Notorious: The Surprising Patterns Behind Viral AI Products (Yaakov Carno)

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I came across the below post in one of my favorite newsletters: Growth Unhinged by my friend Kyle Poyar that explores the hidden playbooks behind the fastest-growing startups. Below (and originally here) is one of the best blog posts I’ve read this year and Kyle and Yaakov have kidly given permission to share it with the Notorious community.

There is so much love for new AI products for note taking (Granola), photo editing (PhotoRoom, Aftershoot) and even app building (Replit, Bolt). What’s been fascinating is seeing new 🔥 UX patterns emerge. These products are reaching millions of users and tens of millions in ARR in a matter of weeks. Repeat contributor Yaakov Carno — founder of Valubyl and author of the Product Led Growers newsletter — unpacks the subtle UX choices that are leading to breakout growth.

AI products are shattering growth records, with some hitting $100M ARR faster than any software in history.

Just look at Bolt—within two months, the product reportedly skyrocketed to $20M ARR with over 2 million users. Its secret? Not just powerful AI, but a ridiculously smooth, intuitive UX that makes complex development workflows feel effortless.

Bolt isn’t an isolated instance; I’ve noticed similar hockey-stick growth at companies like Cursor, Replit, Lovable and PhotoRoom.

Meanwhile, many AI products end up as a flash in the pan. They attract AI ‘tourists’—users who sign up, get confused, and churn almost instantly. Why? Because they can’t figure out how to use it, don’t trust its decisions, or feel like they’re wrestling with AI rather than collaborating with it.

The difference between AI-native products that explode in growth and those that fade away often comes down to one thing: user experience.

Unlike traditional software, AI-driven products are dynamic and unpredictable. They generate unique outputs, adapt to user input, and, when poorly designed, can feel frustrating, mysterious, or outright unreliable.

The best AI-native products don’t just deliver powerful automation. They guide users through a seamless, intuitive, and trustworthy experience—one where AI feels like an assistant rather than a guessing game.

I’ll break down five key UX challenges in AI-native products and how the best companies are solving them.

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Challenge 1: AI feels like a black box

🧠 "AI feels like magic, but that makes it hard to trust."

Users hesitate to rely on AI when they don’t understand how it works. If an AI system produces results without explanation, people second-guess the accuracy. This is especially problematic in industries where transparency matters—think finance, healthcare, or developer automation.

How companies are solving this

• Bolt breaks down the AI process step-by-step in real time, so users see exactly how their code is being generated or automated.

• Cursor doesn’t just “fix” your code—it explains why it made each suggestion, reinforcing trust.

• PhotoRoom adds explanations behind AI edits, helping users understand the “why” behind its decisions.

Pro-tips

✅ Show step-by-step visibility into AI processes.

✅ Let users ask, “Why did AI do that?”

✅ Use visual explanations to build trust.

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Challenge 2: AI is only as good as the input — but most users don’t know what to say

📝 "Users don’t need better AI—they need better ways to talk to it."

AI is only as effective as the prompts it receives. The problem? Most users aren’t prompt engineers—they struggle to phrase requests in a way that gets useful results. Bad input = bad output = frustration.

How companies are solving this

• Bolt & Replit make it easy for users to refine prompts with one-click enhancements, helping users improve their input before execution and get better results.

• PhotoRoom introduces three AI editing paths:

  • Assisted mode: Guides users step-by-step through structured editing.

  • Image mode: Suggests similar images to spark inspiration.

  • Manual mode: Gives advanced users full control over edits.

Pro-tips

✅ Offer pre-built templates to guide users.

✅ Provide multiple interaction modes (guided, manual, hybrid).

✅ Let AI suggest better inputs before executing an action.

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Challenge 3: AI can feel passive and one-dimensional

💡 "A great AI assistant should work with you, not just for you."

Many AI tools feel transactional—you give an input, it spits out an answer. No sense of collaboration or iteration. The best AI experiences feel interactive.

