Leon Papu

How to split equity in a start-up is essentially about founder alignment. It is not an easy task. One of the difficult aspects is to (1) incentivize the right people to join in the early stage and yet (2) to keep enough equity to get to the finish line (in the current climate this takes about 10-12 years) Founder alignment shall be considered: - Short term - Medium term - Long term

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Insights on how to hire amazing people from Pedro Arnt, CEO of dLocal (1,000 employees) and ex-CFO of Mercado Libre (58,000 employees). Pedro has hired a lot of people over the last three decades. What has he learned? Structured Interviews Aren’t Enough. Work Samples & Reference Checks Are Key. Relying solely on structured interviews is a poor way to evaluate talent. While structured interviews are a step up from unstructured ones, they still feel like a crapshoot and leave too much uncertainty about a candidate’s potential. Pedro’s research showed that work samples are more predictive of future performance than interviews. However, the single best thing you can do before hiring someone is getting insights from people who’ve worked closely with the candidate. What colleagues and former managers say about a person over a long working relationship is the most reliable predictor of success. Redefining Reference Checks. Reference checks can often be regarded as a formality, with referees being hesitant to provide critical feedback. To change that, one has to create an environment where referees feel comfortable giving honest, candid evaluations. This involves setting the right tone early in the reference call, ensuring confidentiality, and asking structured questions about both strengths and weaknesses of the candidate. Full Fintech Leaders episode ⤵⤵⤵ Substack: https://bit.ly/3YnBopc Spotify: https://spoti.fi/3Yr711r Apple: https://apple.co/4f4VoTb Youtube: https://bit.ly/3U8V8dH

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AI Adoption Beats in Latam companies | Volume #2 The Age of AI is about 18 months old. Hundreds of $ billions have been invested in laying down the infrastructure needed to support this AI revolution – from Data Centers (GPUs) to more capable LLMs to Enterprise applications (AI Agents). And now businesses are beginning to bring these tools – such as ChatGPT, Claude, Perplexity, Co-Pilot – to their workforce. From the media hype and the number of times CEOs mention AI in their earnings calls and investor days, you would think the average knowledge worker is using AI every day of an efficient and productive way. The truth: A very small group of knowledge workers is using AI every day. An even smaller group is using it effectively. And that means very few organizations are seeing ROI on their workforce AI investments. According to recent “AI Proficiency Report” by Section, only 7% of employees are in the “AI Leaders” class. These are people who have experimented with various LLMs, learned how to prompt, and integrated AI into their operations and workflows. In comparison, nearly 60% are “AI Newcomers” – people who have played around with ChatGPT a few times, but haven’t committed to it or learned to use it well. If your company is 60% of “AI Newcomers”, you have no idea (yet) what AI can do to transform your workforce. Pharma Moderna boasts an 80% AI employee adoption rate – suggesting that they are seeing significant productivity gains across their 6,000 person workforce. But they are the exception in 2024. Most companies won’t see the efficiencies they hope for with a small AI working group of superusers. So where should you start? The 82% of employees who are “AI Newcomers” or “AI Experimenters” are open-minded, but they need help. 60% of the “AI Leaders” are saving between 10% and 30% of their time each week with AI because they’re using it as more than a content creator. That’s 12 hours (per week) ripe for more creative, strategic, and analytical thinking. So what’s stopping the 93% of other employees from doing the same?. What AI Leaders’ companies do differently? 1. Their company approves of AI (and says so publicly) AI Leaders members are more likely to be working in companies that have a clear AI policy that is in favor of AI use. 2. Their company has deployed AI training and paid for it The AI Leaders Class is the most likely to be receiving company support, largely in the form of AI training, from their employer. 3. Their company has deployed an LLM 77% of companies have not deployed company- or team-wide LLMs — but the largest segment of people who have access to one are in the AI Leaders Class (39%). Your turn: I hope it is useful… if you think it deserves a like, comment, repost, it will be welcome. On your side… if you want to share how you are going to design, plan and lead the AI Proficiency, Strategy and Roadmap Planning 2025… I’m just a DM or Free Discovery Call away (link on first comment). #AI #Adoption #Latam

