For decades, we have been conditioned to see software as a set of tools that wait for us. We click a button, the computer responds. We type a prompt, the LLM hallucinates a poem. But a fundamental shift is occurring in how we define “product,” moving away from reactive interfaces toward autonomous executors. We are entering the era of the silicon-based workforce, and for product leaders, the challenge isn’t just technical—it is deeply operational.
The transition from AI Copilots to Autonomous AI Agents is not a mere feature upgrade. It is a structural change in enterprise execution. While 2024 and 2025 were spent “chatting” with boxes, 2026 is seeing the rise of systems designed to progress work once intent is defined, continuing to act until a goal is reached without needing a human to click “run” at every step. But as we rush to deploy these agents, many organizations are hitting a wall. Why? Because they are trying to automate existing processes designed by and for humans, without reimagining the work itself.
The Agent Reality Check: Redesigning for Autonomy
In a recent Deloitte Insights report, it was noted that while a vast majority of enterprises are now testing AI agents, many implementations are failing to move past the pilot phase. The bottleneck isn’t the AI’s intelligence; it’s the architectural brittleness of the organizations they inhabit. We’ve spent years building “human-compatible” workflows. When you drop an autonomous agent into a process built for human judgment, manual sign-offs, and legacy interfaces, friction is inevitable.
Leading organizations are realizing that success requires building agent-compatible architectures. This means moving toward microservice-based agent structures and robust orchestration frameworks. As CTO Magazine points out, the shift from copilots to agents redefines execution processes and the distribution of risk. If an agent at NVIDIA or Lenovo (both of whom are doubling down on AI inferencing servers this year) completes a complex workflow independently, who owns the accountability? The product manager who defined the prompt, the engineer who built the guardrails, or the executive who approved the autonomous policy?
Beyond the Hype: The Threat of Agentic Enshittification
We must also guard against the “Rot Economy.” Digital historian Cory Doctorow famously coined the term “Enshittification” to describe the lifecycle of digital platforms that eventually sacrifice user value for shareholder extraction. As we deploy agents at scale, there is a risk of a new kind of decay. When agents interact primarily with other agents—AI-generated content being consumed by AI-driven scrapers to inform AI-led marketing decisions—we risk creating a closed-loop system that loses its connection to real human needs.
For product leaders, the antidote is distinctiveness and empathy. At easyJet, where I spent years leading digital product, the focus was never on technology for technology’s sake; it was about the traveler’s experience. If an agentic system in a travel app can autonomously rebook a flight, handle a refund, and book a hotel during a strike, that is immense value. But if that agent is designed primarily to obscure refund buttons and upsell useless insurance, we’ve just automated enshittification. We must ask: is the agent solving a user problem, or just lowering the cost of being mediocre?
The Workforce Paradox: Management as Product Strategy
As we integrate these “silicon teammates,” the role of the Product Manager is shifting toward that of a Workforce Orchestrator. Zapier’s 2026 survey reveals that 84% of enterprises plan to boost agent investment, yet the most successful ones are those keeping a “human-in-the-loop” approach. This isn’t about micromanagement; it’s about governance.
- Outcome-Based Intent: Stop defining tasks; start defining outcomes. Agents need objectives and constraints, not step-by-step instructions.
- Observability is Strategy: Documentation and “product tea” sessions won’t cut it. We need real-time dashboards for agentic behavior to ensure they haven’t drifted into unintended territories.
- Cross-Functional Autonomy: The “Product Trio” (Product, Design, Engineering) must now include AI Governance. The speed of agentic execution means mistakes happen at scale and at speed.
Just as the transition from “dumb phones” to “smartphones” during my time at Nokia caught many legacy players off guard, the move to agentic systems will leave behind those who treat AI as a veneer. Organizations like Salesforce and ServiceNow are already embedding autonomous agents into the very core of their platforms, moving away from simple chatbots to proactive assistants that manage entire service tickets without human intervention.
The long view of technology cycles tells us that every boom is followed by a “sobriety test.” In 2026, that test is pragmatic utility. If you are a CEO or a CDO, your objective is no longer to “ship AI.” It is to redesign your operating model so that AI agents can actually work. The organizations that thrive will be those that view agents not as tools to be wielded, but as a workforce to be led, guided by a steadfast commitment to creating genuine user value rather than just digital noise.
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