Stripe's Experimental Projects Team discovered that embedding its members directly within existing product and infrastructure teams leads to higher success rates. These "embedded projects" are more likely to reach escape velocity and be successfully adopted by the business, contrasting with the common model of an isolated R&D or innovation lab.
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Contrary to the remote-first trend, Crisp.ai's founder advises against a fully distributed model for initial product development. He argues for gathering the core team in one physical location to harness the energy and efficiency of in-person collaboration. Distributed teams are better suited for iterating on an already established product.
Small firms can outmaneuver large corporations in the AI era by embracing rapid, low-cost experimentation. While enterprises spend millions on specialized PhDs for single use cases, agile companies constantly test new models, learn from failures, and deploy what works to dominate their market.
In an AI-driven world, product teams should operate like a busy shipyard: seemingly chaotic but underpinned by high skill and careful communication. This cross-functional pod (PM, Eng, Design, Research, Data, Marketing) collaborates constantly, breaking down traditional processes like standups.
When an experiment succeeds (e.g., positive framing after a loss), don't just iterate. Exploit the core psychological insight by applying it across adjacent product areas, turning one team's discovery into a company-wide growth strategy.
Afeyan advises against making breakthrough innovation everyone's responsibility, as it's unsustainable and disruptive to daily jobs. Instead, companies should create a separate group with different motivations, composition, and rewards, focused solely on discontinuous leaps.
Chess.com's goal of 1,000 experiments isn't about the number. It’s a forcing function to expose systemic blockers and drive conversations about what's truly needed to increase velocity, like no-code tools and empowering non-product teams to test ideas.
Forcing innovations to "scale" via top-down mandates often fails by robbing local teams of ownership. A better approach is to let good ideas "spread." If a solution is truly valuable, other teams will naturally adopt it. This pull-based model ensures change sticks and evolves.
To launch new products and compete with agile startups, embed a small "incubation seller" team directly within the technology organization. This model ensures tight alignment between product, engineering, and the first revenue-generating efforts, mirroring the cross-functional approach of an early-stage company.
Spreading excellence should not be like applying a thin coat of peanut butter across the whole organization. Instead, create a deep "pocket" of excellence in one team or region, perfecting it there first. That expert group then leads the charge to replicate their success in the next pocket, creating a cascading and more robust rollout.