Kasspian’s honest read
Workable if you own a specific painful workflow, but most AI agent startups are thin wrappers the model providers will absorb.
Who actually pays
Operations and revenue teams at small-to-mid companies who feel a manual, repetitive workflow every week — support triage, lead research, data entry, scheduling — and would rather pay than hire for it.
Riskiest assumption
That the agent works reliably enough on real, messy inputs to be trusted without a human babysitting every run. Demos are easy; production reliability is where most agents quietly fail.
Cheapest test first
Pick one workflow and run the agent manually for five real customers as a done-for-you service, charging real money. If they pay and stay, the automation is worth building.
The hard truth is that 'AI agent' is a capability, not a business. The companies that win wrap a specific, expensive-to-do-manually workflow in deep domain context, integrations, and guardrails that a generic model can't replicate. The ones that die are a clever prompt and a Stripe button, sitting one model release away from irrelevance. Your moat isn't the agent — it's the proprietary data, the integrations, and the trust you build doing a narrow job better than anyone.
Be honest about reliability. Agents are demoed at 95% and shipped at 70%, and that last gap is where customers churn, because a workflow that fails one time in five still needs a human watching it — which kills the value prop. Pick the narrowest workflow you can defend, charge enough that you can afford to make it actually work, and don't sell autonomy you can't deliver yet. The edge here is discipline, not ambition.
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