October 2026
Building Got Fast. Discovering What to Build Didn't.
A few weeks ago, I got interested in the user research topic. Seeing how the industry changes with agents that write your code is amazing and terrifying at the same time. For the first time in history, we can deliver 10x more stuff by simply describing to an agent what we want to see. However, that doesn't mean that we have 10x'ed the understanding of what should be built.
This study aims to understand how software teams talk to their users in 2026 before shipping new products. I analyzed 560 Reddit threads and more than 11 thousand comments from product managers, researchers and founders. Here is how people tackle this problem, what actually works, and where AI stands in all of it.
Whether you are a founder, a product manager or simply a curious person, I invite you to take part in part two of the study, where we will ask respondents to share their opinions on the user research topic, analyze them, and then share the results with every single person who contributed to it. To learn more about it, see the What Comes Next section at the end of the page.
“…Claude Code ships in an afternoon. Discovery still takes two weeks.”
TL;DR. Five Things to Know
- Agents 10x'ed building new features. Teams say the time allocated to discovery shrank to make room for shipping, not the other way round.
- Finding the right people to concept-test your idea is most of the work. One specific question beats a request for a meeting.
- Meeting no-shows run from 10% to over 50%. Payment motivation, flexible booking times and a quick rebook decrease call churn.
- People tend to describe a tidier version of what they do. Ask about the last time they had a problem, then listen.
- Use AI for notes? Yes, with checks. AI interviewers? Yes, now it is possible. Try synthetic users? Absolutely not.
Finding 1
The Bottleneck Moved to Discovery
Prevalence: 21% of all threads mentioned the problem
We can agree that engineering teams went all in on AI coding this year and now they can ship far more than they used to. On the other hand, product managers say the time to understand what users need didn't grow with it. It shrank. More specs get written, fewer customers get called, and nobody is sure the work is the right work.
“Since AI went crazy, three months of discovery has asymptoted to zero.”
“…an 8 dev team handles like 8 epics per cycle instead of like 2. There is no way to get any discovery done properly in such a rush.”
“The hard part of the job was never writing the PRD. It was sitting with ambiguous customer feedback and making judgment call.”
“Code is cheap. Conviction in the wrong direction is incredibly expensive.”
What Works
- Spend the time that AI saved you on users, not on writing another pack of documents.
- Build a rough prototype in the morning and put it in front of customers the same day.
- Ask customers to describe their day-to-day pains. Listen to them and prioritize solving problems, not assumptions.
Finding 2
Finding the Right People
Prevalence: 35% of all threads mentioned the problem
Recruiting people for user research gets more comments than any other hands-on part of the work of a product manager. Interview panels work for the general public and break down for anyone specific. The places nobody warned against are slow and personal. They are in person, referrals, and your own sales and support teams.
Said it worked, as a share of comments that named the channel
- In person 99% (97 of 98)
- Sales and support teams 93% (42 of 45)
- Specialist recruiters 93% (40 of 43)
- Network and referrals 93% (99 of 107)
- Your own users 84% (109 of 129)
- Online communities 84% (185 of 221)
- LinkedIn 78% (86 of 110)
- Paid panels 71% (77 of 108)
- Cold email and calls 53% (73 of 137)
Share of recruiting comments that named a channel and said whether it worked.
Specific ask
- Email to users who opted in on a survey 9.2%
- LinkedIn to engineering managers, clear it wasn't a sale 25%
- LinkedIn DMs to the person closest to the pain 30%
Generic ask
- Generic LinkedIn messages to accountants 0%
- Pitching Reddit DMs 0.5%
- Cold email to company inboxes 1.0%
- Discovery requests to 100 Heads of a function 3.0%
- Bulk cold email from a sales database 3.5%
Outreach results people reported with their own counts, one comment per bar.
“…honestly recruitment is like 50% of the job and nobody talks about it enough.”
“On paid platforms (panels), assume everyone is a professional participant.”
“…don't ask for a meeting. Ask one specific question.”
“Difficulty recruiting interviewees is often a product signal itself if people won't spend 15 minutes talking about problem, the pain may not be meaningful enough to solve.”
What Works
- Write to the person closest to the problem, not the CEO or a shared inbox.
- Open with one specific question about how they work today. Once the pain is confirmed, only then schedule a call.
- Be open, say that you're not selling anything, and send it as a real person.
- Start with your own users. Try an in-app prompt or a line at the end of a survey.
- Book more people than you need. Twelve to get ten, or eighteen to get twelve.
Finding 3
Getting People to Show Up
Prevalence: 70 threads on logistics. 84 threads on pay.
Booking the call is only half the battle. People report losing 10-50% of all booked calls to no-shows. Pay motivates the users the most, and it ranges from a dollar for a survey to $750 for an hour with a professional. Whether to pay in cash or in your own product splits opinion.
- 50%+in a bad week of B2B calls
- About 30%when there's no incentive, or a low one
- 10 to 20%even with email and text reminders
- Under 10%with tight screeners, high incentives and flexible times, even with executives
No-show rates people reported.
- Survey, general public $1 to $3
- Unmoderated test $10
- Consumer interview $50 to $75
- Interview in the US $75 to $100+
- B2B professional $100 to $150
- Doctors and specialists $500 to $750
What people said they pay per session. Log scale.
“I’d send an email 5 minutes after the start time and offer to rebook with a calendar link. Got 50%+ to rebook that way.”
“Try having evening and weekend spots and that should improve your show rate”
“I purposely chose to go with free annual subscriptions so the users can see their feedback in the product within the year”
“Free product is not as appealing as a tangible, immediate, personal reward for the participant.”
