The evolution of 'agentic AI' extends beyond content generation to automating the connective tissue of business operations. Its future value is in initiating workflows that span departments, such as kickstarting creative briefs for marketing, creating product backlogs from feedback, and generating service tickets, streamlining operational handoffs.

To build a durable business on top of foundation models, go beyond a simple API call. Gamma creates a moat by deeply owning an entire workflow (visual communication) and orchestrating over 20 different specialized AI models, each chosen for a specific sub-task in the user journey.

Simply offering the latest model is no longer a competitive advantage. True value is created in the system built around the model—the system prompts, tools, and overall scaffolding. This 'harness' is what optimizes a model's performance for specific tasks and delivers a superior user experience.

Harvey's Forward Deployed Engineering team isn't just for building custom solutions. It's a strategic product discovery tool. By embedding engineers with large clients who have undefined GenAI needs, Harvey identifies and builds the next set of platform features, effectively using customer problems to pave its future roadmap.

While current AI tools focus on individual productivity (e.g., coding faster), the real breakthrough will come from systems that improve organizational productivity. The next wave of AI will focus on how large teams of humans and AI agents coordinate on complex projects, a fundamentally different challenge than simply making one person faster.

Unlike coding with its verifiable unit tests, complex legal work lacks a binary success metric. Harvey addresses this reinforcement learning challenge by treating senior partner feedback and edits as the "reward function," mirroring how quality is judged in the real world. The ultimate verification is long-term success, like a merger avoiding future litigation.

A new ecosystem is emerging where law firms are not just end-users of Harvey's AI but also channel partners. They are leveraging their expertise to help their in-house legal clients adopt and implement the technology, creating a new, high-margin line of business for themselves as tech consultants and implementers.

The transition from AI as a productivity tool (co-pilot) to an autonomous agent integrated into team workflows represents a quantum leap in value creation. This shift from efficiency enhancement to completing material tasks independently is where massive revenue opportunities lie.

Instead of building a single-purpose application (first-order thinking), successful AI product strategy involves creating platforms that enable users to build their own solutions (second-order thinking). This approach targets a much larger opportunity by empowering users to create custom workflows.