Intelligence from frontier models is now a commodity. The real value comes from Forward Deployed Engineers (FDEs) who customize and apply this general intelligence to a company's specific, unique workflows, creating a competitive edge through superior deployment.

While AI models get the headlines, they are becoming commodities. The true competitive advantage lies in building a custom "harness"—the surrounding application, data integrations, and specialized tools that direct the model's power to solve a specific user problem effectively.

Investing heavily in building custom AI agents is risky. The emergence of platforms like OpenAI's Workspace Agents, which allow non-technical users to build powerful agents with a few clicks, can render months of complex, custom development work obsolete.

While it's tempting to build custom AI sales agents, the rapid pace of innovation means any internal solution will likely become obsolete in months. Unless you are a company like Vercel with dedicated engineers passionate about the problem, it's far better to buy an off-the-shelf tool.

The rise of AI agents introduces a new strategic layer for marketers. They must now decide when to buy out-of-the-box agents, use workflow tools for assembly, or custom-build agents for niche, proprietary tasks. This "build vs. buy" competency is becoming a key marketing differentiator.

Companies will adopt a hybrid "build vs. buy" approach. They will use AI agents to build bespoke, simple software "screwdrivers" for specific workflows on the fly, eliminating many niche SaaS tools. However, they will continue to "rent" large, foundational platforms like ERPs and CRMs, which serve as heavy-duty "trucks."

Microsoft's CTO observes that the most compelling agent-based startups are not building unique infrastructure. Instead, they are leveraging existing platforms to solve a specific user problem they understand better than anyone else. This signals a market shift from infrastructure-level to application-level innovation.

As foundational AI models become commoditized, differentiation will come from building specialized platforms for specific business functions like sales or marketing. This involves deep integration with industry-specific data, workflows, and context, making the 'intelligence layer' the key competitive advantage.

AI agents are simply 'context and actions.' To prevent hallucination and failure, they must be grounded in rich context. This is best provided by a knowledge graph built from the unique data and metadata collected across a platform, creating a powerful, defensible moat.