Kevin Lehtiniitty

How to pitch: The company has zero traction —> “We’re early” You only have 2 customers —> “We’re working with design partners” You currently have no revenue but hoping some pipeline finally closes —> “we’re on track to exit this year at $3M ARR” You’re in the natural kill zone of a FAANG —> “We view them as partners rather than competitors” There’s no way the tech can actually work —>“We’re manifesting the future” And of course: One of your developers uses Co-Pilot to write some front end code —> “We’re an AI company”

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Just shipped this week's Diaspora.nz podcast with Paul Copplestone, founder & CEO at Supabase. We talk about: ⚡️why open source is an unfair advantage — as a product development strategy, supercharging recruiting, and helping build customer community. ⚡️how they are building the end-to-end tech stack for AI startups — seeing many customers grow into the millions of users in just weeks, growing to be one of the most tagged products by makers on Product Hunt + most redeemed Y Combinator “perks.” ⚡️raising $116M, and scaling to ~80 people in 30+ countries over the past 4.5 years, operating as a distributed + asynchronous team. ⚡️building three startups over nearly a decade living in South East Asia. Subscribe + listen links in comments below👇 Subscribe at diaspora.nz for weekly episodes 🎧👈

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Movac KiwiNet Deep Tech is difficult because you do not comprehend 95% of the universe using the Standard Model of Particle physics. Either learn that measurement is flawed due to human bias or experience and unbiased state through transcendence experiences corresponding to Christ consciousness. The physics of life is based on LENR and not the Standard Model of Particle physics. Unfortunately, scientific research has been captured by the materialism perspective. This is mutually exclusive to the light observed in consciousness. Physics of life. Deep Tech https://lnkd.in/gKqC3PAR Gateway into the aromatic ring Faraday cage system. Time to see the light 😁.

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“People need to eat – apps don’t,” states Evan Alcala, an entrepreneur based in Los Angeles. TriYum couldn’t have come at a better time. The app offers a number of solutions to a wide variety of bigger problems. The struggle in the food delivery app industry is real. In mid-February, food delivery app drivers, along with on-demand app drivers, went on strike in cities across the USA and Canada, demanding better pay and better work conditions. To top it all off, restaurants in cities everywhere are now being more vocal than ever before, calling third-party delivery apps a disadvantage with their high commission fees. Many restaurants now even contend that most food delivery apps are hampering their businesses on many levels: loss of brand identity, less control over customer experience, data ownership issues, and reduced customer loyalty. Customers too, like food establishments, are also getting fed up with all the hidden fees. TriYum however will be a game-changer in the food delivery app industry, which is expected to reach $165 billion market size by 2029. The new app will offer subscription-based fees for both restaurants and drivers, and customers will be billed with a flat-rate delivery fee. The app will not include any hidden fees. Customers will also receive “true” restaurant pricing. #app #fooddelivery #innovation #eat #employment https://lnkd.in/g4Zx48j3

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Vishal Sachdev highlights the strategic integration of open source and proprietary tech in architecting tech stacks, developer ecosystems and resulting business models. The world class companies effectively balance value commoditization in open source and value capture in proprietary tech. This is the strategic challenge for companies operating in #blockchain and #AI. I believe those who operate at the intersection of blockchain *and* AI stand to win this strategic battle...

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Many assumed that the industry would be well on its way to AGI or superintelligence before AI model builders’ efforts to take advantage of scaling laws might hit a wall. Recent headlines are chipping away at that assumption. One question I've been getting in my inbox: is this the era of diminishing returns for AI? We don't think so. Even if an avalanche of new clusters and synthetic data fail to deliver significantly better model performance, there are good reasons to believe that AI is still going to become orders of magnitude more powerful in the coming years — powering a new generation of startups and ultimately productivity growth and positive benefits for mankind. In fact, with agents and reasoning just beginning to scale and thousands of industry-specific models coming online, it's about to get really exciting. Read our latest blog post on the topic: https://lnkd.in/gFhniNX8

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The best founders know that enormous markets are really just chains of niches. You need to know how to attack step-by-step, building systems, gaining traction, and honing expertise with each move. Finding a true Killer Wedge can catapult you to rapid scale and help you move up the chain to the next, bigger opportunity. #startup #startups #founders

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Here’s another fantastic project built with Smart Layer, Farcaster Flow https://lnkd.in/g59-ZFwe #Web3 #SmartLayer #Blockchain

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There are good reasons to fund projects without a thesis for generating value. (1) situational ambiguity of an emerging opportunity is so high (e.g. paradigm shifts, poor/no historical data) that you'll miss out waiting for the thesis to become more clear. This is a variant of the Pascal wager (the upside is probably so magnificently big that even with low probability of success the investment is worth it) (2) the operating team is strong and reliable enough that funding them to learn-while-doing develops a better thesis than waiting for them to bootstrap it. (betting on the team then the plan). Most of the time, however, investors aren't predicating investment off these criteria. In ZIRP, it was simply because capital was (almost) free. In hype cycles, it's mostly FOMO. Sure there are other rationalizations which can be made, but these are more for optics rather than articulating the underlying decision-criteria. Investors who pay closer attention to clarity of thesis, plan, and operational rigor will fundamentally be allocating capital more efficiently than those who follow trends/patterns on sector and pedigree alone.

