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AI Will Return Sales to Full‑Cycle Sellers

In the 80s and 90s, most sales reps were full-cycle. They found their own meetings. They ran the process. They renewed and expanded accounts. Then we specialized: --> SDRs (thanks to the “predictable revenue” era) --> CSMs and post-sale roles (as we realized retention is growth) --> More layers of management to coordinate it all And we paid a price: more handoffs, more misalignment, more overhead, and more “local optimization” instead of true LTV optimization. My belief for 2026: AI evolves us back to the full-cycle seller. Not because the buyer journey got simpler — but because AI will make individual sellers radically more capable at: --> generating meetings --> converting meetings to customers --> onboarding customers --> expanding customers And that has a second-order effect: Sales orgs get flatter. Less middle management. Higher rep-to-manager ratios. Sellers become less dependent on managers for training, coaching, pipeline hygiene, and process adherence. If I were building a sales team from scratch in 2026, I’d do three things: Change the first-hire profile (PMF stage): Still strong at customer conversations + pattern recognition… but much more weight on experimenting with sales tech and AI workflows. Build a modular AI-native stack: Start on top of multiple LLMs. Stay interoperable. Avoid “one-vendor operating system” lock-in while we’re still in the early innings. Incentivize productivity innovation before hiring headcount: Set a higher bar, give the team tools + autonomy, and reward output — so you find the frontier of what’s possible before you scale org complexity. One caveat: AI won’t replace critical human moments (escalations, high-stakes trust) and it won’t fully replace true creativity. But it will change how we design sales teams. Watch the entire video on The Science of Scaling YouTube channel here: https://lnkd.in/e9Wxgq2F Stage 2 Capital