AI Agents Are Only As Good As The Tools They Can Reach

Jennifer Artabane is SVP of Product Management at Auros, with 20+ years of experience in enterprise software, health tech and e-commerce.

Every serious software company supports Model Context Protocol (MCP) now. In under two years, MCP has gone from experimental to an assumed offering. According to a December 2025 Stacklok survey, almost half of the responding technical leaders from the software industry stated they were using MCP in production.

MCP support on its own no longer distinguishes anyone. Best-in-class MCP is now an expectation, and the question is now what your agents can reach through MCP? For product teams, the answer that matters is real customers and the ability to learn from them.

While agents have made building fast, they haven’t accelerated learning from customers in the same way. The teams that pull ahead are the ones that fold customer insight into every stage of the AI product development life cycle instead of running it as a separate step tacked on at the end.

The Missing Half Of The AI-PDLC​

For 20 years, product development has been getting quicker. The AI-native product development life cycle (AI-PDLC) is the latest turn of that screw. Agents draft specs, generate prototypes, write code and run QA. The stages are the same, but the speeds at which they’re completed aren’t, with AI and humans now working together on those tasks. Work that used to require a sprint can now fill an afternoon.

The same is happening to research, validation and feedback loops, going from cycles measured in weeks to cycles that can happen in hours or days. Human feedback needs to be rigorous but doesn’t need to slow down development. The goal is to learn at the same pace you build so you can keep moving fast without losing sight of what you’re building and why you’re building it in the first place.​

When Research Becomes Something Agents Call On

Humans Staying In The Loop

The moments of surprise are where the product value sits, so don’t forgo the user or customer.