From Demo to Deployment: AI Implementation Framework

From Demo to Deployment: AI Implementation Framework

Transform your AI initiatives from unreliable demos to trusted production systems

Stop explaining why your AI initiatives fail in production. Start building solutions that work when it matters.

Are you tired of AI systems that look impressive in demos but fall apart in production? Of being woken up by alerts at 3 AM when your AI behaves unexpectedly? Of explaining to executives why that promising AI project still isn’t delivering business value?

I help engineering leaders and their teams transform AI prototypes into reliable, production-grade systems through comprehensive MLOps practices that most AI training ignores. This isn’t about building quick demos—it’s about creating AI solutions your entire organization can trust.

What Makes This Workshop Different

Most AI training teaches you to build proof-of-concept systems that look good in demos but crumble under real-world conditions. They treat AI as “just another API” rather than the complex ML systems they truly are.

This 2-day hands-on workshop focuses on what others ignore: rigorous testing, evaluation frameworks, and reliability practices that ensure your AI works in production, not just in presentations.

What Your Team Will Master:

• Production-Ready Evaluation Frameworks – Build comprehensive test suites that expose AI weaknesses before deployment, not after
• Prompt A/B Testing Methodologies – Apply data-driven approaches to optimize prompts with measurable improvements
• Systematic AI Reliability Practices – Implement monitoring that catches issues before they impact users or wake you up at night
• Real-World MLOps for AI Systems – Apply proven ML engineering practices to LLMs, RAG implementations, and AI agents
• Failure Prevention Strategies – Identify and mitigate the most common failure modes of production AI before they occur

Transform Your Team’s Capabilities:

From Frustration to Confidence:

Before: Explaining repeated AI failures to skeptical executives

After: Showcasing reliable AI systems that consistently meet business expectations

From Crisis to Control:

Before: Constant firefighting and late-night alerts for unpredictable AI behavior

After: Systematic evaluation and monitoring that prevents problems before they reach production

From Wasted Resources to Measurable Results:

Before: Endless development cycles with no production deployment

After: Clear implementation pathways with measurable success metrics aligned to business outcomes

Why Engineering Leaders Trust This Approach:

I bring 5 years of MLOps experience and 4 years working on data engineering teams to this workshop. With 14 years of total programming experience and 5 years teaching programming workshops, I understand both the technical challenges and how to effectively transfer these skills to your team.

Unlike theoretical AI courses, this workshop is intensely practical. Your team will work in small groups on hands-on exercises that mirror real-world implementation challenges. They’ll build evaluation frameworks, testing methodologies, and monitoring systems they can immediately apply to your organization’s AI initiatives.

What Workshops Participants Say:

Limited Availability

This 2-day online workshop is limited to 20 participants to ensure personalized attention and maximum learning effectiveness. Each session includes:

• Comprehensive hands-on exercises in small groups
• Real-world testing and evaluation frameworks you can adapt for your systems
• Systematic approach to production-grade AI implementation
• Immediate application of concepts to your specific AI challenges
• Post-workshop implementation guidance

Don’t waste another quarter explaining AI failures or rebuilding the same system repeatedly. Equip your team with the skills to build AI that works in production, not just in demos.

Want to see how this can work for your team?