Jonas Diezun

Founders need conviction capital and long-term alignment. Web3 is rapidly maturing as fintechs acquire into the crypto ecosystem. Web3 innovation haven’t slowed and capital is rapidly catching up to where the frontier use cases in Web3 x AI are.... Wonderful report from Jamie Burke, Rumi Morales, Pietro Negri and the Outlier Ventures team. Their growth playbook offers a clear framework for what it takes to support founders through hype cycles into durability: 1/ Grants are not a growth strategy. Founders chasing capital over users burn out before they break out. 2/ Post Web ≠ Web3 hype, We’re entering an intent-driven internet. The convergence of AI x crypto is foundational. AI agents, RWA tokenization, and DePIN are reshaping what scalable utility looks like. 3/ Domain expertise matters from your capital partners, especially those with deep vertical conviction and ecosystem design. At Decasonic, this is what we mean by "enhancement capital." We don’t just invest, we co-build alongside the frontier. And we back founders early before they scale escape velocity. If you’re building the next breakout in AI x Web3, don’t just ask who’s funding you. Ask who’s building with you.

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We’ve looked at well over a thousand Vertical AI startups over the past few yrs at Equal Ventures. One of the important strategic questions we’ve seen many founders grapple with is around how to package AI for their chosen sectors. The 2 pathways: 1. Sell AI-powered software or services to incumbents 2. Leverage AI to build modern versions of existing industry operators (and compete head-on) We’ve backed several taking both paths and believe both can be immensely successful under different circumstances. In our latest post, we share one of the frameworks we’ve found most helpful to guide the decision on which path to go down: https://lnkd.in/eJV7KpBi

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The news around DeepSeek AI has caused a bit of a surprising “uproar” within the VC community overnight. Whether foundational models become more capital efficient or not should be irrelevant to the majority of the venture capital asset class. I gave my thoughts to PitchBook over a month ago that the most probabilistic value capture would come at the application layer and that most funds are actually best designed to fund innovation at that part of the stack. If anything, this is a great reminder that taking a first principles approach to understanding how and why technology breakthroughs will impact *end customers* and *end industries* is more important than chasing the “hot deals” in market. Overall, what DeepSeek and other leading foundational models continue to trail-blaze are net positive progressions for the world of technology and AI. This serves as more evidence that brilliant builders will only have more options, not less, as they continue to help key industries evolve to make the world a better, more productive place. https://lnkd.in/exGQzdpH

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How we rebuilt every Draper investing workflow with a custom AI stack, and why any VC team needs to do the same. 👇 We tested everything: Off-the-shelf CRMs, AI deal platforms, fancy automation suites. They were rigid, pricey, and built for box-checking, not for how we actually invest: fast, via 40 years of pattern recognition, thesis-driven, intuition-heavy. So we built our own, simply using Airtable, Otter.ai, Mappa, Open AI APIs, and Zapier to no-code automate everything together. With a lean team (plus a few fearless MBA interns) we spun up an in-house AI stack that now: 1️⃣ Ingests every update email, pitch deck, and transcript of every minute of every company meeting. From the first second we meet them to portco updates and follow ons. 2️⃣ Maps each incoming company to our sector theses and flags the outliers we love 3️⃣ Summarizes founder calls, comps, and market data in one view. Shout out to Otter.ai (a Draper portco) for the integration into our workflow. 4️⃣ Scores deals against 40 years of Draper success stories. Thank you to our Mappa (a Draper portco) AI integration that codifies our unicorn, rhino, and decacorn founders into actionable heuristics. 5️⃣ Creates one source of truth for every company that touches Draper. Every company has one singular record that that auto-logs emails, notes, memos, meeting minutes, etc. topped with an AI summary that updates in real time. 🤠 Impact in 10 weeks: • Inbox triage: 4 hours → < 20 minutes • 100% real-time visibility from first touch to term sheet • Our team of interns/analysts jumping in to run deep diligence and AI builds • Our investment team noticeably spending the reclaimed hours with founders, not multiple spreadsheets ⚡️Next up: → AI that learns what we invest in, why, and surfaces the next unconventional founders → A digital twin of Tim Draper trained on his brain, his thought processes, to coach founders for what we’re looking for in investments → Custom Draper pitch-deck feedback for founders (no more mystery rejections) → Network matching across our 18K+ contacts This isn’t just a productivity tweak. It’s venture capital rebuilt from the inside out, where internal VC intelligence compounds alongside not only our portfolio, but founders across the startup ecosystem. Thank you so much to Lucas Rosillo for leading the charge in building this incredible AI system for us. Proud to have him as an AI Advisor at Draper Associates. What else should we build in our AI stack? Drop ideas below! Would love to share thoughts. #AI #VentureCapital #Startups #Automation #FutureOfVC #DraperAssociates

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