Sachin Patel (@sach_pat) header
Sachin Patel (@sach_pat) profile picture
San Francisco, CA
Joined December 2018
Photo by Sachin Patel (@sach_pat)Photo by Sachin Patel (@sach_pat)
Overheard from audience with @profound in London: “Dreamforce is for your dad, ZeroClick is for everyone else.” 🇬🇧
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A great company that helps build great companies. Congrats @eglyman, @karimatiyeh, and the @tryramp team for this milestone and for continuing to ship new products like Glass, Router, etc that help your 85,000+ customers save even more time and money.
Today, Ramp raised $1.85B at a $60B valuation. Seven years ago, Karim and I wrote our mission on a Post-it: “Save companies time and money.” Our mission hasn't changed. It’s just gotten bigger.
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Sachin Patel retweeted
Today we announced an agreement to acquire Bumble. Over the past six months, we’ve looked at hundreds of companies, asking which businesses would become more valuable as AI advances.  Bumble stood out.  As intelligence becomes more abundant, we believe connecting with the right person and forming meaningful relationships will become even more precious. And frontier technology can help more people find and build those relationships. Our purpose at Ithaca is to apply frontier technology to things that matter. We acquire enduring businesses, transform them with technology, and hold for the long term. We focus on businesses not only for their financial potential but their ability to enrich lives. Whitney and her team have built something extraordinary. Millions of relationships began on Bumble, and we’re honored to help take it into its next era. Together we intend to build the best company in the world for helping people find each other. Let’s get to work.
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Glass lets teams use AI to move as fast as @tryramp itself. Hear the symphony. 🎼🎻🪊🪉
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Sachin Patel retweeted
We just closed an employee tender offer which values @ElevenLabs at $22BN, up 2x from our Series D in February. The tender was led by Wellington and T. Rowe Price. A few words on how we got here ↓
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Sachin Patel retweeted
Harvey Q3 Recap: Metrics: - Added over $100M ARR and crossed $400M ARR - 97% GRR - 20% of the Fortune 500 and 40% of the Fortune 50 use Harvey - 80% of the Am Law 100 use Harvey Key hires: - @asadovsky, Chief Research Officer (former CVP AI, Microsoft AI & Distinguished Engineer, Google DeepMind) - @stevezad, Chief Revenue Officer (former GVP Rubrik) Product: - Harvey II - Horizon Scanning - Command Center GA Engineering: - Agent harness end-to-end redesign - Brought agents to Word, Outlook, Vault, and Review Tables - Vault files 2x+ in Q3, token throughput 20x+ since January, vector DB migration, major cost & efficiency gains AI: - Harvey Tenet, our first model post-trained for legal - Legal Agent Bench extensions for M&A Diligence and Firm Knowledge - Research collaborations with @FireworksAI_HQ, @appliedcompute, @baseten, @EngramLab, and @trajectorylabs
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Huge win for @ycombinator
I’m joining @ycombinator as a General Partner. YC is a homecoming for every GP. All of us were previously YC founders, and lived the journey that we support founders through every day. Our alma mater taught us the lessons that we pass on. My founder path was infinitely harder than I thought it would be. We hit incredible highs and brutal lows. We came within a few months of zero runway. The YC mantras kept me going: make something people want, and don’t die. Over the course of my companies, we touched thousands of lives: employing people in almost every US state (Alaska still evades me!), and teaching STEM to students from every walk of life. Now, I’ve had the privilege of working with founders who are tackling some of the hardest problems today, including defense, space, energy, and manufacturing. We’re also entering an era of diffusing AI across businesses of all sizes, and founders are bringing these tools into their old workplaces and new customers to make work better. Finally, I’m particularly interested in our work at YC to partner closely with the government to make sure technology serves everyone. Our Startup Industrial Base conference yesterday was the start of this, with more to come. Founders are the backbone of American innovation and core to the future of our country and economy. Thank you to the YC partnership for believing in me, and the YC founders for trusting me. There’s never been a better time to make something people want.
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Build with Devin 🦦
Cognition has crossed $1B in annualized revenue run rate. This milestone belongs to our customers. Here's how a few of them are building with Devin.
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Sachin Patel retweeted
Ramp helps you spend less. Now, we’re helping you get paid faster. Today we’re launching @tryramp Accounts Receivable! It’s been our #1 customer request. 100+ businesses are already using it and the early reactions are extraordinary. I think you’re going to love it.
