Patrick Monnot 🐙

Qasar Younis on quitting at a startup and what he learned at YC... "It’s harder to quit than it is to start. Absolutely. When you take a job — say at Meta — and you quit three months later or get fired six months in, there are a thousand ways to rationalize it. You can explain it to yourself, your peers, your family, your friends. Everyone gets it. But when you start a company, it’s all on you. You win, you lose — it’s you. When the company is just the founders, the company is the founders. There’s no separation. It’s a one-to-one match. So when the company fails, it feels like I fail. There’s no hiding in that. And to avoid facing that reality, many people just keep pushing, trying to will it forward. Which is tricky, because the dominant narrative is that startups are all about “willing your way there.” At YC, I noticed something important: the good companies were good pretty quickly. And they stayed good for a long time — often a decade or more — before going public. The idea that you’re “lost in the wilderness” for years and years? That’s the exception, not the rule. The rule is that good companies look good early."

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We nearly doubled our team in 2 months while revenue per employee jumped 5x. Here’s how we're achieving efficiency that our competitors can't match: Welcome to Ribbon: Dylan Mendonca, Hayden Caravan, Jerry Liu, and Patrick Foy! Going from 6 to 10 might not sound like much. But when you're processing hundreds of thousands of AI interviews with a tiny team, adding 4 people changes everything. We interviewed over 400 candidates to find these 4. Not because we're picky for the sake of it, but because scaling efficiently requires people who don't just execute, they reimagine how things should work. Each new hire spotted opportunities we hadn't even articulated yet. They came in asking why things worked certain ways, then fixed them without being asked. That's how a 10-person team handles what others need 50 for. We're still small enough that everyone knows everyone. But we're handling enterprise scale with startup agility. The common thread? Every person here has either been ghosted by recruiters or knows someone who has. We're building the solution to our own problem. That's not just team growth. That's building leverage the right kind of talent. The kind that transforms operations, not just maintains them.

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You don’t need funding to validate an idea... You need time with customers. Too many founders raise before they’ve really done that. Here’s how I think about when to raise: 🌱 Pre-seed — You’ve got conviction, a prototype, and you need just enough capital to run real experiments. 📈 Seed — You’re seeing usage and early traction. Funding helps chase what’s working. 🔁 Series A — You’ve got a repeatable GTM motion. Now you need to scale it. Raising too early can hurt you. You start building toward a pitch instead of listening to users. You skip the hard (but necessary) work of discovery. Being capital-constrained forces clarity. It forces focus. At Clarify, we raised Series A early — because we’re going after a big, high-leverage problem. It needed upfront investment. But we still operate with the urgency and sharpness of a seed-stage team. Raise when capital unlocks the next milestone. Not before. Curious how others think about timing. When did you feel ready to raise?

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Hiring great talent should be a founder's #1 priority. But most founders say hiring is critical, then spend less than 5% of their time on it. I've seen this pattern at hundreds of startups through Weekday. One bad hire cost: 6-12 months, team morale, opportunity cost Time to fix bad hire: 50+ hours Time to hire right the first time: 20-30 hours Yet founders spend more time choosing their laptop than choosing their team. When we have an active high-priority role open, I personally track my time allocation: - 30% of my time goes to recruiting/team building - 40% goes to sales and growth - 20% goes to product and alignment with teams - 10% goes to operations and admin This intensive focus on recruiting isn't sustainable forever, but it's critical for getting the right people in place. This 30% of time spent upfront on recruiting dramatically reduces the time you'll need to spend on alignment and operations later. The compound effect of good hiring: - Great hires recruit other great people - Strong teams attract customers and investors - Quality people create quality systems The compound effect of bad hiring: - Mediocre people hire worse people - Weak teams repel talent - Poor execution destroys opportunities Most founders optimize their time for immediate tasks (product, sales, fundraising) instead of foundational tasks (hiring, culture, systems). The practical playbook to follow here is to: 1/ Block 2-3 hours daily for recruiting when you've key roles open 2/ Treat interviews like sales calls (prepare, follow up, measure) 3/ Review your time allocation monthly What % of your time actually goes to recruiting when you are hiring for a critical role?

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Building Sales Muscles Early This thought has been brewing in my mind for a while now. We meet hundreds of companies every month and one of the most common challenges of scaling that we hear is that 90% of our business is driven by referrals. Here’s a recent conversation with a founder: His company: ₹6 crore revenue, 4 years old, great product, happy customers. "We don't need Recepto - referrals work fine," he told me. When I asked about next year's target (₹10 crore), I knew something he didn't - he'd already hitting his ceiling. From analyzing hundreds of companies (including my own), I've found: - 80-90% of Indian companies between ₹1-5 crore rely only on referrals - By ₹8 crore, most hit an invisible wall - Referral-only models reach just 20-25% of potential - Companies with proper sales processes grow 50-60% faster - Only a small percentage of referral-dependent companies ever cross ₹80 crore The stark reality? Companies that build sales muscles early on (by ₹8 crore) reach ₹80 crore in much faster than otherwise. I've lived this. At Mettl, our first ₹5 crore mostly came from my network. Relatively easy but not scalable. When we hired our first real sales team (after some painful attempts), we grew 3X (9 cr to 27 cr) in a year. What most founders miss: - Your network gets you started - Your referrals validate your product - Your sales process gets you to scale - Unknown new customers give you the best feedbacks that you can iterate upon and improve your product / service / positioning Every day without building sales muscle, you're leaving 20-30% annual revenue behind. More if you are selling globally and have a product that your existing customers love. At Recepto, I see this pattern constantly. Companies missing countless buying signals because they can't see beyond their network. If you're approaching or stuck at ₹8 crore and each sales person is ROI+, your next hire shouldn't be another engineer - it should be someone who can sell. Send me a DM if you are a founder struggling to sell / scale inspite of having a stellar product. #startupgrowth #salesstrategy #indianstartups

