Satish Kanwar

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The AI hype bubble is almost over. When investors refused to fund new AI startups because they know they’re going to fail, then the AI hype bubble is starting to fail. Even the most clueless, Investors now know that this is a bubble waiting to burst like the metaverse bubble and the dotcom bubble. And nobody wants to be left, holding the back on this bubble. The era of free money iis over with interest rates sky high. When big tech companies are losing money on AI and the bigger AI startups are demonstrating that they are all dead and struggling to even have revenue, then no one is interested in funding, smaller AI startups that they don’t believe will be profitable anytime soon. People aren’t waiting for an AI unicorn to break out. They are waiting for Microsoft, Google, Amazon, and similar to start buying distressed AI startups. Collapsing companies and minimal paths to profitability doesn’t help a space that was already overhyped. Don’t forget in all this mess that the unfortunate reality is that engagement and retention don’t match installs and downloads. What I mean by this is the most basic of mobile tracking were ignored. You don’t judge success in the mobile market based on downloads or installs, but rather based on retention and engagement. What this means is, it’s not actually impressive for OpenAI to get to 100 million users quickly if 2% of them retain. The question is not how many people signed up for a free account. The question is how many monthly active users and daily active users do AI startups like OpenAI, Anthropic, Perplexity, Stability, and others have. And how many are paying customers? And what we are finding is that retention is in low single digits. The reality is that AI startups are getting users the way that mobile free to play did. And they haven’t found a way to actually make money on that. Don’t ask an AI startup how many users signed up. Ask them how many DAUs and MAUs they have. Ask them what their ARPDAU is. What you will find is that every number is low. AI startups have no idea how to do monetization, and they don’t have regular active users in any volume. What this points to is that they’re all going to fold or get bought.

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The size of Canada combined with the geographic distribution of health conditions make the country ideal for multi-channel healthcare (e.g., Telehealth). Despite the significant demand for healthcare broadly, those business models haven't been able to achieve exponential growth or ideal unit economics just yet -- they've certainly grown and many are profitable, but millions of Canadians still lack primary care. It's a problem that's on the cusp of being solved (e.g., AI, integrated care) and could unlock significantly more access to care for Canadians. 

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For the past two weeks, I've been on the road, traveling across Canada and the US, giving talks on the intersection of AI and biotech. On a philosophical level, I feel fortunate to work in a field that is transforming biology from a specialized craft into a standardized engineering discipline. This shift is incredibly exciting. Just as mathematics revolutionized physics by uncovering nature's rules, AI and machine learning are now deconstructing biology into an engineering science. On a professional level, computational techniques are becoming central to biotech and healthcare startups, enabling close collaboration with domain experts. This transformation compels us to rethink resources, cloud infrastructure, access models, business models, and care paradigms. It's an exhilarating time for innovation and change. On a personal level, I’ve been overwhelmed by the large, diverse crowds of professionals attending my talks. They range from recent graduates from top-tier universities to mid-career and senior professionals from various technical and social backgrounds, all seriously considering careers in this space. Yes, there is hype. It takes effort to discern which companies are genuinely substantive. However, we have made significant progress, often led by quieter yet impactful startups. Yes, data silos are a problem. However, we are seeing leaders from government, academia, industry, and the private sector work together to unlock that access in an ethical and safe way to support advances. Stay tuned for some exciting news I'll be sharing soon :) #synbio #bioengineering #compbio #startups #biotech #venturecapital #artificalintelligence #AI #ArtificialIntelligence #Innovation #AICommunity #StartupEcosystem

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Collision Conf is one of the biggest tech AI events in North America and I am looking forward to learning more in this exploding space. If anyone is heading that way, feel free to ping and we can connect! #AI #generativeAI #digitaltransformation

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Over the weekend, Tobi, the founder and CEO of Shopify, discussed the major reason investors passed on Shopify in the early days : market size. I remember that financing round, & I remember having the same concern, & making the same mistake. Living in the valley & driving on 101, the billboards & logo-adorned headquarters of successful companies provide a daily infusion of all the mistakes in I’ve made in guessing how a company or a market might evolve. Years later, I listened as Bill Gurley shared his thoughts about market size. He asked himself a question : whether the startup was increasing, decreasing, or maintaining the market size? (I can’t seem to find the link - but I have it in my notes!) I added that question to my diligence list when meeting startups. Now much later, having seen many companies create categories or reinvigorate aging ones, the question I ask myself has evolved. It’s not as the market size large enough? Instead, it the question is : do we believe this company can create the market? Market size is the output of all the players marketing, selling, building. Their efforts alter, distort, & juice the supply/demand curves of macroeconomics. It’s not a given - not an output or a steady-state CAGR. Often it’s the startups that engender the demand, change the market dynamics, & make markets massive by taking risks with products. When done right, these founders create category-defining businesses like Shopify (now worth $90b)!

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