Machine learning

Aligning Founder Superpowers with Product Cycles

Watching the generative AI space shape up over the past several months has reaffirmed my belief that, as product cycles mature, different types of builders have leverage at different moments in the cycle. And, at this early stage in generative AI, technologists and product pickers will likely have the biggest impact on which companies emerge as winners.

Typically, technologists and product designers have the leverage early in a product cycle as new capabilities and product patterns emerge and stabilize. Technologists and product pickers are the kings in this stage because of the rapid feedback loop between new capabilities exposed by the technology and new compositions of those capabilities delivered to customers by product pickers. This is too soon for a purely GTM-oriented founder, as the underlying technology and product patterns have yet to stabilize; word of mouth is the biggest driver of customer adoption. This corresponds to what Carlota Perez would call (in Technological Revolutions and Financial Capital: The Dynamics of Bubbles and Golden Ages) the “installation phase” of a new technology, when exuberance drives rapid installation and adoption of new technologies, lead by tinkerers and technologists.

Later, as the product patterns commoditize and the goal is to maximize market share for products that are already working, marketing-oriented founders have the advantage. This is why GTM-oriented founders dominate markets like SaaS: The underlying enablers have stabilized and hardened, and there is a lot of competition (it’s crowded), so the battle shifts from the feature war to a GTM execution game. Finally, as the marketing patterns and best practices stabilize, and markets consolidate around a few winners, business development and corporate development leaders (at new companies and incumbents) have leverage.

These two cycles (marketing- and business-development-led) correspond to the “deployment” phase that Perez outlines, where new technologies are widely deployed throughout industry and society, delivering the benefits more widely than in the installation phase.

Source

Mots-clés : cybersécurité, sécurité informatique, protection des données, menaces cybernétiques, veille cyber, analyse de vulnérabilités, sécurité des réseaux, cyberattaques, conformité RGPD, NIS2, DORA, PCIDSS, DEVSECOPS, eSANTE, intelligence artificielle, IA en cybersécurité, apprentissage automatique, deep learning, algorithmes de sécurité, détection des anomalies, systèmes intelligents, automatisation de la sécurité, IA pour la prévention des cyberattaques.

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