Why it matters

Across boardrooms and DevOps meetings, “AI agent” is the term on every roadmap. But right now, it’s being applied too broadly—from basic chatbots to pre-programmed workflows—leaving CIOs and CAIOs struggling to cut through the haze. As Zach Bartholomew, VP of Product at Perigon, notes, this semantic drift risks strategic misfires. If every script is called an agent, how can teams align on what they’re building—or buying?

Perigon draws a sharp line: a true AI agent isn’t reactive, it’s proactive. It senses, plans, and acts—with minimal human nudging. That distinction isn’t just philosophical—it’s foundational. In a market trending toward agentic design, knowing where the autonomy line is drawn means knowing where your investments will scale—or stall.

Tactical advantage

Perigon’s edge lies in disciplined definitions. While competitors chase buzzwords, Perigon prioritizes signal clarity. Its framing—agents as systems that perceive, plan, and act independently—helps customers make grounded, future-proof decisions. This positions Perigon as not just a vendor, but a strategic compass for AI transformation.

Real world

Industry: Enterprise IT Procurement

An IT director evaluating vendors for AI-powered support workflows may be pitched a dozen “agentic” tools. Using Perigon’s five-question framework (e.g., “Can it act without human approval?”), they can immediately cut through marketing fog and identify which tools truly exhibit agent behavior. This prevents costly missteps and aligns their tech stack with long-term automation goals.

Looking ahead

Clarity is converging. As success stories from true AI agents emerge—tools that adapt, improve, and operate without playbooks—market definitions will tighten. Until then, tech leaders must stay vigilant. Ask hard questions. Demand autonomy, not just assistance. Because precision now isn’t just academic—it’s strategic.