Agentic AI: Cutting Through the Hype

What works in production today

• Single-purpose agents for narrow, well-scoped tasks (lead enrichment, ticket triage)
• Human-in-the-loop agents where the agent proposes, a human approves
• Agents over deterministic tools - fewer surprises than open-ended browsing

What's still flaky

• Long-horizon "autonomous" agents that plan over 50+ steps
• Multi-agent orchestrations where many agents debate
• Web-browsing agents on unstructured public sites

A sensible 2026 default

One agent, 3-7 tools, a clear success metric, and a human in the loop for the first three weeks. Graduate from there.

The honest cost picture

Agent runs are 5-20x more expensive per task than a single LLM call. Build the cost model before you scale.