AI analysis
AI that fits what you record,
built in, not bolted on.
A generic summary treats a Reel, a sales call, and a lecture the same way. Pepys doesn’t. Every transcript can be read through a framework shaped for what it actually is, with a layout to match. Six of them, all live today.
Six frameworks. One upload.
Pick the lens that matches your recording, or let the default catch it. Each one is a real analysis option in the tool, with its own purpose-built layout.
- Live
Short-form video
Hook, CTA & retention structure for TikToks / Reels / Shorts.
- Live
General
TL;DR, key points & a title – for anything.
- Live
Podcast / long-form
Show notes, key topics, pull-quotes & guests.
- Live
Meeting / sales call
Decisions, action items, next steps & open questions.
- Live
Lecture / study notes
Key concepts, an outline, takeaways & practice questions.
- Live
Interview
Themes, notable quotes & a Q&A breakdown.
Short-form video
Hook, CTA & retention structure for TikToks / Reels / Shorts.
Creators live and die by the hook. This framework names your content type, pulls the exact opening line, and explains why it stops the scroll, then maps the retention beats from tension to payoff. You also get the core message, the on-screen CTA, topic tags, and ready hashtags, all read straight from what you actually said.
The hook
“We launched with everything... and ninety-five percent of our active users only ever touched one thing.”
Core message
Subtraction is underrated: when the data showed almost everyone used only the weekly meal planner, cutting three quarters of the app roughly quadrupled retention – and later killing the free tier tripled revenue. Trust what users do, not what you hoped they'd do.
Retention structure
- 1
Confession hook: launched with a dozen features, but ~95% of users only used one of them
- 2
Tension: eight months and most of the runway spent building things almost nobody opened
- 3
Turn: cut three quarters of the app despite team pushback – 'subtraction is underrated'
- 4
Proof: retention roughly quadrupled the moment the app got smaller
- 5
Escalation: killed the free tier – signups fell ~30% but revenue tripled
- 6
Payoff line: 'data beats ego' – find the one feature your best users can't live without and delete the rest
Topics
Suggested hashtags
General
TL;DR, key points & a title – for anything.
The default for anything you upload. It gives you a clean title, a TL;DR you can paste into a doc, and the handful of key points that carry the whole recording, so a long file becomes something you can skim in seconds.
Cutting 75% of the Product Made It Better
Founder Maya Chen describes turning a struggling, feature-stuffed meal-planning app around by doing less. When the usage data showed 95% of active users only touched the weekly meal planner, she cut three quarters of the app, which roughly quadrupled retention. She also killed the free tier: signups dropped about 30% but revenue tripled. Her throughline is 'data beats ego' – trust what users actually do over the story you want to tell.
Key points
- The app launched with a dozen features, but the usage data showed ~95% of active users only ever used the weekly meal planner.
- Maya cut three quarters of the app to keep the one feature users loved; retention roughly quadrupled afterward.
- Killing the free tier dropped signups ~30% but tripled revenue, since the people who stayed actually valued the product enough to pay.
- Her core lesson, repeated throughout: 'data beats ego' – and 'subtraction is underrated.'
- Her advice to founders: find the one feature your best users can't live without, and have the nerve to delete the rest.
Podcast / long-form
Show notes, key topics, pull-quotes & guests.
Built for long-form episodes. It writes the summary, lists who is on the mic, and surfaces the key topics, the pull-quotes worth clipping, and a show-notes outline, so the post-production writing is mostly done before you open your editor.
Maya Chen on Why Subtraction Beats Shipping More
Founder Maya Chen explains how cutting three quarters of her meal-planning app and killing its free tier made the business healthier, arguing that 'data beats ego' should guide every product decision.
Guests
Key topics
Pull-quotes
- “About ninety-five percent of our active users only ever touched one thing: the weekly meal planner.”
- “Subtraction is underrated. Nobody gives you a medal for deleting eight features, even when that's the braver, smarter move.”
- “We had a third fewer signups and three times the money, and a much healthier business underneath it.”
- “Data beats ego. Every time I trusted the numbers over the story I wanted to tell myself, the company got healthier.”
Show notes
- The launch: a dozen features (recipes, pantry tracker, grocery lists, macro counting, a social feed) that looked impressive in the demo
- The humbling data: ~95% of active users only ever used the weekly meal planner, after eight months and most of the runway
- The cut: removing three quarters of the app despite team pushback, because 'the product got better the moment it got smaller'
- The result: retention roughly quadrupled once users were no longer lost in features they never asked for
- The pricing call: dropping the free tier cost ~30% of signups but tripled revenue by keeping only users who valued the product
- The takeaway: find the one feature your best users can't live without, charge for the value you deliver, and let data beat ego
Meeting / sales call
Decisions, action items, next steps & open questions.
Made for calls where the follow-through is the point. It separates the decisions that were made from the action items, each with an owner, then lays out next steps and the open questions still hanging, so nobody has to rewatch the recording to remember who owns what.
Product Strategy Review: Scope Cut & Pricing Change
A product-strategy discussion in which Maya Chen walks through two decisions: cutting three quarters of the meal-planning app down to the weekly meal planner after usage data showed ~95% of active users only used that feature, and removing the free tier. The cut roughly quadrupled retention; dropping the free tier cut signups ~30% but tripled revenue. The guiding principle is 'data beats ego.'
