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Revenue Engineering: How to Price (and Reprice) Your AI Product — Kshitij Grover, Orb

Jun 27, 2025 · 15:39

Kshitij Grover, CTO of Orb, argues that AI-native pricing treats monetization as a first-class engineering concern, with pricing acting as a form of friction that must balance value delivery, audience, and rapidly changing margins. He walks through examples like Replit’s multi-tier transparent pricing with a free tier to prove value before charging, Unify’s higher price point and credit-based model to signal enterprise readiness, and Cloudflare’s charging for CPU milliseconds rather than wall time to pass on architectural advantages. Grover explains that margins are not fixed; companies should protect against degenerate workloads with guardrails rather than linear scaling, as Jasper did by going unlimited after switching models seamlessly. He emphasizes flexibility, noting Orb customers make price changes two to three times a month, and advises simulating pricing impacts on different usage cohorts. Predictions include price wars, convergence toward effectively unlimited plans with caps, more real outcome-based pricing with clear SLA definitions, and real-time spend visibility with agent prompts estimating credit usage.

The Price of Intelligence - AI Agent Pricing in 2025

Feb 22, 2025 · 20:38

Shitej, co-founder and CTO of Orbe, argues AI agent pricing must continuously evolve, citing Intercom's 99 cent per resolution outcome model, Clay's prospecting credits, and Cursor's tiered usage limits. He stresses aligning pricing with target audience—SMB vs. enterprise—and maintaining simplicity and predictability. Cost structure is key: Character.AI optimized inference to support 100M DAUs, while Jasper leveraged a model decision engine to offer unlimited credits. Shitej emphasizes flexibility, noting OpenAI's price drops force repricing, and predicts 2025 will see more unlimited plans, outcome-based pricing with SLAs, and greater investment in pricing R&D for usage visibility.