questions were more broad and about their day-to-day lifestyle, and weren’t leaving much room to dive deeper into their struggles. So we decided to make the new questions more explicit and helpful when it comes to finding out the issues PMs in startups or in big companies are facing. Here are some of those questions along with the full interview script linked:
Collaboration and Ownership
- (If they work at a mid-sized or large company) How do you determine who owns what? How do you communicate about that?
- How do you handle situations where engineering, design, and business teams disagree?
Tools and AI
- Are there any products you use on a daily basis that feel inadequate?
- How do you learn about how to use AI products?
Friction Points
- When do you find yourself getting the most frustrated?
- What are you currently doing to alleviate that frustration?
Option 1: Too Many Priorities
- How do you decide what comes first?
- What gets delayed?
- What have you tried?
Option 2: Cross-Team Communication
- When did miscommunication last cause a problem?
- Who was involved?
- How was it fixed?
Option 3: Not Being Included in Decisions
- When did this last happen?
- Who was involved?
- What problem did it cause?
Option 4: Customer-Facing Bugs
- When did this last happen?
- What did you do next?
- How did it affect customers?
Interview Script
Interview Screener
Affinity Map (AI second pass) and Comparison
What did it catch that you missed?
It was very good at comprehensively mapping out the results from our interviews phrasing our insights in a more concise way, pairing them well with the exact interviewee that mentioned them. It was also useful in surfacing some insights our humans may have overlooked such as the AI not having your company’s context so not being all that useful from Bryce and Abby’s interviews. But mostly since we only asked it to give insights we hadn’t covered, there weren’t any major insights we had missed.
What did it flatten into something generic?
In some places it was asserting exaggerated conclusions e.g. the healthcare startup PM only mentioned that she has to do a lot of repeated iterated work based on customer feedback and how customers a lot of the times misinterpret how a product is supposed to be used which can be frustrating, but the AI automatically drove a conclusion saying “Customer customization demands pull PMs away from the core product, and AI removes the “no capacity” excuse.” which isn’t necessarily true because for the healthcare startup PM, the core product depends on user feedback itself.
Did it assert anything that isn’t in the transcripts?
Not necessarily, but it was incorrectly grouping correct evidence from the transcripts with insights that aren’t necessarily what the evidence suggests.
Long List
Who conducted each interview
| Interviewee | Who conducted it |
| Healthcare PM | Aimen |
| Coinbase PM | Aimen |
| Bryce | Elline |
| Abby | Elline |
| Amelia | Elline |
| Craig | Elline |
| Google APM | Ashley |
| Anonymous PM Big Tech | Ashley |
| Abdullah | Turki |
| Board insight | # | Who | Quotes |
| Alignment and shared understanding (words mean different things, decisions shift) | ~7 | Healthcare PM, Bryce, Abby, Google APM, Amelia, Coinbase PM, Craig | “Someone can agree to what you’re saying, but they could understand a completely different thing unless you literally draw it out.” (Healthcare PM)
“A big issue is that everybody has something different in their head.” (Bryce) |
| Prioritization is hard (urgency and importance, deciding what not to do) | 5 | Healthcare PM, Coinbase PM, Abby, Abdullah, Craig | “Whatever has the quickest deadline, honestly.” (Healthcare PM) |
| Unexpected issues and edge cases during building | 5 | Coinbase PM, Abby, Craig, healthcare PM, Abdullah | “The minute that you do a mock… you realize, like, oh, we forgot this edge case.” (Abby) |
| Meetings dominate and are draining | 4 (heavy meetings in ~7) | Amelia, Abby, Google APM, Craig | “You’re like, cool, I just was in meetings for, like, 8 hours, but I have a to-do list that’s still a mile long.” (Amelia) |
| Protected time for deep thinking is hard to come by | 4 | Amelia, Abby, Coinbase PM, healthcare PM | “A good day is I’m in advance, planned, and I have deep learning and thinking time.” (Abby) |
| AI speeds timelines, adds pressure, changes the role | 4 | Bryce, Craig, Coinbase PM, healthcare PM | “You’re expected to work on much more scope than PMs were working on before.” (Coinbase PM) |
| Need visual or sketch alignment, and remote work makes it harder | 4 | Healthcare PM, Bryce, Abby, Craig | “It’s not as easy, it’s not as tactile, it’s not as satisfying.” (Bryce, on digital whiteboards)
“I’ll draw it on paper and then give it to Claude with some examples, but I feel like it doesn’t get it right.” (Healthcare PM) |
| Unclear ownership of who owns what | 4 | Abby, Bryce, Craig, healthcare PM | “I am always asking, like, what team owns this?” (Abby) |
| Information gets scattered or lost | 3–4 | Google APM, Abby, Bryce, healthcare PM | “There are so many different teams involved… information can get lost.” (Google APM) |
| Context switching | 3 explicit, plus Abby | Healthcare PM, Coinbase PM, Amelia | “While I’m waiting for that (prompt), I’ll start working on another thing, and then it turns into too much task switching.” (Coinbase PM, on waiting for AI) |
| How many PMs? | ~2.1 million product managers worldwide. A 2025 analysis using LinkedIn’s global database counted about 2.1M people in product management roles. (Chacon’s Newsletter). |
| What gets spent on PM tools? | A reasonable estimate for the global product management software market is about $8–10B per year. Dataintelo estimates $8.4B in 2025, while another 2026 market estimate puts it at $10.09B in 2026. (Dataintelo) |
| TAM | ~2.1M potential PM users and roughly $8–10B in annual product-management software spending globally. |
TAM – Product Managers: There are approximately 2–2.6 million product managers globally, based on LinkedIn-derived estimates. Current dedicated PM tools show significant willingness to pay: Jira Product Discovery costs 10–25 per creator/month, Productboard 19–59 per maker/month, and Aha! Roadmaps starts at $59 per user/month. This implies a direct PM-seat software TAM of roughly 0.6–1.8B per year, depending on price. As a cross-check, industry research estimates the broader global product-management software market at roughly $8–10B annually, although that larger figure includes cross-functional users and broader product-management tooling.
Sources :
Product Focus: Product Managers Across the World Product Focus
Victor Chacon: Product Managers Around the World Report Victor Chacon / Substack
Atlassian: Jira Product Discovery Pricing Atlassian
Productboard: Pricing Productboard
Aha!: Roadmaps Pricing Aha!
Dataintelo: Global Product Management Software Market Dataintelo
Maia Research / MarketResearch.com: Global Product Management Software Market MarketResearch.com
Cold and Round 2 Interviews Comparison
One thing we noticed between the Round 1 and Round 2 interviews is that we felt much more confident and comfortable interviewing, simply from getting more practice. We had a better idea of how to avoid leading questions and how to let interviewees fill silences themselves. We also found that by opening with broad questions (open questions!!) we allowed for our interviewees to tell us their story from their perspective, just like this week’s reading recommends. From there, we could dig into specific pain points as they surfaced.