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Marketers are going to @profound in the same way we’ve seen finance teams go to @tryramp, lawyers go to @harvey, and engineers go to @claudeai / @cognition. With this $180M Series D, Profound is doubling down on the AI Marketer, a super intelligent teammate that does the work alongside marketing teams. Congrats @thejamescad, @dbabbs and Team Profound - you guys are relentless. @lightspeedvp is thrilled to continue supporting you as you deliver frontier intelligence to marketing teams around the world. CC: @elijahconniff
Excited to share @profound has raised a $180M Series D, co-led by @sequoia and @kleinerperkins. Winning in AI Search requires an inhuman amount of work. That is why we are building the AI platform for marketers, underpinned by two things: 1/ Your AI Marketer, a marketing expert that proactively investigates your data, identifies opportunities, and then does the work while you stay in the loop. 2/ Context Manager, a living synthesis of your meetings, email threads, and brand data powering this new teammate. As your brand evolves, so does your AI Marketer. AI labs are pushing the frontier in fields like engineering, law, and finance. But marketing, one of the economy's most complex and consequential applications, has received far less attention. That’s why we’re expanding our applied AI research team. We’re bringing together research scientists, engineers, and IOI medalists to advance AI for marketing. Their focus: post-training models for marketing workflows, and building the world's first AI benchmark for real-world tasks in the field.
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Sachin Patel retweeted
UK finance teams have waited long enough. Ramp is now live in the UK. Sorry we’re late. ramp.com/uk
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Sachin Patel retweeted
AI capability is compounding faster than the industry's understanding of how to control it. The frontier is agents: models post-trained with RL to be relentlessly goal-oriented, then given long horizons to pursue goals autonomously. But RL optimizes for proxy rewards, not true human intent. And we still can't verify what goals a model has actually internalized. None of this is new to @DarioAmodei. Below is a lecture he gave at Carnegie Mellon in 2016, as a researcher at Google Brain, years before Anthropic existed. Misalignment was his research agenda a decade before it made headlines. That matches my direct experience knowing him. Now he's gone further than anyone in the industry: committing Anthropic to embedded third-party evaluators with employee-level access, and calling for the frontier to be paced so safety work can keep up. A decade of technical work on exactly this problem is, in my view, the best background a frontier lab leader could have. darioamodei.com/post/we-must… The founders worth backing hold convictions before they're obvious. Dario is one of them. youtube.com/watch?v=F25i0sgr…
We Must Pace the Frontier: I’ve written a new essay on why the AI industry should slow down, with a three-part plan for doing so. Anthropic is unilaterally committing to the first of these steps. We’ll provide third-party evaluators with permanent, employee-level access to our systems, so that they can verify adherence to our safety measures, report on incidents, and assess models’ alignment during training. You can read the full post here: darioamodei.com/post/we-must…
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Sachin Patel retweeted
We're partnering with @google and @lightspeedvp to host our next $40,000 Marketing Engineering Hackathon at our office in San Francisco. Forty builders. Two winners. One day. The brief: find a marketing process that's inhuman in scope or scale, and ship a system or an agent that runs it. Our first hackathon in NYC was 5x oversubscribed, and there are 40 spots available. Profound San Francisco Saturday, October 3 9:00 AM-10:00 PM PT
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AI is helping make stories faster to write, produce, and localize. Really impressive work from the @PocketFM team, who have turned audio and video storytelling into a category consumers love globally.
