18 个 AI 员工真实成本揭秘：订阅制 vs 自部署

Everyone talks about AI agents replacing teams. Almost nobody shows the real bill. After 3 months running an 18-role AI employee bot in production, here's the actual math — the honest version, not the marketing version.

Running 18 AI employee roles (support, data analysis, copywriting, research, ops, etc.) costs us about $10–14/month in raw API tokens at current usage levels. That's the number people quote. But it's only half the story.

Where the money actually goes

1. Token cost by model tier (the 90/10 split)

We route ~90% of requests to a fast/cheap model (DeepSeek V4 Flash class, roughly $0.15–0.20/M input tokens) and escalate only ~10% to a stronger model for complex tasks. This is the single biggest lever — using one expensive model for everything would multiply the bill 5–10x.

2. The hidden costs nobody lists

Context windows. Every role carries a system prompt + shared memory summary. Long-running conversations with large histories burn tokens on every request. This is where most silent overspend happens — not in the "per message" price.

Retries and fallbacks. When a model fails or times out, the fallback chain re-runs the request. Each retry is a fresh bill. We capped retries at 2 and added circuit breakers.

Embeddings / memory writes. If you persist conversation summaries, every write is a small but recurring cost that grows with active users.

3. The $10/month myth vs. reality

$10/month is real at our scale (light usage, single team). It scales roughly linearly with usage. At 100 active daily users doing 20 requests each, you're at a different order of magnitude — call it $80–150/month, still cheap vs. humans, but not "$10".

What actually breaks the budget

• Ignoring model routing — using one premium model for everything (4–8x cost)
• Unbounded context — never trimming conversation history (grows linearly forever)
• Retry storms — no circuit breaker, each failure chains 3+ paid retries
• Long tool-call loops — agents that keep "thinking" in circles, each step billed

The comparison that matters

The real advantage isn't "free labor" — it's elasticity. You don't hire a data analyst for one weekend project; you spin one up for the weekend and it costs cents.

AI employees are genuinely cheap — if you engineer the cost, not just the prompt. Routing, context discipline, and retry limits are worth more than any model discount. We cover the routing layer in this post, and the full architecture in the 18-roles deep dive.

What's your biggest AI agent cost surprise? Drop it in the comments — I'll cover the top ones next.

Part of the AI Employee Diaries series — practical, real-number takes on running AI agents in production.