Advisory for the boards of portfolio companies at a technology-focused VC firm on agentic AI for internal efficiencies across the portfolio

Context

A technology-focused venture capital firm with a portfolio of enterprise software and AI companies at different stages of growth. The firm wanted to help its portfolio leadership teams understand, quickly and practically, where agentic AI could create operational leverage.

The challenge

Portfolio companies face strikingly similar operational pressures regardless of vertical: long, multi-stakeholder enterprise sales cycles, implementation-heavy onboarding, and customer success teams that don't scale linearly with the customer base. The opportunity for agents was real, but every company was at a different stage and had a different appetite. Leadership teams needed a way to separate signal from hype and to know what to adopt now versus what to build later.

What we did

I advised the boards of portfolio companies on agentic AI for internal efficiencies — helping leadership teams understand where agents could streamline operations, reduce manual overhead, and accelerate decision-making across the portfolio. The advice was framed around practical decisions: where to buy proven, off-the-shelf agents versus where to build differentiated capability; how to sequence adoption by company stage; and how to keep tooling interoperable as the ecosystem matures.