AI for product managers who defend their calls

One AI agrees with how you framed it. Five will fight about it.

Deepest sends your decision to several top AI models at once and shows you exactly where they disagree. For a job that is mostly making calls under uncertainty and defending them to engineering, design, and executives, the disagreement is the stakeholder review before the stakeholder review.

200 free credits. No credit card required.

Watch three models tear apart the same prioritization

One roadmap call, three top models, three different verdicts. Where they split is what you will hear in the review.

Claude
Claude Opus 5
Generating...
OpenAI
GPT-5.6 Sol
Generating...
Gemini
Gemini 3.1 Pro
Generating...
Responses will appear here...

Simulated demo for illustration. Actual responses are more detailed and personalized.

Why one AI is not enough for product decisions

A single chatbot answers inside whatever framing you gave it. That is comfortable, and it is exactly how bad prioritization gets confident.

One model agrees with your framing

Ask a single chatbot whether your prioritization is right and it will mostly find reasons you are. Models are trained to be agreeable, and your question already contains your conclusion. Several models answering independently break the mirror: at least one usually attacks the premise, and that answer is the one worth reading twice.

Every call gets attacked eventually

Engineering will question the estimate, design will question the problem, and an executive will question the whole quarter. The only variable is whether you hear the objections before the meeting or during it. A panel of disagreeing models is the rehearsal: the arguments they raise against each other are the ones headed for your review.

You find what you went looking for

Read twenty interview transcripts hunting for validation and you will find it. That is confirmation bias, not synthesis. Three models reading the same notes independently produce three different theme lists, and the differences show you which "insights" were actually your own assumptions reflected back.

How product managers use Deepest

Three ways to combine the models, mapped to how product decisions actually get made and defended.

Compare · where the models agree and disagree

Compare: the stakeholder review before the stakeholder review

Ask once and every model answers side by side, with an automatic breakdown of where they agree and where they split. Use it on prioritization calls, metric definitions, and any decision headed for a room full of skeptics. One model would have answered inside your framing; three independent answers show you which parts of your reasoning only work because of how you asked.

Should we ship SSO before usage analytics?

GPT-5.6

Claude

Calls the tradeoff a false binary

Gemini

Compare

Two of three reject the ranking. Their reasons are your review prep.

Debate · models argue and converge

Debate: the pre-mortem that argues back

Debate makes the models argue against each other and converge over rounds. Feed it a launch plan and ask why it failed; feed it your roadmap ranking and watch which arguments survive contact. The objections that emerge are a preview of the review meeting, and the position left standing is the one worth writing into the decision doc.

Pre-mortem: this launch failed. Why?

GPT-5.6 · opening

Claude · rebuttal

GPT-5.6 · concedes

Claude · holds

Debate

Three failure modes survive two rounds. Those are your launch risks.

Synthesis · one combined best answer

Synthesis: one PRD from the strongest parts

For documents, you rarely want three versions; you want the best one. Synthesis has the models answer independently, then combines the strongest structure, cleanest language, and every edge case any of them caught into a single draft. PRDs, decision docs, and launch comms arrive already cross-pollinated instead of carrying one model's blind spots.

Draft a PRD for usage-based alerting

GPT-5.6

Claude

Gemini

Synthesis

One draft, with the edge cases each model caught folded in.

What product work looks like with a model panel

Four places product managers put Deepest to work on day one. Each prompt is copyable as written.

PRD and spec first drafts

Run the same brief past several models and each drafts independently. One model's spec looks complete until a second one lists the failure states it skipped; the disagreement is your edge-case review before engineering does it for you.

Try this prompt

Draft a one-page PRD for adding usage-based alerts to our B2B analytics product: problem statement, user stories, success metrics, explicit non-goals, and the three riskiest edge cases. Context: [paste context]

Prioritization stress-tests

Put your ranking and its reasoning in front of the panel and have the models attack it. What survives is defensible; what does not was going to fall apart in the roadmap review anyway, just later and in public.

Try this prompt

Here is next quarter ranked by priority, with my reasoning for each item. Attack the ranking: which item is misranked, what evidence is missing, and what would a skeptical head of engineering push back on first? [paste roadmap]

User research synthesis

Have several models read the same interview notes independently, then compare their theme lists. Where the readings differ is exactly where your own expectations were doing the interpreting, which is the bias a single summary hides.

Try this prompt

Here are notes from eight customer interviews. Independently: list the top three themes with supporting quotes, the single most surprising finding, and one conclusion these notes do NOT support: [paste notes]

Decision docs and stakeholder comms

The call is made; now it has to survive an executive audience. Synthesis merges the models' drafts into one tight document, and running Compare on the finished doc tells you which section a skeptical reader will hit first.

Try this prompt

Turn this decision into a one-page doc for executives: the call, the two strongest alternatives and why they lost, the risks we are accepting, and the tripwire that would make us reverse. Keep it under 400 words: [paste decision and context]

Start with 200 free credits and up to 2 models per prompt.

Confidentiality

Built for roadmaps you cannot leak

Conversations are encrypted in transit and at rest, are never used to train models, and you can export or permanently delete everything at any time. Prompts go to model providers through enterprise APIs, not consumer chatbots. Follow your company's AI policy, and strip customer names or unannounced partner details where your rules require it; the workflow works exactly the same.

Questions product managers ask

Work in a different field? Deepest works the same way for software engineers, consultants, marketers, and every other profession.

Hear the objections before the meeting

Start free with 200 credits. No credit card required.