Participants
Decisions
- Cut three quarters of the app and keep only the weekly meal planner – the one feature ~95% of active users actually used.
- Remove the free tier and charge for the product, accepting fewer signups in exchange for users who value it.
- Stop optimizing for the raw signup number and judge growth by retention and revenue instead.
Action items
- Decommission the cut features (pantry tracker, grocery lists, macro counting, social feed) and focus the app on the weekly meal plannerTeam
- Sunset the free tier and move new users to a paid planMaya
- Track retention and revenue after both changes rather than top-of-funnel signupsMaya
Next steps
- Double down on the weekly meal planner now that retention has roughly quadrupled.
- Monitor revenue, which tripled after the free-tier change, against the ~30% drop in signups.
- Use 'find the one feature your best users can't live without' as the filter for any future feature work.
Open questions
- Is there a paid acquisition path that replaces the ~30% of signups lost when the free tier went away?
- Are any of the cut features worth revisiting later, or is keeping the product small the durable advantage?
Lecture / study notes
Key concepts, an outline, takeaways & practice questions.
Turns a recorded class into something you can study from. It defines the key concepts in plain terms, lays out the lecture as an outline, distills the takeaways, and writes practice questions, so revision starts from real notes instead of a wall of text.
Startup Lessons: Subtraction, Retention, and Pricing for Value
Using founder Maya Chen's account as the case study, this lesson examines how doing less can make a product stronger. It works through four ideas – feature creep, the retention curve, subtraction as strategy, and willingness to pay – and how she used usage data to override her own instincts, with 'data beats ego' as the organizing principle.
Key concepts
- Feature creep
- Launching with a dozen features (recipes, a pantry tracker, grocery lists, macro counting, a social feed) that looked impressive but left ~95% of active users touching only one of them, the weekly meal planner.
- Retention curve
- The rate at which users keep coming back. Once the app was cut down to the single feature people came for, retention roughly quadrupled because users were no longer lost in a menu of features they never asked for.
- Subtraction
- Treating deletion as a strategy, not a failure. Maya cut three quarters of the app despite team pushback – 'the product got better the moment it got smaller' – and argues subtraction is undervalued because founders are praised for shipping, not removing.
- Willingness to pay
- Charging for value to filter for real users. Removing the free tier dropped signups ~30% but tripled revenue, because the people who stayed valued the product enough to pay – a signup that never pays or sticks is noise, not growth.
Outline
- The setup: a meal-planning app launched with a dozen features that demoed well
- The data: ~95% of active users only ever used the weekly meal planner
- The cut: removing three quarters of the app despite the work and the pushback
- The result: retention roughly quadrupled after the product got smaller
- The pricing turn: killing the free tier cost ~30% of signups but tripled revenue
- The principle: 'data beats ego' – look at what users do, not what you hoped they'd do
Takeaways
- Usage data, not feature count, tells you what your product really is – here, ~95% of use was a single feature.
- Subtraction can be the braver, smarter move: cutting three quarters of the app roughly quadrupled retention.
- Pricing for value beats chasing signups: -30% signups but 3x revenue produced a healthier business.
- Find the one feature your best users can't live without, and have the nerve to delete the rest.
Study questions
- Why did cutting three quarters of the app improve retention instead of hurting it? Reference what the usage data revealed.
- How can dropping signups ~30% while tripling revenue still count as a healthier business? Explain in terms of willingness to pay.
- What does Maya mean by 'data beats ego,' and where in her decisions does that principle show up?
Interview
Themes, notable quotes & a Q&A breakdown.
For conversations you need to quote accurately. It pulls the recurring themes, lifts the notable quotes verbatim, and reorganizes the talk into a clean question-and-answer breakdown, so finding the line you remember takes a glance, not a scrub.
Maya Chen: The Discipline of Deleting Your Own Work
In this interview, founder Maya Chen unpacks two counterintuitive decisions behind her meal-planning app's turnaround: cutting three quarters of the product down to the one feature ~95% of users actually used, and killing the free tier. The cut roughly quadrupled retention; ending the free tier cost ~30% of signups but tripled revenue. Her recurring theme is that data should override ego.
Themes
Notable quotes
- “About ninety-five percent of our active users only ever touched one thing: the weekly meal planner.”
- “Subtraction is underrated. The product got better the moment it got smaller.”
- “Data beats ego. Every time I trusted the numbers over the story I wanted to tell myself, the company got healthier.”
Q&A
You shipped a dozen features and then deleted most of them – what happened?
The app launched with everything (recipes, a pantry tracker, grocery lists, macro counting, a social feed), but the usage data showed about 95% of active users only ever touched the weekly meal planner, so Maya cut three quarters of the app to keep the one feature people loved.
Cutting three quarters of the product is drastic – did the team push back, and was it worth it?
The team did push back because it feels like throwing away work, but Maya frames subtraction as underrated and braver than shipping more. The payoff was measurable: retention roughly quadrupled once the app was just the feature people came for.
You also killed the free tier, which runs against most growth advice. How did that play out?
Signups fell about 30% the week the free tier dropped, which was frightening, but the users who stayed valued the product enough to pay and revenue tripled – a third fewer signups, three times the money, and a healthier business.
If a founder takes one thing from this, what is it?
'Data beats ego.' Look at what people actually do rather than what you hoped they'd do: cut bravely, charge for the value you deliver, and let the data tell you who your real product is for.
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