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Centralized AI Brain Fuels Bottom‑Up Innovation

Last week, we gathered 100 Stage 2 LPs to discuss the modern AI-native go-to-market system with Ryan Meadows , CRO at Lovable and LP Stage 2 Capital . Here is a summary of my takeaways: 1. Design big, start small. Aspire for a centralized “company brain,” not a disaggregated cluster of agents The goal isn’t more agents—it’s one centralized intelligence layer that ingests all point-of-work data (Zoom, email, Slack, calls) and allows any employee to query anything. The hard part isn’t the tech—it’s operationalizing every employee's daily habits so their point of work, unstructured data feeds the brain. One brain to update. One brain to query. 2. …but operationalize a bottom-up innovation process, not top-down. Empower every employee to build. Think: ~20% time for experimentation, recurring hackathons, and a system to evaluate, dedupe, optimize, and scale the best ideas into the centralized brain. 3. RevOps shifts from system admin to spreading bottom-up innovation across the org RevOps drives the above process, identifying the breakthroughs, packaging them for scale, and spreading them across the org. Low hanging fruit GTM use cases include: next-best-action, real-time call coaching, deal rooms, CPQ. The future CRM doesn’t store data—it optimizes actions. (check out Letter AI if you want these use cases now) 4. Best change management support beats best product. The biggest blocker to AI transformation isn’t product gaps—it’s getting organizations and people to work differently. Current AI winners prioritize developing an A+ change management capability in the GTM org. 5. “Adaptive curiosity” and “creative agility” become critical hiring criteria for modern AEs AEs who perform in this modern system demonstrate adaptive curiosity, creative agility, and the openness to continually evolve the way they work. 6. The most influential innovator’s dilemma that startups can exploit is not product innovation, but internal operation innovation Incumbents can copy the product, but will struggle to copy the modern internal operating system, causing them to ultimately lose market share to the native AI startups that exploit this opportunity. 7. Humans will always outperform AI on delivering the “trust” needed to win deals.