Notes ·
Building Got Fast. Learning What to Build Didn't.
How software teams talk to their users in 2026, in their own words. I read 560 Reddit threads and 11,543 comments from product managers, researchers and founders. Here is what’s hard, what actually works, and where AI helps.
- Threads
- 560
- Comments
- 11,543
- Communities
- 4
- January to October 2026
- 9 Months
“Cursor/Claude Code ships in an afternoon. Discovery still takes two weeks.”
- 35%of threads are about finding people to talk to. The most common practical problem.
- 63%of the praise for AI interviewers came from people selling them.
- 3×more often researchers distrust AI analysis than product managers do.
The short version
Six Things to Know in a Minute
- AI sped up building. Teams say discovery shrank to make room for it, not the other way round.
- Finding the right people is most of the work. One specific question beats a request for a meeting.
- No-shows run from 10% to over 50%. Pay, flexible times and a quick rebook move the number.
- People describe a tidier version of what they do. Ask about the last time, then watch.
- Research teams shrank and everyone now does research, so often nobody does.
- AI for notes: yes, with checks. AI interviewers: not yet. Synthetic users: no.
Finding 1
The Bottleneck Moved to Discovery
Engineering teams went all in on AI coding this year and ship far more than they used to. Product managers say the time to understand users 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.
116 threads · 21%
“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 AI saves on users, not on more documents.
- Build a rough prototype in the morning and put it in front of customers the same day.
- Ask customers what pace of change they want. Few of them want features ten times faster.
Finding 2
Finding People Is Most of the Job
Recruiting gets more comments than any other hands-on part of the work: 1,121. Panels work for the general public and break down for anyone specific. The places nobody warned against are slow and personal: in person, referrals, your own sales and support teams.
198 threads · 35%
- Online communities185 worked · 36 didn’t
- Your own users109 worked · 20 didn’t
- Network and referrals99 worked · 8 didn’t
- In person97 worked · 1 didn’t
- LinkedIn86 worked · 24 didn’t
- Paid panels77 worked · 31 didn’t
- Cold email and calls73 worked · 64 didn’t
- Sales and support teams42 worked · 3 didn’t
- Specialist recruiters40 worked · 3 didn’t
Recruiting comments that named a channel, vendors left out.
- 0% Generic LinkedIn messages to accountants
- 1% Pitching Reddit DMs
- 1% Cold email to company inboxes
- 3% Discovery requests to 100 Heads of a function
- 4% Bulk cold email from a sales database
- 9% Email to users who opted in on a survey
- 25% LinkedIn to engineering managers, clear it wasn't a sale
- 30% LinkedIn DMs to the person closest to the pain
Outreach results people reported with their own counts. Bars are to scale; the longest is 30%.
“…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. The call follows.
- Say plainly that you're not selling anything, and send it from a real person.
- Start with your own users: 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
Then Getting Them to Show Up
Booking the call is half the battle. People report losing a tenth to over half of them. Pay moves the number most, and it ranges from a dollar for a survey to $750 for an hour with a doctor. Whether to pay in cash or in your own product splits the room.
70 threads on logistics · 84 on pay
- 50%+in a bad week of B2B callsr/UXResearch · Jun 2026 ↗
- About 30%when there's no incentive, or a low oner/UXResearch · Apr 2026 ↗
- 10 to 20%even with email and text remindersr/UXResearch · Apr 2026 ↗
- Under 10%with tight screeners, high incentives and flexible times, even with executivesr/UXResearch · Jan 2026 ↗
- Survey, general public · per complete$1 to $3 r/UXResearch · Oct 2026 ↗
- Unmoderated test · 20 to 25 minutes. Testers say it's too little$10 r/UXResearch · Mar 2026 ↗
- Consumer interview · 30 minutes$50 to $75 r/UXResearch · Feb 2026 ↗
- Interview in the US · one hour, more for harder recruits$75 to $100+ r/UXResearch · Mar 2026 ↗
- B2B professional · 30 minutes$100 to $150 r/UXResearch · Feb 2026 ↗
- Doctors and specialists · one hour$500 to $750 r/UXResearch · Mar 2026 ↗
“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 clash, not a no. Email five minutes in with a link to rebook.
