AI cost doesn't explode because models are big. It explodes because patterns aren't controlled.
Here's the lean version of what every enterprise needs to know:
1) AI Agents
Agents don't run tasks — they behave. That's where cost spikes.
FinOps patterns:
Limit reasoning loops. Set cost-per-task budgets. Route to small models by default. Track every step and call.
If you can't see the agent, you can't control it.
2) RAG
RAG cost comes from retrieval, not generation.
FinOps patterns:
Reduce context size. Cache embeddings and responses. Use hybrid search for efficiency. Refresh only what's actually used.
Better retrieval means cheaper intelligence.
3) Domain Models
The hidden cost is the lifecycle — not training once.
FinOps patterns:
Only retrain when drift is proven. Standardise fine-tuning pipelines. Retire unused models. Validate ROI before any training.
Training is the expensive part. Retraining without governance is the costly habit.
The Takeaway
Agents need behavioral controls. RAG needs retrieval discipline. Domain models need lifecycle governance.
FinOps isn't about cutting cost. It's about making AI scale without surprises.