Recall.ai

$5M ARR, and you’re asking if you have product-market fit? You don’t. PMF isn’t a number. It’s a feeling. And when you have it, it’s impossible to miss: 1/ People you’ve never met are talking about you 2/ Prospects chase you down, not the other way around 3/ Downtime keeps you awake at night. Not for your team, but because your customers can’t operate without you When Recall.ai hit PMF, the moment was clear. A CTO called at midnight, furious because they thought our API went down for 2 minutes (it didn’t). That’s when I knew we had become mission-critical. So stop chasing a number. Start chasing signals: Do your customers need you—or could they live without you? What was your unmistakable sign of PMF?

Raised $10M without finishing the pitch deck. Here’s why: Investors didn’t care about our slides. They cared about our traction. When we raised our Series A last year, we didn’t spend hours pitching the market size or TAM. Instead, we focused on proving we were the 10x bet. What we showed them: 1/ Growth: $2M+ ARR in the first year, entirely founder-led 2/ Momentum: 200+ companies using Recall.ai from inbound demand 3/ Retention: Customers scaling usage by 150% because their businesses relied on us The result? We didn’t need to get through the deck. Our numbers did the talking. If you’re prepping for a raise, remember: Slides don’t close rounds. Your business does. What’s the 10x story you’d tell in the room?

Hit $1M ARR and everyone said we had PMF. I wasn’t so sure, and I’m glad I wasn’t. Our wins had no clear pattern. Customers bought for different reasons. Features were used randomly. So we cut everything except meeting integrations. Today: 1/ Closing 3x more deals 2/ Sales cycle dropped 60% 3/ 800+ customers are now building on us Real PMF isn’t a revenue milestone. It’s when the market starts pulling you forward instead of you pushing uphill. What other false signals have you seen?

2025 goal: Keep building with people who make things better by default 2024 taught us something important: culture isn’t about perks or processes. It’s about finding those rare people who see what’s broken and fix it, without waiting to be asked. They’re not the loudest voices in the room or the ones who ace every interview question. They’re the ones who quietly solve problems before anyone else notices they exist. These are the people who’ve shaped Recall.ai into what it is today. They’re why we can move fast, adapt, and keep improving. Here’s to finding and building with more of them in 2025. Who’s someone on your team who makes things better by default? Tag them below. 👇

I turned down a $500k deal. Here's why: Saying yes would’ve turned us into a different company. Instead of doing many things okay, I’d rather do one thing exceptionally well. Here’s the truth about PMF: Your best customers ask for less, not more. Focus on the ones who already see the most value. They’re the ones naturally aligned with your core product vision. At Recall.ai, our fastest-growing customers don’t need or care about fancy stuff. They need meeting data to flow into their workflows without breaking. That’s it. PMF isn’t about pleasing everyone. It’s about being undeniably the best at one thing. When have you said no, and it paid off?

$100K ARR vs $10M ARR. The difference? Stop trying to be good at everything. My first startup: great product, solid features, happy customers. Still failed. At Recall.ai, we took the opposite approach: 1/ Cut half our features 2/ Focused on one thing 3/ Became obsessed with being #1 at that single problem This year, we achieved 300% growth with 800+ companies building on our API and 150% net revenue retention. The brutal truth about PMF: 1/ Being "good enough" = death 2/ Being "#1 at everything" = impossible 3/ Being "the obvious best" at one painful problem = growth Your customers don't want options. They want the clear best choice. What one problem are you number 1 at solving?

I broke every startup “best practice” and found PMF with >$2M ARR in the first 12 months. What I didn’t do: 1/ Hire senior people first I always start with founder-led execution, then bring in a founding dev, DX, AE, or marketer. With a small, scrappy team, we build faster than teams 3x our size. Today, we’re processing millions of meetings every month. 2/ Start with a sales team We hit $1.9M ARR before hiring our first AE. By obsessing over the product instead of the pipeline, we grew to 800+ companies building on our API. 3/ Follow the standard playbook No standups. No sprints. All async. We still ship 50x/day. Real growth doesn’t come from following someone else’s formula. It comes from solving real problems in a real way. What “best practice” did you break that worked?

Today we process millions of meetings per month, and we grew 3X this year. These 3 decisions got us to this point: 1. Speed > perfection. You learn more from 10 customers using you than 6 months of planning. 2. Pick boring problems. 90% of AI companies struggle with meeting integrations. Not sexy, but that’s where the pain (and opportunity) is. 3. One thing done right. We’ve turned down $2M+ in revenue from features outside our core. Focus beats FOMO. Got any unsexy problems you’re solving?

In 2011, I thought learning the "No. 1 programming language" would make me the best programmer. So I spent 6 months mastering Lisp... I read somewhere that Lisp was the No. 1 programming language, and I was convinced I could win programming. Learning the best language = becoming the best programmer, right? Turns out, no one cared about my elegant Lisp solutions. They needed someone to fix their broken Java integrations. That expensive lesson shaped everything: Being the best only matters if you're the best at something people actually need. It's not about being the best. It's about being the best at the right thing. What expensive lesson changed how you build?

AI agents aren't just hype. We interviewed 73 companies and here’s what actually matters for enterprise adoption: 1/ AI agents fail when they can't access the right data at the right time. The winners connect to existing workflows - calendar, email, and most importantly, meetings. 2/ Companies don't want "general" AI. They want agents that solve specific problems really well. The best performing ones focus on single use cases like sales coaching or customer support QA. 3/ Integration > Innovation. Enterprises care more about how an agent fits into their tech stack than how "cutting edge" the AI is. 4/ Security is non-negotiable. The companies seeing actual adoption? They let IT teams control data access and retention at a granular level. The winners aren’t just building cool tech. They’re solving real workflow problems. What’s been your experience with AI agents? What do you see as the biggest challenge to adoption?