How companies are solving this

• Replit uses a dual-mode AI assistant: agent mode (automates full builds) and assistant mode (helps with smaller refinements).

• Cursor combines AI chat with execution, allowing users to switch between exploratory conversation and direct AI-powered coding assistance.

• Fathom’s Ask Fathom feature turns AI meeting summaries into an interactive experience, letting users engage with transcript results instead of just receiving static output.

Pro-tips

✅ Design AI tools to be interactive, not just output-driven.

✅ Provide different modes for different types of collaboration.

✅ Let users refine and iterate on AI results easily.

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Challenge 4: Users need to see what will happen before they can commit

🤔 "People don’t trust what they can’t test."

Users hesitate to use AI features if they can’t predict the outcome. The fear of irreversible actions makes them cautious, slowing adoption.

How companies are solving this

• Bolt uses predefined AI prompts that allow users to test it before committing — even before signing up.

• Replit adds confirmation & rollback checkpoints so users can preview AI-generated code before executing it, reducing risk and fear.

• Fathom provides interactive onboarding, where users can test AI insights in a sandbox environment (a two minute test call) before having the recording bot join them in real meetings.

Pro-tips

✅ Allow users to test AI features before full commitment.

✅ Provide preview or undo options before executing AI changes.

✅ Offer exploratory onboarding experiences to build trust.

Thanks for reading Kyle Poyar’s Growth Unhinged. Please support my work: subscribe, like & share this post!

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Challenge 5: AI can feel disruptive

⚙️ "AI should weave into the workflow, not interrupt it."

Poorly implemented AI feels like an extra step rather than an enhancement. AI should reduce friction, not create it.

How companies are solving this

• Cursor lets users accept/reject AI suggestions instantly for a seamless workflow.

• Granola seamlessly blends your rough notes with a comprehensive, contextual summary, allowing you to capture loose thoughts effortlessly - without ever losing focus on the call.

• Grammarly adapts to each scenario, offering context-aware edits and replies - eliminating the need for repetitive “Write me a reply that…” prompts.

• Bolt allows users to seamlessly switch between AI-generated code and a live preview.

Pro-tips

✅ Provide simple accept/reject mechanisms for AI suggestions.

✅ Design seamless transitions between AI interactions.

✅ Prioritize the user’s context to avoid workflow disruptions.

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Designing AI that works for people

AI isn’t the differentiator anymore—great UX is. If you want your AI product to succeed, make sure it’s clear, trustworthy, and seamless—or watch users disappear.

The patterns we’ve explored—transparency, guided input, interactivity, predictability, and seamless integration—are key to creating AI experiences that drive real adoption and retention.

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The Notorious community can use this link to get 15% off their order of HBS Professor and Flybridge VC Founer Jeff Bussgang’s new book on building AI startups (discount applied at checkout): Get The Experimentation Machine

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Thanks for reading. By way of background, I am an early-stage investor at Wing and a former founder. Please reach out to me on X @zacharydewitt or at zach@wing.vc. Some of the early-stage PLG + AI companies that I have the privilege to work with and learn from are: AirOps, Copy.ai, Deepgram, Hireguide, Slang.ai, Tango, Tome and Workmate.

Operating Benchmarks (from PLG Startups):

I will continue to update these metrics and add new metrics. Let me know what metrics you want me to add (zach@wing.vc)

Organic Traffic (as % of all website traffic):

• Great: 70%

• Good: 50%

Conversion rate (website → free user):

• Great: 10%

• Good: 5%

Activation rate (free user → activated user):

• Great: 50%

• Good: 30%

Paid conversion rate (free user → paid user):

• Great: 10%

• Good: 5%

Enterprise conversion rate (free user → enterprise plan):

• Great: 4%

• Good: 2%

3-month user retention (% of all users still using product after 3 months):

• Great: 30%

• Good: 15%

Conversion from waitlist to free user:

• <1 month on waitlist: ~50%

• >3 months on waitlist: 20%

For more detail on acqusition rates by channel (Organic, SEM, Social etc), please refer to this prior Notorious episode.

