With 17 years at Google witnessing AI's evolution from research curiosity to global infrastructure, Yariv Adan brought unparalleled technical insight to the Panoramai panel. Now investing from the other side of the table, his perspective combines deep understanding of AI development cycles with stark realism about startup survival in an age of instant commoditization.

The Commoditization Prophet

Adan coined the term that defined the panel's central tension: "commoditized magic." His observation fundamentally challenges traditional innovation economics: « We used to associate when there is something that is highly innovative and highly valuable. We used to say, okay, that's also valuable to invest in. And I think what we're seeing today is that innovation is faster and more powerful and magical than ever. But so is the commoditization ».

The speed of this commoditization shocked even seasoned observers: « The time between creating a new state of the art thing and the open source version of it now is about 24 hours ». This insight stems from his front-row seat to AI's development, watching breakthrough after breakthrough become freely available almost instantly.

The Moat Strategy Framework

Adan's investment thesis crystallized around two defensive strategies against commoditization: unique data that cannot be easily scraped or generated, and specialized expertise that cannot be readily simulated. This framework drives his focus toward manufacturing, industrial expertise, and scientific domains where barriers remain meaningful.

His geographic perspective reflects global startup experience: « I also just wouldn't confuse made in Europe with Made for Europe. I think Europe should be much more global ». Drawing from Israeli startup culture, he emphasized: « Israel was never a market on first day. You have sales and business development in the US », criticizing European founders who limit themselves to regional markets.

The Infrastructure Bet

Adan identified two primary investment areas. First, process-level automation requiring unique data with strong network effects: « Once you're in, you can actually get better. So after a year you're better than you were when you got in. So there is like kind of a stickiness to it ».

Second, specialized infrastructure components where expert teams can outcompete larger organizations: « Every stack has this kind of pockets of expertise that usually a smaller team of much bigger experts build it. This is a kind of security running on device, maybe identity payments, these kind of things that usually either they become a horizontal or a very attractive acquisition ».

The Death of Traditional Software

Adan presented the panel's most radical vision of software's future, predicting fundamental disruption of current development models. He argued that software built on scarce engineering resources creates artificial complexity: « Because of that, it's an economy of scale. Meaning you have one company that specializes in building it for 1,000 other companies. Because of that, they need to build something that is very generic and needs to last ».

His alternative vision eliminates this complexity: « I think we're moving to a whole new place where basically the world is Excel. Right? Excel is a very generic platform and I think just AI is a much more capable one that the end user does the last mile ».

The economic implications are dramatic: « It will be so easy to generate a specific software for the thing I actually need to do right now. And the cost of that will be about a million tokens. That's about 40 cents. You will not save it ». He compared future software to disposable napkins - created for immediate use and discarded.

The Venture Capital Disruption Prediction

Adan offered the panel's most pessimistic view of venture capital's future, predicting potential industry obsolescence: « I think that yes, I think to a large degree the world should start thinking on a much larger economy of much lower margins. And I think in that economy the model of venture and startups is not the ideal one ».

His advice to founders reflected this economic reality: « Think about bootstrapping a company that is built to last. That starts from the beginning, thinking on operating at low margin ». He sees current high-margin opportunities as temporary: « There is a lot of money on the table that is not recurring because you automate humans only once ».

The industry's inefficiency particularly frustrated him: « Both entrepreneurs and investors is one of these areas that is begging to be disrupted with data based automation. Like so wasteful ». He predicted AI will eventually automate the investment process itself, eliminating what he sees as an unscientific "magic art."

The Humanistic Vision

Despite his stark economic predictions, Adan maintained profound optimism about AI's humanitarian potential. He envisioned democratizing access to knowledge: « I would just like to bring the very best education at PhD level to every person on the planet ».

His vision extended to healthcare through programmable medicines, agricultural knowledge transfer to developing nations, and energy efficiency improvements. The underlying theme emphasized AI's democratizing power: « I think this wave of AI has a, the opportunity to democratize and I think that a less hungry and more educated population is much less easy to manipulate by populist politics ».

The Google Advantage

Adan's perspective uniquely combines technical depth with market realism. His Google experience provided unmatched insight into AI development cycles, competitive dynamics, and the pace of innovation commoditization. This background enables him to distinguish between sustainable competitive advantages and temporary technical leads.

His warning about traditional software moats proves particularly prescient: « I think other modes that were used to like marketplaces could be replaced by very scalable peer to peer that agents can do. So I think a lot of the laws are being rewritten on how software is being built, used and sold ».

Key Achievement

Yariv Adan demonstrated how deep technical expertise can inform radical strategic thinking about technology's economic implications. His framework for understanding commoditization cycles provides essential guidance for European investors and founders navigating an environment where traditional competitive advantages rapidly erode.

His combination of humanistic vision with hard-nosed economic analysis offers a sophisticated model for thinking about AI's dual nature as both democratizing force and market disruptor. By grounding optimistic predictions in realistic assessment of competitive dynamics, Adan provides the kind of strategic insight that distinguishes successful technology investors from those caught unprepared by rapid change.