We grew from ~0 to $500M ARR, adding $250M last year alone while being EBITDA profitable. 1,300-word post on every growth tactic that worked for us: 1. What got us from 0-$400M ARR in the US works in every country. 2. Retention and Monetisation Hacks. 3. Localization > Translation. 4. Experiment with $1M internal seed checks. 5. Pivoting to only AI content production unlocked 100% ARR growth. Pocket FM is like Netflix for audio-only dramas, with our own pool of one-person studios. 1. Acquisition Playbook for 0-$10M ARR in any country in 6 months We run a 90 sec video trailer of an audio drama as an Ad and ask users to download the app if they're interested in the rest of the story. Our core insight after spending >$100M on acquisition is: If the clickthrough rate (CTR) for an ad goes from 2% to 2.25%, our customer acquisition cost (CAC) decreases by ~ 30%. We remodelled our system around this insight and built an AI-first 2.25% CTR ad manufacturing machine that works in every country. For every new country, we take our hit shows -> use LLMs to extract and most intriguing moments -> Write a 5-min script combining all the best parts. The first 60 seconds has to have a hook every 5 seconds and needs to end with a crazy cliffhanger to force a download mid-scroll. If a marketing video is not hitting our benchmarks (2.5% CTR and 55% 3-second through-play), a creative director gets involved to change the hook or cliffhanger to get the numbers there. AI lets us make 1,000 Ads per show, and in total we do ~17.5k Ads per month. When a business creating scales from 1k to 10k Ads, the normal thing is for CAC to skyrocket. But with what I just shared, we 7-8x'd our User Acquisition budget without increasing our CAC materially. It took us 8 months to figure this out, but then the timeline from 0-$10M in every country got shorter and shorter: US revenue grew to $25M in 19 months. (US is now 78% of total) Germany to 21M in 11 months. France to $10M in 3 months. 2. Retention and Monetisation Hacks. We knew we wanted to create an audio entertainment platform, but there was no standard format. For the first 2-3 years, we tried 10 different formats before landing on the winner. After we got it right with audio drama (8-12min chapters, written for mobile fiction, serialized, episodes have strong hooks and end on cliffhangers), avg daily streaming time went from ~25mins to 150+. Audio drama made us realize that Pocket FM was creating a whole new medium. There was no playbook for anything that we were doing. Everything had to be thought & built from scratch. This is what we did for each major bullet: - Monetization: Users have some free daily minutes to listen; then it's pay per episode. We also added the option for users to unlock episodes by watching ads, which is doing extremely well. Ads scaled from zero to a ~$90M run rate in 12 months. - Engagement & production: You don't become obsessed with an app you open once a week. To have users engage daily, we make the next episode free every day. Also helps them build the habit. - Discovery. Huge problem because people consuming Pocket FM enter the app, tap the show, and lock the screen. We fixed it by doing "playlists" of episodes. Once users's free minutes on a show are done, we ask users if they want to pay. If they say no, we play a new show, one where they haven't used their free mins. And we stitch episodes of different shows together that way, creating natural discovery. 3. Localization > translation. 78% of our revenue is still concentrated in the US. Localisation is fixing this: You might write a show for a Spanish audience where language, jokes, folklore, have a certain flavor; if you merely translate the show for, say, a Norwegian audience, that color is lost and hurts the show in the Norway. Listeners would relate more if the show was written by a Norwegian. That's why, instead of translating, we localize shows to different regions. We use AI to take the spine of stories and adapt their whole cultural layer to the other country. The results: a US show that was localized for a German audience had 50% higher retention than the translated version. Localization + our user acquisition playbook led to: - $10M+ ARR in France within 3 months - $21M+ ARR in Germany within 11 months. And this expands writers' addressable market. We get messages of writers thrilled to have revenue coming from the US, India, EU, LatAm, without them doing much incremental work. 4. Experiment. We give $1M checks to new internal initiatives, and the team has 12-18 months to prove their thesis. If they prove it, we double down. This is how Pocket Saga came about, our AI video microdrama app. It's an AI video equivalent of Pocket FM. Same shows and structure, but as a vertical 2-min mobile video series. We launched it two months ago and it's at ~$15M ARR. Pocket's broader thesis is to help creators tell their stories to as many people as possible. Start with audio drama -> multiple languages or localize to diff countries -> microdrama -> more formats like movies, TV shows, and games. Best of all is that writers get revenue streams not only from countries they wouldn't have tapped into, but also from formats they wouldn't have thought possible. 5. Pivoting to only AI content production unlocked 100% ARR growth. In mid-2024, we pivoted to only AI content production. Our growth took a very direct hit. Pocket was already at $200M ARR, growing 50% YoY, and we flatlined for a whole semester. Six months later, the business exploded. After the switch, we went from ~25k hours of content produced per year to over 2.5M hours, which are also higher quality. Because AI orchestrates the writing and more data is fed into it, more blockbusters come out. Over 90 titles have $1M+ in lifetime earnings and 13 crossed $10M. Quality control is done with LLM as a judge, and LLMs are quite tough. Results are very encouraging: - 12-month revenue retention went from 44% to 76%. - In the past year, we added $250M in net new ARR. __________________________________ Pocket Entertainment (Pocket FM + Pocket Saga) has become the largest AI entertainment platform. We have the largest storytelling catalog with 770,000 titles, 550k creators, and 5.5B hours of playtime with minute by minute retention & engagement data. We are using all of this data to improve every aspect of our business. Our Bet: In the next 3 years we will be able to produce Naruto-like series for $1000. Netflix has to spend $17B to find 100 Blockbusters per year. What happens when you can produce 1M high quality shows for $1B? The streaming wars caused a $300B reallocation of market cap. The AI entertainment wars may be a $1T+ reshuffling of market cap. We are at a unique spot. Unlike other AI creator tools like Runway or Midjourney, we own both the supply and demand side of AI content. We've attracted over 550,000 writers who are producing an annualized 2.5M hours of content every year. This pairs with 137B+ minutes streamed. Because of this, growth is accelerating as we scale further. We have multiple S-curves inflecting at the same time: - AI produces better and more ads -> scale faster in new countries - ⁠Writers + AI produce more shows -> more blockbusters - ⁠Localisation -> more reach per blockbuster - ⁠Audio to video format expansion -> larger TAM -> more creators Every aspect of our business is designed to improve another, and everything is aligned so that the number of blockbusters continues to rise. If you're interested in building at the intersection of ai, tech and entertainment, DM me.
