Reverse-Engineering the AI Buyer — Aliisa Rosenthal, Acrew Capital
AI Engineer World's Fair 2026 · 19:10
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Venture capital
Acrew Capital
Acrew Capital invests in technology companies across fintech, security, data, healthcare and applied AI. Its Early Fund leads or co-leads seed and Series A rounds with checks of $1–15 million; its Inflection Fund invests $10–20 million at Series B and beyond. Alongside capital, Acrew offers founders access to its whole investment team, supporting company building and leadership development as businesses expand operations and reach more customers.
Founded in 2019, Acrew’s founding partners include Theresia Gouw, Lauren Kolodny, Asad Khaliq and Mark Kraynak, whose backgrounds combine venture investing with product, engineering and company-building experience. The firm organizes specialist practices in Data & Security, Fintech and Health within one investment team. This connects healthcare founders with cybersecurity expertise and gives data and security companies access to experience serving financial-services and healthcare markets.
In 2026, Acrew reported managing over $1.7 billion across multiple funds. Its portfolio includes Chime, Cato Networks, Vanta, Writer and Invisible Technologies. Aliisa Rosenthal joined as general partner in 2026 after leading sales at OpenAI. Her work with early-stage founders covers go-to-market strategy, pricing and packaging, sales architecture and enterprise readiness—concrete commercial decisions facing companies bringing AI products into business use.
Explore the recordings
The supplied Acrew Capital archive contains one recording: Aliisa Rosenthal’s account of AI enterprise go-to-market lessons from her time at OpenAI. The paths below explore different parts of that talk. Revenue figures, pricing, launch decisions and operating practices are presented as her recorded recollections and recommendations, not verified facts about OpenAI today.
Choosing between self-serve and enterprise sales
Start with Reverse-Engineering the AI Buyer for Rosenthal’s account of enterprise demand shaping ChatGPT’s launch and the tension between supported sales and self-serve adoption. She says that, in hindsight, she would have launched self-serve first and used customer feedback to shape the enterprise tier. Her discussion of an initial $60-per-user monthly enterprise price, subsequent usage-based charges and spend caps provides a recorded case study in pricing tradeoffs, rather than a guide to current pricing.
Finding and removing buyer friction
Follow the sales-process thread in the same recording: acknowledge inbound inquiries, automate research and follow-up, then identify where human help is necessary. Rosenthal connects missed follow-up opportunities with practical ways to shorten buying cycles, including simpler paperwork, trust portals and automated security questionnaires. She also discusses alternatives to supported pilots, such as reference calls, evaluations on customer data and contracts with a 90-day opt-out.
Deciding where people and customization matter
Use the talk and its Q&A to examine when sellers, design partners and forward-deployed engineers may justify their cost. Rosenthal distinguishes self-serve product-led growth from resource-intensive supported proofs of concept, recommends closely supporting carefully selected first customers, and describes customized integration as potentially valuable for retention. These are her recorded recommendations; the archive does not establish their effectiveness for every company or describe Acrew Capital’s current operating practices.
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