⭐ 𝐅𝐨𝐜𝐮𝐬 𝐨𝐧 𝐭𝐡𝐞 𝐏𝐫𝐨𝐛𝐥𝐞𝐦 𝐅𝐢𝐫𝐬𝐭, 𝐍𝐨𝐭 𝐭𝐡𝐞 𝐀𝐈: 𝐓𝐡𝐞 𝐊𝐞𝐲 𝐭𝐨 𝐒𝐭𝐚𝐫𝐭𝐮𝐩 𝐒𝐮𝐜𝐜𝐞𝐬𝐬 My startup mentoring sessions have become exciting lately. I’ve noticed a clear pattern with early-stage startups reaching out for guidance. They fall into two distinct buckets: 1️⃣ Those focusing on 𝒊𝒎𝒑𝒍𝒆𝒎𝒆𝒏𝒕𝒊𝒏𝒈 𝑨𝑰 into their products. 2️⃣ Those focusing on 𝑨𝑰 𝒖𝒔𝒆 𝒄𝒂𝒔𝒆𝒔. The first group tends to dive straight into the tech. Their questions revolve around which AI models to use, what tech stack to build, or how to fine-tune and optimize their algorithms. It’s a highly tech-driven conversation from the get-go. The second group, however, starts differently. They begin with the use case—discussing the problem they’ve identified, the gaps in the market, and how they can solve it. Only after that do we explore if and how AI could add value. I find these 𝒔𝒆𝒄𝒐𝒏𝒅 𝒄𝒐𝒏𝒗𝒆𝒓𝒔𝒂𝒕𝒊𝒐𝒏𝒔 much more enriching. Why? Because we aren’t rushing to assume that AI is some magical fix. Instead, we invest time in understanding the problem and where technology, including AI, can act as an enabler rather than the solution itself. 🔑 𝐇𝐞𝐫𝐞’𝐬 𝐚 𝐭𝐢𝐩 𝐟𝐨𝐫 𝐬𝐭𝐚𝐫𝐭𝐮𝐩𝐬: Focus on the problem your product is solving before jumping into tech discussions. It’s tempting to force-fit AI into every product just because it’s a hot trend. But trust me—if AI isn’t genuinely needed, it could end up consuming valuable resources and delaying your time to market. 𝑺𝒐𝒎𝒆𝒕𝒊𝒎𝒆𝒔, 𝒕𝒉𝒆 𝒂𝒏𝒔𝒘𝒆𝒓 𝒕𝒐 𝒚𝒐𝒖𝒓 𝒑𝒓𝒐𝒃𝒍𝒆𝒎 𝒎𝒊𝒈𝒉𝒕 𝒏𝒐𝒕 𝒆𝒗𝒆𝒏 𝒓𝒆𝒒𝒖𝒊𝒓𝒆 𝑨𝑰 𝒂𝒕 𝒂𝒍𝒍. 🧠 #StartupMentoring #AI #TechStrategy #ProductDevelopment #UseCaseDriven #Innovation #AIInStartups
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Hi Jeffrey! The reasoning and rationale you exhibit in this post are oriented towards increasing marginal profitability in the near and medium terms. But in exchange for accumulating additional golden eggs now, I'm concerned that this reasoning severely endangers the goose later. As it turns out, this is the one functional goose we all rely on as it serves our many diverging interests imperfectly. Writ large, or taken to its logical conclusion, ANY opportunity to trim or wholly eliminate human headcount as an input in the processes of production should be embraced. I often write and/or comment about the demand side's "convenience trap;" well this would be the corollary on the supply/capitalist's side. Eventually, a tipping point is reached -- same as with relying on massive increases in national debt/deficit spending to fund/finance social goods such as infrastructure spending and human capital investment, so too will a threshold be reached whereby consumer spending (the economic deployment of wages and discretionary gains from capital) will prove no longer able to power 70% of American GDP. A more astute observer might conclude that any ego-driven desire to prove my point in this public forum, however advantageous in the immediate term, can or will hamstring me in the long run were the more powerful & connected to sour on my perspectives. The same can be said of maximizing any short-term profits aided by artificial intelligence in general and LLMs in particular. There will be tradeoffs. I solemnly hope that this post is indeed food (from a golden egg) for thought because winning some small battles can be tantamount to losing more comprehensive wars that drag on with no end and with no clear winners in sight. IMO.
General Partner and Co-Founder, Flybridge Capital Partners; Senior Lecturer, Harvard Business School
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Building at the intersection of Food and Technology | Helping Organizations and Individuals thrive in the Digital/AI age.
5moI echo this 100 pc. The obsession with AI being the answer to everything is mind numbing. Really good founders start with the second approach and most likely end up with the following three buckets. 1. No AI needed 2. AI + Non AI hybrid solution 3. Solved by AI. 1 and 2 are more common if the problem is thought from a first principles perspective.