Visions Are Seldom All They Seem: Dreaming Big with Agentic AI

”I know you, I walked with you once upon a dream…”

In Sleeping Beauty, Princess Aurora sings this line as she drifts through the forest, imagining a perfect future she hasn’t lived… one that feels inevitable, effortless, and fated.

It’s a beautiful moment: wistful, romantic, and full of optimism.

From Fairy Tale to Framework

Right now, many teams are dancing with AI like it’s a Disney prince but as magical as it may seem, Agentic systems don’t work with the flick of a wand. They’re carefully crafted collaborators, fine-tuned for the goals they’re meant to serve.

In Agentic Artificial Intelligence: Harnessing AI Agents to Reinvent Business, Work, and Life, Pascal Bornet (with co-authors) lays out a practical blueprint for building these systems. One of the key frameworks is a five-level maturity model:

• Level 1 – Assisted: Basic task helpers powered by rules. Useful, but not adaptive.
• Level 2 – Augmented: Systems that offer contextual suggestions or support human decision-making.
• Level 3 – Semi-Autonomous: Agents that initiate actions based on goals and adjust to context.
• Level 4 – Autonomous: Systems that act independently across tools and workflows — with oversight.
• Level 5 – Collaborative: Human-agent ecosystems built on shared goals, transparency, and adaptability.

This model helps teams calibrate expectations. Not every product needs to hit Level 5 but every team needs to know where they are and why.

The book also highlights four core principles that shape effective agentic design:

• Autonomy with purpose: not just responding to prompts, but taking initiative aligned with goals.
• Orchestration, not automation: coordinating across people, tools, and systems to achieve outcomes.
• Human-centered design: pairing agents with context and oversight, not handing over control blindly.
• Resilience and adaptability: agents that learn and respond, not just execute static commands.

Visions Are Seldom All They Seem…

We’ve seen what happens when AI systems are treated like fairy-tale shortcuts:

• A lawyer submits a legal brief with citations hallucinated by an LLM- not because the model failed, but because the system lacked guardrails.
• Job-matching algorithms reinforce bias- because they’re optimized for clicks, not equity.
• “Automated” chatbots require constant hand-holding- because they weren’t designed as agents, just parrots.

The problem isn’t ambition. It’s failing to design for real-world complexity.

That doesn’t mean we should stop dreaming. It means we should build the vision with structure.

Designing Agentic Systems with Intention

If you’re leading an AI product team, the goal isn’t to dial back ambition; it’s to ground it in design that anticipates edge cases, escalations, and learning loops.

Ask:

• Is this agent goal-aware or just reactive?
• Does it know when to escalate?
• Is there a feedback loop to refine performance over time?
• Can it orchestrate across tools, teams, or workflows?
• Do users understand what the agent is doing — and why?

Agentic AI isn’t about replacing humans.

It’s about enabling systems that make decisions, initiate actions, and adapt in real-time all while staying aligned with human goals.

But if I know you, I know what you’ll do…

If I know good product teams, I know they’ll embrace this challenge.

They’ll push the boundaries and engineer the guardrails.

They’ll imagine bold use cases and test every failure path.

They’ll build systems that surprise and delight….not by accident, but by design.

So yes…..dream big. Imagine what a truly agentic system could unlock:

Orchestration, not just automation.

Outcomes, not just outputs.

But build it with structure.

Build it with care.

Build it the way great product teams always have…

The way you did once upon a dream.