Adeo Ressi

Working with NRF to pursue our patent strategy is an important step in recognizing that proprietary AI systems and workflows are becoming a new form of intellectual property for modern firms. Great to partner with George, John McBride, and the team at Norton Rose Fulbright as we work at the frontier of how AI can transform investment decision-making in venture capital. At Decasonic, we believe the next generation of companies will reinvent with AI workflows and systems how organizations operate, how leaders make decisions, and how teams collaborate with intelligent systems. In going through this streamlined process, it's clear to me that many more startups should clarify their IP strategy. Our internally developed AI platform, RLEN, reflects that philosophy. We are building AI not to automate tasks and flourish outcomes, in collaborative ways for human and AI teammates. This enables our investors to test ideas, explore alternative perspectives, and reach deeper insights faster when navigating uncertainty. More broadly, we are seeing trailblazing work across industries and cities as leaders experiment with how AI can reshape communities, companies, and countries. Leadership with AI forever transforms. We are still in the early innings. Appreciate the partnership and collaboration from the Norton Rose Fulbright team as we continue inventing and innovating. Special shoutout to my colleague Abdul Al Ali who's listed as a co-inventor.

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I’ve spoken to over 2 dozen MDs at PE firms I can confidently say that the arb of figuring out how to implement Vertical AI at portfolio companies is very real right now It will fundamentally change underwriting for those who can do it predictably and unlock generational returns. Most are aware they need to act. Very few have.

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😧It appears the public markets fear of AI has done a 180 - from fear of excessive investment to AI's ability to obliterate long incumbent software companies. I have a feeling we are going to hear the new riff "software is eating software" more times than the famous 2011 op-ed statement from Andreessen that "software is eating the world". Another 180 - long hardware, short (trad) software 🤯. AI infrastructure is literally eating memory. The global memory-ship shortage is expected to last another few years! 💽 Shout out to our pals at Inovia Capital for their State of Canadian Software Report. Thanks for the Miovision mention regarding the massive partnership potential for Canadian companies in the Middle East. 👉 https://lnkd.in/dyB8JkEh

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There’s a lot of conversation about how AI is concentrating capital. That’s real. But I’m also seeing how it’s expanding what small teams can build. At ThriveLink, AI has allowed us to move faster, reach more patients, and build technology that helps families navigate systems that were never designed to be easy. We’ve been able to do with a small amount of capital what used to require entire teams and millions in funding. The tools are changing. The mission isn’t. Thankful to the Los Angeles Business Journal and Plug In Ventures for highlighting the changing venture landscape and what founders like myself are navigating right now.

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More layoffs announced as the economy remains uncertain and the slow (but increasing) march towards increasing ai/automation dominance continues. Neo-liberal capitalism is not equipped to deal with the social upheaval this will cause. In order to soften the blows, business and government leaders need to re-orient our system from income for labor towards income from assets, with more widespread asset ownership. At the national level, it looks like sovereign wealth funds, but at the local level, it’s increasing support and incentives for employee-owned businesses and co-ops, which have proven to be more resilient through economic shifts over time. https://lnkd.in/esXW4CKa

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Two articles I've been thinking about together this week: Amir Kabir at Overlook VC on "the defining tension of 2026: extraordinary concentration at the infrastructure layer, extraordinary democratization at the application layer" Take a read: https://lnkd.in/gyaFg-nB And Isaac Arnold's framework for what actually makes an application layer company durable: workflow entanglement, domain specific knowledge, and data that compounds from usage rather than just intelligence. Take a read for yourself: https://lnkd.in/gSDXA-vH Amir identifies where the opportunity is, Isaac identifies why most companies building there won't capture it durably and what separates the ones that will.

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Wow! Fascinating article Andrew Antos & Nischal Nadhamuni about how the Klarity platform does knowledge capture! A total disruptor indeed for how consultants traditionally did this work! Capturing not just what happens but why it happens has always been the missing link in enterprise AI, and Klarity ’s approach to surfacing human reasoning through its intelligent platform is a real step forward. The #AI Advisor’s ability to traverse vast context graphs, uncover cross-team patterns, and turn knowledge into actionable insights shows how innovation in knowledge capture can truly transform enterprise decision-making.

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AI isn't just powering software. BrightAI just raised $51 million to automate inspection and other hardware-based AI capabilities. As Alexa von Tobel, co-founder of Inspired Capital put it: “So many people are so focused on the future of digital AI, but we’re excited about this new layer of AI: the physical world AI.” We are in the early innings of a series of AI-fueled innovations! https://lnkd.in/enhmafvH

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“Hey DC — I’m raising a pre-seed at a $50M cap. Interested???” I ought to ignore the cold outreach like everyone else, but I can't help myself from replying, “Not at a $50M valuation!” “But we did a discounted cash flow analysis and calculated the valuation at $50,874,392.66.” DCF is the perfect answer to the question: tell me you know nothing about startups without telling me how you’re going to fail. But how should this founder determine the valuation of his startup? There’s a lot of methods to value startups. DCF. Berkus Method. Discount off next round. Cost to duplicate. Scorecard. Comparable transactions. Blah blah blah. None of them work. Valuation is not a calculation. It’s a negotiation. The only method that works is what I'll call the Palter Valuation Process. It's a process rather than a formula, with the following simple steps: 1. Determine your stage. Honestly. Based on customer traction rather than wishful thinking. Is this raise a friends & family & network (no traction yet), pre-seed (initial sales), seed ($100K+ ARR), or Series A ($4M+ ARR)? 2. Find typical valuations for your stage, sector, and geography. Look at both the median and ranges. Use the incredibly helpful data from Carta (thank you Peter Walker and Carta) plus whatever you can find from Pitchbook, Crunchbase, investment banks, and VCs that follow your sector. 3. Adjust within the ranges based on your traction and risk factors. 4. Check with a few trusted advisors who invest regularly at your stage to see if they think your proposed valuation will be attractive to investors in their network. 5. Begin pitching to potential lead investors. Negotiate the valuation and other investment terms. 6. See if the valuation attracts follow-on investors to fill the round. If not, renegotiate with the lead investor and other investors to set the final valuation. Keep in mind that valuation is just one piece the investment puzzle. Liquidation preference frequently determines how much (if anything) founders and employees get in an exit and is arguably more important than valuation. Investment vehicle (preferred shares, common shares, SAFE, convertible note) make a big difference to investors and will affect the valuation we find attractive. Full details on the Palter Valuation Process in the following article: http://bit.ly/3UAIwMw

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Very exciting to see the future of light based AI infrastructure becoming very very real. The next big wave is starting.

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mpathic is becoming THE partner to the AI industry as they work to safeguard users from adverse mental health and safety outcomes As millions of users — including large numbers of young people — increasingly turn to AI chatbots as their first-line “counselors” and confidants, Seattle-based startup mpathic is stepping in to ensure those digital agents don’t provide dangerous advice when it matters most.

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