I am a consultant. My job is to understand my clients’ needs and help them build products to meet those needs. Over the last 3 years, the vast majority of my projects have been applied AI projects.
The truth is that AI projects often struggle to live up to expectations when they hit production. Poor performance, token costs, inverted metrics, and frustrated users are the reality of most AI deployments.
Our industry focuses too much on hype-driven architectures and flashy demos. Most of us ignore the boring part: cost guardrails, evaluations, and design choices that survive the next model release. And above all, knowing when to reach for AI and when not to.
On May 21, Andrei and I are running the second webinar in Jeavio’s series on AI. The focus is running AI workloads in production.
We will cover:
– Understanding and managing token costs
– Mental models for effective AI adoption
– Making architecture decisions when underlying model capabilities move so fast
– Engineering implications when AI writes most of the code
Link to sign up is in the comments. We will be posting the recording of the first webinar shortly. Please DM me if you have any questions.