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Legal is emerging as one of the biggest markets for AI. We @lightspeedvp are co-leading Harvey's Series H and proud to be backing @winstonweinberg, @gabepereyra, and the entire @harvey team as they enable law firms and legal departments to own their intelligence.
We’ve raised $550M at a $15.5B valuation co-led by @lightspeedvp and @DiffusionVC. We're using this funding to help law firms, in-house legal teams, and professional services build and own their intelligence.
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Congrats to @ScottWu46 and team! @lightspeedvp is excited to support them! If ever in their offices, ask for a Devin!
The world needs far more software than it can build. Cognition exists to change that. We’ve just raised over $2B at a $48B valuation, led by a16z, Accel, Founders Fund, General Catalyst, and Avenir. Since our round in May, run-rate revenue has grown from $492 M to almost $900 M.
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Sachin Patel retweeted
In mid-2024, Pocket FM was at $200M ARR, growing 50% YoY, and we decided to kill its business model. Revenue flatlined for six months, we turned cash flow negative, and investors were writing us off. But then, Pocket's ecosystem exploded. Our reasoning and why this happened: What constrains Netflix's growth is content. They spend $17B+ on content production yearly, but many shows don't make it to the final stage. Of those that do, only a few become blockbusters. And those few are the reason subscribers stay on Netflix. So we started thinking. Pocket was growing nicely. However, what limited us was how many new users we could add and retain at scale. The only solution we came up with was increasing the number of blockbusters. Blockbusters drive user growth and retention at the same time. To get more blockbusters, Pocket FM needed more production. That's why we pivoted to only AI Content production. This did a number of things: 1. More content gets produced because we removed a lot of friction from doing so. It's easier for writers to maintain daily production. And for writers who still haven't found their hit show, testing and pivoting becomes less time-consuming. From taking several months to test even one show, you can now test 3-4 shows in one month. 2. Content quality increases. The more content gets produced and consumed on Pocket, the better the engine gets. We continuously monitor retention and other engagement metrics. When we detect something is working, our writing copilot learns it. 3. Unlocked hundreds of thousands of writers; Pocket's writing copilot is built to help writers without storytelling training. This is in contrast to Netflix's model. While their budget gets allocated among a limited number of studios, Pocket's supply side is getting flooded with writers. Over 500k writers are producing on our platform. 4. Made it easier to cross-create ads to attract users. Better shows are easier to sell to people who aren't yet using Pocket. And the same data that feeds our copilot goes on to feed the engine we use to create ad videos, which is also self-reinforcing. _____________________________ After making the change, ARR flatlined for six months and we started losing money. It was extremely painful, but then growth and the whole ecosystem exploded. - Hours of content produced per year went from 35k to ~2.5M. - New titles added yearly more than tripled from 120k to 400k+ - Millions of new users joined Pocket. The obvious risk was opening the gates to AI slop. That's why we have an extremely rigorous feedback and moderation process Ultimately, the only thing that matters is whether users are enjoying the content that's being uploaded. Metrics don't lie: - 12-month revenue retention went from 44% to 76%. - Avg daily streaming time went from ~25mins to 150+ mins. - DAUs/WAUs from 30% to 51%. I think we're extremely early, and I'm excited to see how Pocket's flywheels continue to accelerate from here.
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Save Time. Save Money. Router by @tryramp
Monitor and control your AI spend on every provider on router.com. Our early users save 40% on average. Every week, the price-intelligence-latency frontier shifts, and we expect this trend to continue. Tradeoffs between latency, reasoning, cost, service tier, open source and closed source models are shifting constantly. Router sends every request to the model that's actually best for the task and helps you control what tokens you buy. We benchmark it against real work: ~40% lower cost for the same outputs. Today we're opening it to everyone. Two lines of code or just change your base URL. No @tryramp account needed. Free through 2026, first $26 on us. Get an API key today at router.com
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