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Every startup pretends it’s “too early” for management until the culture rots and nobody knows who is calling the shots. Let’s drop the myth. Chaos is not a strategy. Move fast, sure. But “we’ll figure it out later” is how you end up with secret Slack channels, backroom decisions, and power games nobody admits exist. Organizational design is happening even when you’re not conscious to it. In every decision you let slide, every messy Zoom call, every time you brush off the new hire’s confusion and every quiet founder huddle that changes the plan without explanation. The unwritten rules always outlast the official ones. Onboarding docs are ignored. What sticks is what people witness, who gets away with it, and what you tolerate when you’re tired or stressed. A startup’s operating system is built in silence. It’s not what you claim in meetings. It’s the shortcuts that calcify into habits. It’s the workarounds nobody questions. By year three, most decisions happen out of habit, regardless of intention. The real price of ignoring this is that when you finally want to shift the culture, you’re fighting muscle memory, not logic. You are always shaping the organization. The only real choice is whether you do it by design or by default. Don’t brag about being rule-free. Find the rules already running the place. If you don’t like what you see, start rewriting them. Loudly, early, and for everyone to see.

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YC just announced the startups they would like to fund in 2025. And they are still bullish on AI. Retraining Workers for the AI Economy 🔍 Opportunity: Upskill workers for trades essential to AI infrastructure — from data centers to fabs. 🧩 The Gap: There’s a shortage of skilled tradespeople and no scalable way to train them quickly. 🎯 The Bet: Build AI-powered, practice-based vocational training using AR/VR and multimodal coaching to fill workforce bottlenecks. Video Generation as a Primitive 🔍 Opportunity: Generate photorealistic, sound-on video at near-zero marginal cost. 🧩 The Gap: Existing platforms weren’t built for real-time, personalized video as a core input. 🎯 The Bet: Build apps, interfaces, and infrastructure that assume video is infinite, customizable, and native to the product experience. The First 10-person, $100B Company 🔍 Opportunity: Use AI tools to operate with high leverage — and minimal headcount. 🧩 The Gap: Legacy companies are bloated and slow; modern teams can now do more with less. 🎯 The Bet: Build ultra-lean, high-agency companies where revenue per employee becomes the defining metric of scale. Infrastructure for Multi-Agent Systems 🔍 Opportunity: Deploy AI workflows that involve hundreds or thousands of agents coordinating in real time. 🧩 The Gap: There’s no mature tooling for building, observing, or debugging complex agent systems. 🎯 The Bet: Create a new layer of infrastructure — like what Spark or Kubernetes did — purpose-built for multi-agent orchestration. AI Native Enterprise Software 🔍 Opportunity: Rebuild core enterprise tools with AI embedded into the actual workflows. 🧩 The Gap: Incumbent platforms are adding AI as a feature, not rethinking the architecture. 🎯 The Bet: Build “systems of action” that help people do their jobs faster and better — not just log what’s already been done. Using LLMs Instead of Government Consulting 🔍 Opportunity: Automate expensive, repetitive tasks across regulation, compliance, and procurement. 🧩 The Gap: Over $100B is spent annually on outdated government consulting work ripe for automation. 🎯 The Bet: Replace traditional consulting with lean, scalable LLM-first products that deliver better outcomes for public sector clients.  Link to the full article in the comments👇

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The shift from ‘this is my art’ to ‘what does my company need from me?’ isn’t an easy one. One of the most unexpected parts of founding and scaling a company is how quickly your job stops being your job. Zachary Lipton — CTO and Co-founder of Abridge — reflected on exactly this. And it’s something every technical founder, especially in AI, eventually has to confront. If you're building a company around your own strengths — your ability to ship, to research, to solve hard problems — here's the truth:  ⚠️ The company’s needs will outpace your preferences.  ⚠️ Delivering value may mean doing less of what you're best at. ⚠️ You won’t be one thing. You’ll be many things, each for a season. That evolution can feel like loss — letting go of the thing that gives you pride. But it’s not just okay. It’s the job. You’re not abandoning who you were — you’re expanding what you can be. In a startup, your identity isn’t fixed. It’s adaptive. And that adaptability — more than your technical brilliance — will define your impact.  👉 So if you're leading a growing team, don’t ask yourself, “What do I love doing?” but “What does the company need most from me right now?”

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