Future Forward: Turning AI Experiments into Real Products

​From POC to Production: Turning AI Experiments into Real Products Outcomes

Stop demo hell. Learn how to transform prototypes into production features that drive real user behavior. This 90-minute session blends stories, frameworks, and a practical readiness workshop.

Relevance:
Many teams can build impressive demos, but deployment, reliability, measurement, and adoption are different problems. Moving to production requires product, engineering, and organizational alignment.

What we’ll cover:
We’ll discuss product adoption signals, measurement frameworks, instrumentation and MLOps practicality, and the people/process changes needed to sustain AI features beyond the demo.

Why this approach:
This isn’t a talk about tools. It’s about changing how you frame experiments: design for stickiness, instrument for causality, and plan for robustness. We’ll show the checkpoints that distinguish a demo from a durable feature.

Speakers & format:
There will be a technical founder who built production ML systems, a product operator who led the adoption effort, an AI trainer/consultant focused on data and evaluation, AI-native non-technical co-founder who cracked the growth code and optimized retention. As well as VP of Engineering from Aspire.

Takeaways & target audience:
Expect a “Production Readiness Checklist,” templates for user adoption experiments, and guidelines for balancing iteration velocity with trust. This is for product leaders, ML engineers, founders, and operators responsible for shipping AI features.

RSVP on Linkedin: https://www.linkedin.com/events/futureforward-turningaiexperime7373703524209065984/


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