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For product managers
Twelve discovery calls before standup. None on your calendar.
Validate the bet before you scope it. Totem talks to twelve target users. Tells you which feature they'd actually use, and which would be built-because-asked.
Silent betaFully free in beta
Beta cohort A, week-1 feedback
Beta tester interviews. Totem ran this conversation across 12 beta testers and synthesized what came back into the takeaway below.
Key findingsAI-synthesized from 12 beta testers
10 of 12 got to first value within 8 minutes, but the empty state confused 7 of them before they found a template. Three said they'd ship it with their team today if the share-link worked. Five want a guided first-run tour before they go solo.
- First value < 8 min
- Empty-state friction
- Share-link broken
- Wants guided tour
- Would ship today
- 40%Positive
- 40%Friction
- 20%Focus
- Responses
- 0
- Fully completed
- 0/0
- Avg. completion
- 0%
- Avg. length
- 0m
From silent-beta calls
“I used to prioritise by who-yelled-loudest in the channel. Now I prioritise by who-actually-uses-it. Different roadmap. Better one.”
— a PM, second cycle in
What product managers ask first
“But I need to be in the room for the conversation.”
For the first four conversations of a new line of inquiry, yes. For the next twelve, you don't. Totem runs the same protocol with the same probes for every participant; you read the synthesis and drill into the verbatims that disagreed. The PMs who switch describe it as "I sat through three calls to learn one thing" becoming "I read twelve in twenty minutes."
What product managers start with
The bets PMs run before they scope.
Roadmap prioritization
Roadmap prioritization
What customers would pay for next.
Concept testing
Concept testing
Reactions to a rough idea before you build.
Feature request triage
Feature request triage
Pattern across fifty parallel asks.
Why PMs pick Totem
- 01
Pre-validated bets ship faster. And land more. The team trusts the roadmap because the roadmap is grounded in what users said, not in what loudest feature-requesters yelled in the channel.
- 02
Twelve interviews per cycle. For the cost of two coffee meetings. Discovery becomes routine instead of a quarter-blocking event.
- 03
No more 'we built it because someone asked.' You'll know how many people asked, and what they'd give up to get it.
What changes
What changes for product managers.
- 01
Weekly customer contact, not quarterly
Continuous discovery, the practice popularised by Teresa Torres, recasts customer conversations as a sustained habit, not a phase before scoping.
Continuous Discovery Habits · Teresa Torres
- 02
12 interviews per cycle becomes the floor
Pattern saturation usually arrives around the twelfth conversation in a target segment. AI-moderated interviews make that ceiling the new floor.
- 03
Pre-scope, mid-scope, post-launch
The same Totem prompt-to-synthesis loop runs at three points in the build cycle: bets worth shipping, specs worth validating, friction worth catching in week one.
Common questions
What product managers ask before they try Totem.
- How do product managers validate features before scoping?
- By running discovery interviews with target users before the engineering investment. Totem hosts twelve discovery calls per cycle — same protocol, same probes, real users — and synthesizes which features users would actually use vs. which are built-because-asked. PMs walk into roadmap reviews with grounded patterns instead of feature-request sentiment.
- What's the best discovery interview tool for product teams?
- Tools split into research repositories (Dovetail, Aurelius), participant recruiters (User Interviews, dscout), and AI-moderated interview platforms. For a PM running discovery on a sprint cadence, the AI-moderated category wins on throughput. Totem is built for that loop: prompt seeds protocol, twelve target users in a cycle, synthesis fits in a Slack message.
- How many discovery interviews should a PM run per cycle?
- Continuous discovery (Teresa Torres) suggests weekly user contact at minimum. With AI-moderated interviews, twelve interviews per cycle becomes the default rather than the stretch goal — the bottleneck moves from "can I book the calls?" to "what should I ask this week?"
- How can PMs prioritize features based on user research?
- By running parallel discovery calls and synthesizing across the cohort. Totem's output ranks themes by participant count ("Tier confusion: 7 of 9"), tags them sentiment-coded, and grounds each in verbatims — so a PM can score features by who-actually-asked vs. who-yelled-loudest, and bring real receipts to the prioritization conversation.
- How does Totem help with feature validation?
- Pre-build: discovery interviews surface the bets worth scoping. Mid-build: targeted interviews validate the spec with the cohort that asked. Post-launch: structured check-ins surface adoption friction in week one, not week twelve. One platform, one prompt-to-synthesis loop, three points in the build cycle.
- How is Totem different from a customer feedback tool?
- Feedback tools (in-app surveys, Intercom-style widgets) capture the customer's bandwidth: you get a sentence on the way to checkout. Totem captures the customer's attention: a 15-minute depth interview run async on their schedule. Different output — qualitative depth across the cohort instead of fragmented one-line feedback.
Your turn
Describe the feature. Find out who's waiting for it.
One prompt. Twelve target users. The synthesis tells you whether to scope it, kill it, or sequence it after something quieter.
Drop your promptFree during the betaNo cardYour prompt, your data