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Increasingly we see a lot of fundraising news "leaked" before the fundraising is done. This week there's a $300M at $2B+ story on Physical Intelligence as well as a $500M at $8B+ story about Perplexity AI. Earlier this year we heard rumors around OpenAI's raise and Figure AI's raise. What's going on here? Why all the leaking? As a founder, I try to understand which way the winds are blowing in the fundraising landscape. We've never leaked or had our fundraising details leaked, so I've been curious how it happens and why. Aren't fundraising deals fragile and this adds risk? In practice, usually these are being leaked by someone friendly with the company that is fundraising. Most of the time though, they're leaked after the company has a strong enough hand to get the fundraising deal done. Looks really bad if it leaks and then the fundraising doesn't get done. But the idea is to drum up more investor interest and to force investors who might be on the sideline to jump in by creating a little extra FOMO. Investors understand this game, so rather than a sign of weakness ("wow, that deal's gone on so long that it must be all just rumors"), leaking the fundraise details can be seen as a sign of strength ("wow, they must be pretty confident to put that out there"). The fact that investors are excited about the robotics space and the fusion of AI and robotics is terrific news I think for those of us active in this space. I happen to believe a) everyone knows how important the foundation models for robotics will be and we're going to see multiple models emerge like we have with LLMs b) the winning companies will have a vertically integrated robotics story direct to customers. This is why I think companies like Perplexity AI and Glean are extremely interesting and companies with more academic and less commercial roots like Character AI or Covariant have folded and been acqui-hired. Time will tell how the robotics foundation models space plays out. Our own work on foundation models has revealed both a lot of potential and some significant bottlenecks [links in the comments]. We track everyone and we hear lots of claims, but so far haven't seen an approach that busts through the bottlenecks and nothing that seems protectable or defensible when NVIDIA, Google, Amazon, Meta, Hugging Face, OpenAI are also all investing here. Good luck to PI as they work to close this round! Hopefully this article helps push the deal over the line with the terms they want! https://lnkd.in/dpp24QcY

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📣 Free founders-only event below! I often see founders get a lot of early traction in signing customers and then hit a wall when trying to scale that repeatedly. Why?? Maybe it's because: 1️⃣ that 1st group of customers came through warm intros from your accelerator batch 2️⃣ you've already combed through industry connections from your previous career 3️⃣ you're just good at brute-force selling but you're only one person 4️⃣ you are still narrowing in on product market fit Next week I'm hosting a free, founders-only candid discussion with two people who have had to break through this wall out of necessity and now coach countless founders on this. More on our speakers: 📈 Ian Illig took his 1st job out of college at a friend's startup (employee #1). He quickly found himself trying to sell a product that was still finding its market fit. Fast forward years later and Ian had completely built out the sales team and revenue, allowing the company to get acquired. And then he turned around and did the same thing again with the same founding team. 👀 Sonia Baschez was one of the 1st employees at Atmos, a consumer & builder-facing product for homebuilding. She developed early marketing channels & helped the company grow from Pre-seed to Series A. Sonia optimized product launches to reach the right customers, a challenging feat given their core customers are actively NOT in the tech bubble (aka Techcrunch and a thread on X are not going to do the trick). Whether they know it or not, both Ian and Sonia have been secret superpowers for me as I've grown The Council Fund and supported portfolio companies. I'm excited to share their playbooks & expertise with founders for FREE next Wednesday. Join us 12-1pm Pacific! Link to RSVP in comments below ;)

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This is a must listen to for anyone B2B founder. How to figure out Product Market Fit. One of best frameworks I've seen in a while. https://lnkd.in/ghSmhVNB

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Blind optimism vs. pragmatism, the psychological patterns that lead to failure, the future of "moats" in the age of AI, and images of me apparently staring wistfully into space.... Thanks Brian Ondrako for a great podcast!

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Why founders believe they have an 82% chance of success when the reality is closer to 10%. And why being in that 10% means resisting the standard playbooks. That and more in my conversation with Brian Ondrako of the Just Get Started podcast. Check it out and ping me with questions or ideas! 

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Apple to developers: Heads I win, tails you lose (part 4) In pursuing DMA compliance, Apple’s changes to link-out, in aggregate, don’t make its more use feasible: it’s another example of a “Heads I win, Tails you lose” proposition from the company. The new fee structure, to my mind, erodes the commercial benefits of the new, less-restrictive link-out rules. Developers only save 5% relative to App Store payments on transactions for the first year after a user’s installation, and fees apply to transactions that take place on any platform. The user-level attribution burden and reporting requirements alone render the 5% savings unattractive, not to mention the conversion friction inherent with (admittedly, less intimidating) disclosure sheet and off-platform transaction process.

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So many burnt out founders. But also: So many surplus elites. And also: A new paradigm for low-risk idea-stage innovation in founder/startup/community/vc formation. That's Slyk IO We level up together: https://lnkd.in/grEmV-R6

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Investors today don't fund IP or product development... ...They fund traction. But, how do you establish sufficient runway to traction? Old way: Savings + FFF (friends, family, and fools) funding. New way: Bootstrapping (not self-funding, but customer-funding) Bootstrapping: low burn rate + sell before you build + speed of learning = traction Bootstrapping is the new default startup operating system.

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