Anyone can build an AI agent that dazzles in a demo. An agent that runs in production, handles edge cases and delivers measurable ROI is a different story. Here's where most projects derail.
The 5 mistakes that kill ROI
- ▸Confusing demo and production: a POC that works 80% of the time fails 100% of the time in the real world.
- ▸Zero monitoring: with no logs, no evals, no alerts, you're flying blind, and you'll never know if it works.
- ▸No guardrails: an agent with no action limits and no human validation on sensitive cases is a time bomb.
- ▸Ignoring the data: an agent plugged into dirty or poorly structured data produces confidently wrong answers.
- ▸Automating before scoping ROI: automating a bad process just means hitting the wall faster.
The right reflex: start from ROI, not from the tech
Before writing a line of code, we quantify: how much time or money does this process cost today? What would the gain be? We prioritize a backlog by ROI, ship the most profitable brick first, monitor it, then iterate. Less sexy than a demo, but it holds in production.
That's our method: audit, ROI-prioritized backlog, production deployment with monitoring. No slides, systems that run.