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I remember the pitch deck. It was 2021, and Baubap, a Y Combinator startup, was disrupting the financial landscape in Mexico with their unique approach to microloans. They had impressive traction, but the valuation was high. Most investors hesitated. But I saw something different: a company with explosive growth potential, fueled by a data-driven approach and a strong team. I knew I had to invest. Fast-forward to today, and my investment in Baubap has grown 32x in just three years! On this week's Lobster Talks Podcast - Y Combinator Secrets, I share the insights behind this successful investment, outlining my investment criteria and why I prioritize growth and traction over sky-high valuations. Learn how you can: - Identify top-performing Y Combinator companies. - Maximize your chances of co-investing in these high-growth startups. - Unlock the "YC premium" and achieve greater investment returns. Watch the full episode now to discover the secrets behind my investment strategy and how you can find your own unicorn: https://lnkd.in/eUkUAYF4 #ycombinator #venturecapital #investing #startup #growth #unicorns #lobstercapital #baubap #fintech

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Wing Venture Capital's Founder Docs project is a unique collection of startup wisdom, by founders, for founders. The authors of the docs are talented founders themselves, sharing their experience on the topics they are most passionate about. I'd like to highlight the contributions of Edo Liberty, founder / CEO of Pinecone. Edo writes about the special opportunities for the scientist / founder (and he is one of the best of this breed!), as well as some of the risks and challenges they face. I got a lot out of reading Edo's stuff and I suspect you will too! https://lnkd.in/g_wyRMiE

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Meta Q1 FY 24 Meta has two business segments: FoA: Family of Apps (Facebook, Instagram, Messenger, and WhatsApp). RL: Reality Labs (virtual reality hardware and supporting software). FoA Daily Active People grew 7% Y/Y to 3.24 billion. Zuck called out healthy growth in the US, on WhatsApp specifically. As expected, management stopped reporting Facebook standalone numbers. 📊 Ad impressions grew 20% Y/Y (vs. 21% Y/Y in Q4). Average price per ad grew 6% Y/Y (vs. 2% Y/Y in Q4). Growth was strongest in Europe and Rest of World. The average revenue per person grew 18% Y/Y to $11.20. Higher engagement met continued strong advertising demand. For context, 💰 Operating cash flow was $19.2 billion (53% margin, 4pp Y/Y). Free cash flow was $12.5 billion (34% margin, 10pp Y/Y). Balance sheet: Cash, cash equivalent, and marketable securities: $71.5 billion. Long-term debt: $18.4 billion. 👀 Q2 FY24 revenue was $37.7 billion in the mid-range ($38.3 billion expected). FY24 expenses $96-$99 billion (previously $94-$99 billion). FY24 Capex $35-40 billion (previously $30-$37 billion). So what to make of all this? User net additions were consistent with Q4 metrics. Meta still found a way to add another 50 million users to its Family of Apps. However, it was a slight slowdown after four consecutive quarters of accelerating growth. Revenue grew 27% Y/Y in constant currency. It was another acceleration from 23% Y/Y in Q4. The usual suspects were behind ad revenue growth: The online commerce vertical was the largest contributor to year-over-year growth, followed by gaming and entertainment & media. Growth was strongest in Rest of World (40%) and Europe (33%). 💻 Reality Labs revenue grew 30%, driven by Quest 3. The lower loss for this segment was primarily due to a favorable comp with restructuring costs last The operating margin improved following the “year of efficiency.” Meta incurred $3.5 billion in restructuring charges in FY23 (primarily facilities consolidation and employee severance costs). However, it was slightly down sequentially. 💰 Returning cash to shareholders: Stock buybacks were $15 billion in Q1, a huge increase compared to $9 billion in the prior year. Management still finds the stock attractive enough. They also paid $1.3 billion in dividends. Free cash flow hit a Q1 record, another manifestation of the year of efficiency. While Meta loses nearly $16 billion annually on Reality Labs, the company remains a cash-printing machine ($48 billion in free cash flow in the past 12 months). FY24 Capex and operating expenses were raised, primarily due to higher infrastructure investment to support the AI roadmap. #meta #ai #ads #growth

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