What Works
- Treat a B2B no-show as a battle with the user's calendar, not a no. Email five minutes in with a link to rebook.
- If you are highly interested in users' feedback, offer evening and weekend slots.
- Remind people an hour before and again ten minutes before the meeting.
- Pay strangers in cash or a gift card. Product credit only suits people who already use it, and some say it biases them.
Finding 4
What People Say Isn't What They Do
Prevalence: 45% of all threads mentioned the problem
Interview craft is the second most common theme, and the warnings are consistent. People tell a clean story of how they work. Then they don't pay for the thing they said they needed. The fix isn't fewer interviews. It's asking about real moments and watching, not collecting opinions.
“Nobody was lying. They genuinely believed their description was accurate.”
“We offered to solve their stated problems for $100. They wouldn’t pay.”
“Instead, I try to stay intentionally vague at first: “Tell me about your last orders.””
“A participant might say they like a feature but when you watch the recording you notice a long pause before the answer”
What Works
- Ask about the last time the user had a problem, not what they usually do or would do.
- Start broad and let them raise the problem. If you name it first, they'll agree with you.
- When someone asks for a feature, ask what problem it would solve.
- Watch them do the task, and go back to the recording, not only the transcript.
Finding 5
Everyone Does Research, So Nobody Does
Prevalence: 25% of all threads mentioned the problem
Research teams shrank this year, and the work moved to product managers, designers and engineers. Many product managers say they spend their days on delivery and rarely talk to a customer. One founder ran four months without a PM. The feedback got better. Deciding what mattered didn't.
“Did we democratize user research, or just make nobody responsible for it?”
“…executing predefined roadmaps with almost zero direct customer connection.”
“The guy stopped me to tell me they rely on proxy data here not conversations.”
“Four people with good judgment create four good lists, not one ordered list.”
What Works
- Name one person who turns what users said into a decision.
- Send engineers the sessions where users struggle with what they built.
- When sales says the customer wants it, ask which customer, and ask to meet them.
Finding 6
AI Advances. Enter Autonomous Interviews.
We sorted every comment that took a side on AI in research. Then we left out the ones selling something, because they changed the answer.
GO: AI for Transcripts and a First Pass 352 comments
- 37% trust it (130)
- 44% only with checks (155)
- 19% don't trust it (67)
ITERATE: Autonomous Interviews 107 comments
- 18% for it (19)
- 29% mixed (31)
- 53% against it (57)
NO GO: Synthetic Users 208 comments
- 11% for it (23)
- 31% mixed (65)
- 58% against it (120)
Comments that took a side on each use of AI.
GO AI for Transcripts and a First Pass
Most people use it and like it, as long as someone checks the output against the recording. Researchers check much more than product managers do.
“…a lot of time is spent checking work, identifying and resolving errors the AI has made, even in simple calculations.”
“…make sure the agent files have very strong and strict advice about facts and assertions. Don't let the LLM improvise on anything.”
ITERATE Autonomous Interviews
Previously, it was useful in place of an unmoderated test, where a follow-up question helps. For discovery, the playing field is only forming. People say they don't follow up on the interesting part, repeat answers back, and put participants off. However, this is not the case with recent advancements in voice AI, so the potential for autonomous research opens up.
“Its like when you expect a follow-up question, but it never comes.”
“It felt impersonal and honestly I think less of the company for trying to do it.”
NO GO Synthetic Users
A review of 182 studies found synthetic participants don't stand in for people, and a second study found they matched real design preferences 53% of the time, about a coin flip.
“Synthetic users create synthetic data - don't make product decisions based on fake data.”
“If you have data enough that you are able to accurately simulate user taste, then you don’t need user interviews, but how would you know what you have is accurate?”
Product managers 164 comments
- 50% trust it (82)
- 41% only with checks (67)
- 9% don't trust it (15)
Researchers 181 comments
- 25% trust it (45)
- 47% only with checks (85)
- 28% don't trust it (51)
Comments on AI analysis that took a side: r/ProductManagement for product managers, r/UXResearch for researchers.
The Playbook
Ten Things That Work for Small Teams
The advice people gave again and again, across 2,804 pieces of it. Ranked by how many threads it came up in.
- 99 threads
Start Small
Five conversations or a rough prototype before anything gets built.
- 98 threads
Tie It to a Decision
Say up front which decision the research is for, and what it's worth to the business.
- 87 threads
Watch, Don't Only Ask
See them do the task. Compare what they say with what they do.
- 78 threads
Check the AI
Use it for transcripts and a first pass, then check every claim against the recording.
- 75 threads
Go Where the Problem Is
Niche communities, events, shops. Wherever the problem already comes up.
- 70 threads
Ask About the Last Time
Real past moments and today's workaround, never what they would do.
- 65 threads
Write It Down Right After
A fifteen minute summary after each call beats re-reading transcripts later.
- 54 threads
Bring the Team In
Engineers and stakeholders on the call or watching the clips.
- 53 threads
Pay People
Match the amount to their time and their job. Strangers want cash, not credit.
- 50 threads
Recruit From Your Product
In-app prompts, a line at the end of a survey, an email to people who just churned.
Threads where someone gave the advice, out of the 560 in the study.
What Comes Next?
This study focused on what people wrote online. In Round Two, we are going to ask them out loud.
We are now running a 15-minute voice interview in your language, whenever it suits you, with no account, to hear your thoughts on user research.
It's for founders, product managers and anyone who decides what gets built.
We will share the Round Two report with everyone who takes part once the round closes.