Financial Benchmarks (from PLG Public Companies):

Financial data as of previous business day market close.

Best-in-Class Benchmarking:

15 Highest EV/ NTM Revenue Multiples:

15 Biggest Stock Gainers (1 month):

Complete Dataset (click to zoom):

Note: TTM = Trailing Twelve Months; NTM = Next Twelve Months. Rule of 40 = TTM Revenue Growth % + FCF Margin %. GM-Adjusted CAC Payback = Change in Quarterly Revenue / (Gross Margin % * Prior Quarter Sales & Marketing Expense) * 12. Recent IPOs will have temporary “N/A”s as Wall Street Research has to wait to initiate converge.

Recent PLG + AI Financings:

Seed:

• Aomni, an AI agent platform that helps sales teams conduct deep research on potential customers, has raised $4M. The round was led by Decibel Partners, with participation from Sancus Ventures and Ride Home Fund.

• CO/AI, a community platform designed to help discover and share how to use AI, has raised $1.8M. The round was led by The Critical Co, Movi Partners and Sequoia Capital, with participation from Gaingels.

• CTGT, an enterprise AI risk management and performance platform that actively monitors and audits client’s custom models, has raised $7.2M. The round was led by Gradient Ventures, with participation from General Catalyst, Liquid 2 Ventures, Y Combinator and Deepwater Asset Management.

• Henry AI, an AI-driven deal assistant designed for commercial real estate professionals, has raised $4.3M. The round was led by 1Sharpe Ventures and Susa Ventures, with participation from Pioneer Fund, RXR ARDEN Digital Ventures, Singularity Capital, Unwritten Capital, Coalition Operators, Orange Collective and StoryHouse Ventures.

• Lingo.dev, an AI-powered localization engine that provides the infrastructure to help developers go global, has raised $4.2M. The round was led by Initialized Capital Management, with participation from Y Combinator.

• OpenInfer, a startup building inference solutions that enable developers to run AI models efficiently on any hardware, has raised $8M. The round was funded by Brave Capital, Cota Capital, Essence Venture Capital, Operator Stack and StemAI.

• Pulse, a startup specializing in unstructured data preparation for machine learning models, has raised $3.9M. The round was led by Nat Friedman, with participation from Olive Tree Capital, Sequoia Capital, Liquid 2 Ventures, Soma Capital and Y Combinator.

• Safe Intelligence, a startup that offers deep validation of machine learning models, has raised $5.17M. The round was led by Amadeus Capital Partners, with participation from VSquared Ventures and OTB Ventures.

• Sawmills, a telemetry data management platform that allows companies to automate the management of data that flows from software applications and services to their observability tools, has raised $10M. The round was led by Team8, with participation from Mayfield Fund and Alumni Ventures.

• Singulr AI, an enterprise AI governance and security platform that helps streamline and secure enterprise AI use at scale, has raised $10M at a $35M valuation. The round was led by Dell Technologies Capital.

• Thread, an AI service desk designed for managed service providers, has raised $7.25M. The round was led by Integr8d Capital.

• Valid., an AI-enabled ad agency designed to unlock consumer and product insights, has raised $5.5M. The round was led by Canaan Partners, with participation from J Ventures and Neo.

• WilsonAI, an AI-powered assistant for in-house legal operations, has raised $1.7M. The round was led by Nomad Ventures, with participation from Entrepreneur First, Autopilot Ventures and Transpose Platform Management.

Series A:

• ClustroAI, an edge AI technology that enables local device AI processing without relying on cloud computing, has raised $12M. The round was led by Forum Ventures, with participation from Nvidia, Metaverse Group and metablast.

