From AI Prototype to Production
From AI Prototype to Production
What it takes to turn an AI demo into a real product
Building an AI prototype has never been easier.
A few prompts, a model API, some data — and you can have something impressive running in days.
But then reality hits.
Real users. Real data. Real security requirements. Real integrations. Real costs. Real failures.
The gap between an impressive AI demo and a production-ready product is where many teams get stuck.
Join Streamlogic during AI Week SF for a practical session about what it really takes to move from:
AI prototype → production product
We'll explore:
Why AI prototypes are easy to build but difficult to productionize
Where AI products typically break when real users arrive
What needs to be engineered around the model
How to approach AI evaluation and reliability
Data, security, integrations, latency and cost
Where humans should stay in the loop
When AI should assist, recommend or actually execute
How to design AI capabilities that become part of the product rather than another feature
A practical 90-day roadmap from prototype to production
We'll also look at the difference between a simple AI feature and an AI-powered product:
AI feature:
User → prompt → model → response
AI-powered product:
Context → reasoning → rules → tools → action → human feedback → monitoring
No AI hype. No "build an agent in 20 minutes" demo.
Just a practical conversation about the engineering, product and operational decisions that turn an AI experiment into something people can actually rely on.
Who should attend?
This session is for:
Founders
CTOs and technical co-founders
Product leaders
Engineering leaders
AI/ML practitioners
Teams with an AI prototype or pilot that needs to reach production
Already have an AI prototype? Bring it.
We'll discuss what needs to happen between "it works in a demo" and "we can trust it in production."
This event is part of AI Week SF 2026.