Interesting blog by @JayaGup10 However, I think Jaya’s central claim—that incumbents are structurally incapable of winning the “context + decision” layer—overstates the constraint. There is no hard moat preventing these platforms from capturing this opportunity. They already sit at the point of execution, own the transactional graph, and control the compliance boundary. If agents are embedded directly into workflows—triggered from interfaces like Slack or Microsoft Teams but executed through these systems—then the same platforms that record what happened can also capture why it happened. In that world, systems of record evolve into systems of reasoning without requiring customers to rip and replace core infrastructure.
The argument that incumbents are disincentivized because they profit from complexity also doesn’t fully hold in a recurring-revenue model. These platforms’ installed bases are already deeply embedded; simplifying workflows via agents does not destroy that revenue—it strengthens retention and expands value per customer. In fact, a context-aware agent layer could increase, not decrease, enterprise-specific complexity by encoding nuanced policies, exceptions, and organizational behaviors. That favors incumbents who already manage customization, governance, and auditability at scale. Rather than being disrupted by this shift, they are well positioned to absorb it into their existing economic model.
Nor is there a fundamental capability gap. The tools enabling rapid innovation—LLMs, copilots, and AI-assisted code generation—are broadly accessible. Context may originate in communication layers, but there is nothing structurally preventing incumbents from ingesting that context, especially if agents become the interface between collaboration tools and enterprise systems. The winning architecture is not necessarily one that sits “above” these systems, but one that tightly couples external interfaces with native execution, allowing context to be captured at the moment of action.
It is also worth noting that the traditional advantage of startups—access to a small number of elite engineers who drive disproportionate innovation—has materially diminished. With the rise of “vibe coding,” copilots, and AI-driven development, the constraint is no longer the availability of top 20% engineering talent. Both startups and incumbents now have access to the same underlying AI tools. In that sense, incumbents like SAP or others are not inherently slower because of engineering constraints; in theory, they can move just as fast as startups. The playing field on raw development velocity has leveled significantly, shifting the competitive advantage back toward distribution, data access, and workflow ownership.
The real battleground, therefore, is not whether incumbents can win, but whether they execute with sufficient speed and clarity. Startups may innovate faster at the edges, but enterprises adopt cautiously, and control ultimately accrues to the system that closes the loop between decision, execution, and learning. If incumbents embed agents into workflows and capture decision traces natively, they retain that loop. The outcome is not predetermined: incumbents are not structurally excluded—they are simply required to evolve.
Jaya Gupta@JayaGup10
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