Most “AI” in products today is still a fancy chat box. You ask, it answers. Useful, but it doesn’t change how work gets done.
Agentic AI is different: agents don’t just respond – they reason, use tools, and take action in your systems. For product leaders, that’s the shift from “AI feature” to “AI as the operating system” of how teams work.
From reactive to proactive
In support and ops, the old pattern is: ticket arrives → human reads → human does something. Agentic systems can interpret the ticket, decide what’s needed, call the right APIs, loop in the right people, and only escalate when it’s stuck. The human stays in the loop where it matters instead of doing every step.
For product, that means we’re not just shipping a better search or a summariser. We’re designing workflows where AI is a first-class actor: it has goals, tools, and guardrails. That’s a different product discipline – more systems design than feature design.
What I’m watching
- Orchestration over single models – chaining reasoning, tools, and human checks.
- Clear boundaries – what the agent can do without approval vs. where it must ask.
- Observability – understanding why an agent did what it did, for trust and improvement.
I’ll share more as we build this at scale in Jira Service Management. If you’re thinking about agentic AI in your product, I’d love to hear how you’re framing it.