Move AI from demo to durable production system, without burning your roadmap.
Production gets standing tickets in JIRA.
AI pilots fail in predictable patterns.
These are engineering problems.
The mistake CTOs make is treating the AI program like a research effort and staffing it with researchers.
Build the evaluation harness, the observability layer, and the deployment pipeline before changing the model. The first thirty days produce nothing the customer sees.
Move the pilot from the demo environment to production traffic on 5 to 10 percent of users. Keep it behind a feature flag.
Ramp traffic, harden the system, and produce the business case. The last phase is when the program either earns its next budget or doesn't.
Build the evaluation harness, the observability layer, and the deployment pipeline before changing the model.
Move the pilot from the demo environment to production traffic on 5 to 10 percent of users.
Ramp traffic, harden the system, and produce the business case.
If your AI pilot has been three months from production for the last nine months, the path forward is a 90-day plan with an evaluation harness, production observability, real on-call, and cost as a first-class metric.
Because the budget cycle moves in quarters. 90 days gives you one cycle to prove the program. Anything longer and the political clock runs out.
We embed for the engagement. By day 90 your team has paired with ours long enough to own it. We are not a managed service.
Yes. The plan is provider-agnostic. We have shipped on Anthropic, OpenAI, AWS Bedrock, and self-hosted Llama variants.