- Offer evening and weekend slots.
- Remind people an hour before and again ten minutes before.
- 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
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.
251 threads · 45%
“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 it happened, 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.
- Ask for something real: money, a pilot, an hour of their team's time.
- Watch them do the task, and go back to the recording, not only the transcript.
Finding 5
Everyone Does Research, So Nobody Does
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.
140 threads · 25%
“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 Helps With Notes. Not Yet With People.
I sorted every comment that took a side on AI in research. Then I left out the ones selling something, because they changed the answer.
Yes, with checks
AI for Transcripts and a First Pass
352 comments, vendors left out
- 37% trust it
- 44% only with checks
- 19% don't trust it
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.”
Not yet
AI Interviewers
107 comments, vendors left out
- 18% for it
- 29% mixed
- 53% against it
Useful in place of an unmoderated test, where a follow-up question helps. For discovery, people say they don't follow up on the interesting part, repeat answers back, and put participants off.
“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
Synthetic Users
208 comments, vendors left out
- 11% for it
- 31% mixed
- 58% against it
A preprint 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 Trust AI Analysis More Than Researchers Do
Half the product managers who took a side trust it as it is. A quarter of researchers do, and more than a quarter don’t trust it at all.
Product managers · 164 comments
- 50% trust it
- 41% only with checks
- 9% don't trust it
Researchers · 181 comments
- 25% trust it
- 47% only with checks
- 28% don't trust it
Most of the Praise Came From Vendors
- 32 of 51comments praising AI interviewers pitched a product the writer sells or works for.
- 30 of 53comments praising synthetic users did the same.
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.
Start Small
Five conversations or a rough prototype before anything gets built.
In 99 threads
Tie It to a Decision
Say up front which decision the research is for, and what it's worth to the business.
In 98 threads
Watch, Don't Only Ask
See them do the task. Compare what they say with what they do.
In 87 threads
Check the AI
Use it for transcripts and a first pass, then check every claim against the recording.
In 78 threads
Go Where the Problem Is
Niche communities, events, shops. Wherever the problem already comes up.
In 75 threads
Ask About the Last Time
Real past moments and today's workaround, never what they would do.
In 70 threads
Write It Down Right After
A fifteen minute summary after each call beats re-reading transcripts later.
In 65 threads
Bring the Team In
Engineers and stakeholders on the call or watching the clips.
In 54 threads
Pay People
Match the amount to their time and their job. Strangers want cash, not credit.
In 53 threads
Recruit From Your Product
In-app prompts, a line at the end of a survey, an email to people who just churned.
In 50 threads
Method
How I Did It, and What It Can’t Tell You
I read every post published between 1 January and 4 October 2026 in r/ProductManagement, r/UXResearch, r/userexperience and r/startups: 27,808 posts.
A language model screened the 1,531 whose title or text mentioned users, customers, research or interviews, and kept 560 that are about learning from users. Then it coded every comment of 60 characters or more against 15 themes, the stance it takes on AI, and any advice or numbers it gives.
Comments that pitch a product the writer sells or works for were flagged and left out of every stance and recruiting count: 208 of them.
Percentages are shares of the 560 threads that touch a theme, or shares of the comments that take a side. Every quote was checked word for word against the original and links to it.
Reddit isn't everyone. It leans to people who want to vent or ask for help, and to researchers who are wary of AI. Read the numbers as what these communities said, not as a survey of the industry.
| Community | Threads |
|---|---|
| r/UXResearch | 254 |
| r/ProductManagement | 227 |
| r/startups | 62 |
| r/userexperience | 17 |
Get in touch
Working on This at Your Company?
I’m spending my days on exactly this problem: how teams find the right people, get them on a call, and turn what they say into a decision. I would like to hear how you handle it, what you have tried and what still doesn’t work.