Q

Is agentic AI hype?

Some of it. Here's how to tell signal from noise.

Is agentic AI hype?

Honest answer: about half of what gets called “agentic AI” is hype, and about half is real. Here’s how to tell which is which.

The hype side

When the word “agentic” is sold to executives, here’s what’s usually missing:

  • Production deployments. Demo videos do not equal production.
  • Reliability data. “Sometimes it works, sometimes it doesn’t” gets dressed up as “exciting new model behaviors”.
  • Cost transparency. $0.40 a run sounds tiny. At 10,000 runs a day, that’s $4,000/day.
  • Failure mode clarity. Most pitches don’t tell you what happens when the agent goes wrong (which is often).
  • Real users. Beta = some users tried it. Production = users depend on it.

The signal side

Where it’s genuinely working — and where I see the pattern repeat across real enterprise settings:

  • Coding agents (Cursor, Cline, Claude Code, GitHub Copilot CLI) — for narrow, well-defined tasks like “fix this bug” or “add this test”, they save real time. Verified production tooling.
  • Customer support triage — categorisation, routing, draft replies. Not full automation; assistive layer.
  • Internal IT bots — HR FAQs, password resets, status checks. Boring but valuable.
  • Document workflows — extract, summarise, classify, route. Mature pattern.
  • Code review + PR triage — agentic, repeatable, measurable.

How to spot hype quickly

When you see a vendor pitch about agentic AI, ask:

  1. Show me a production user. Not “we have customers”; specifically: a named customer running this in production for a meaningful workload.
  2. What’s the failure rate? Real agents fail 5-20% of attempts depending on task. If they say “it just works”, they’re lying or they’re shallow.
  3. What does it cost per run? Tokens × calls × time. If they don’t know, they haven’t measured.
  4. What happens when it gets stuck? Real agents loop, time out, hallucinate. The answer should mention guard-rails, not “it doesn’t get stuck”.
  5. Who else does this? If the answer is “we’re the only ones”, it’s either genuinely innovative or a red flag.

What I think is real but oversold

  • Multi-agent systems. Real, but most teams ship a single agent first and don’t need multi-agent yet.
  • Voice agents. Latency is finally OK; UX still rough.
  • Browser agents. Genuinely useful for narrow tasks (data extraction, form filling); not yet for broad autonomy.
  • Workflow agents. Useful, but often a hand-coded workflow + small LLM calls beats an “agent”.

What I think is real and underrated

  • Specialised agents replacing horizontal SaaS. A purpose-built support agent is starting to outperform Zendesk-with-AI for narrow segments. Watch this space.
  • Agentic data pipelines. ETL agents that adapt to schema changes are quietly working.
  • Agent observability tools. Boring infrastructure, but indispensable.

My one-line answer

Agentic AI is real engineering with real wins, surrounded by a haze of marketing that’s overselling it. Treat it like any other tech: ignore the haze, look at the production deployments, measure the cost, and ship the small reliable thing first.

Don’t let hype talk you out of it. Don’t let hype talk you into it either.