• Guidde, an AI-powered video documentation company focused on creating software training videos, has raised $26.6M. The round was led by Qualcomm Ventures and Norwest Venture Partners, with participation from Entrée Capital, Honey Stone VC, Tiferes Ventures and Inkberry Ventures.

• OpenEvidence, a generative AI chatbot exclusively for doctors, has raised $75M at a $1B valuation. The round was led by Sequoia Capital.

• Patlytics, an AI-enabled patent analytics platform designed to help corporations, IP professionals and law firms streamline their patent workflows, has raised $14M. The round was led by Next47, with participation from Gradient Ventures, 8VC, Alumni Ventures, Liquid 2 Ventures and Myriad Venture Partners.

• SmartSuite, a next-generation work management platform that enables teams to manage any business process or project, has raised $38M. The round was led by Canapi Ventures, with participation from Sorenson Capital and High Alpha.

Series B:

• Mercor, an AI-powered hiring platform designed to streamline the hiring process for both candidates and companies, has raised $100M at a $2B valuation. The round was led by Felicis, with participation from General Catalyst, Benchmark Capital Holdings, Menlo Ventures, Emergence and DST Global.

• Sanas, a real-time accent translation startup that helps non-native speakers speak more clearly, has raised $65M at a $500M valuation. The round was led by Quadrille Capital and Teleperformance, with participation from Insight Partners, Quiet Capital and DN Capital.

• Together AI, a public cloud optimized to run AI models for developers, has raised $305M at a $3.3B valuation. The round was led by Prosperity7 Ventures and General Catalyst, with participation from Nvidia, Salesforce, DAMAC Group, SE Ventures, Coatue Management, March Capital, Emergence, Greycroft, Cadenza Capital, Lux Capital, Long Journey Ventures, Definition, Kleiner Perkins, Brave Capital, SK Telecom and SaaS Ventures.

Series C:

• Arize, a unified AI observability and LLM evaluation platform that helps teams develop and maintain more successful AI, has raised $70M. The round was led by Adams Street Partners, with participation from M12, Datadog, PagerDuty, Battery Ventures, Archerman Capital, TCV, Foundation Capital, Swift Ventures, Industry Ventures, SineWave Ventures and OMERS Ventures.

• Baseten, an AI startup that’s focused on high-performance inference for large language models and other AI applications, has raised $75M. The round was led by IVP and Spark Capital, with participation from South Park Commons, Greylock, Conviction Partners and 01 Advisors.

• Hightouch, a data and AI platform for marketing and personalization, has raised $80M at a $1.2B valuation. The round was led by Sapphire Ventures, with participation from Bain Capital Ventures, ICONIQ Growth, New Ventures Capital, Amplify Ventures, NewView Capital and Y Combinator.

• Luminance, an AI assistant for attorneys that automates contract preparation and negotiation, has raised $75M at a $385M valuation. The round was led by Point72 Ventures, with participation from National Grid Partners, Forestay Capital, RPS Ventures, Slaughter and May, March Capital and Schroders Capital.

Series D:

• Abridge, a generative AI platform for clinical conversations, has raised $250M at a $2.75B valuation. The round was led by IVP and Elad Gil, with participation from CVS Health Ventures, NVentures, California Healthcare Foundation, CapitalG, Atria Ventures, SV Angel, K. Ventures, Redpoint Ventures, Lightspeed Venture Partners, Bessemer Venture Partners and Spark Capital.

• Lambda, a cloud computing platform designed for large-scale AI training and inference, has raised $480M at a $2.5B valuation. The round was led by Andra Capital and SGW, with participation from Nvidia, Pegatron, Super Micro Computer, Wistron, Wiwynn, Crescent Cove Advisors, Fortified Ventures, Helios Ventures, AJI Capital, Pureun Investment, US Innovative Technology Fund, G Squared, Bossa Invest, Principal Venture Partners, Launchbay Capital, Fincadia Advisors, In-Q-Tel, 1517 Fund, ARK Investment Management and KHK & Partners.