AGENTIC AI DEVELOPER COURSE
Production AI for backend developers
Hands-on course for experienced backend developers (3+ years). Build production RAG systems, agentic workflows, and evaluation infrastructure from scratch. Real code, real patterns, regulated industry focus. Launching March/April 2026.
Key Features
Production RAG: hybrid search, re-ranking, chunking strategies
Agentic systems: LangChain agents, tool use, multi-agent patterns
Evaluation infrastructure: RAGAS, LangSmith, regression suites
Regulated industry patterns: audit trails, compliance, data isolation
How We Work Together
A proven methodology that delivers results
Discovery
We start with understanding your business, challenges, and goals through workshops and interviews.
Design
Together we design the solution architecture and create a detailed implementation plan.
Deliver
Iterative implementation with regular demos and feedback loops to ensure alignment.
Support
Post-launch support, knowledge transfer, and ongoing optimization recommendations.
Use Cases
- Building production-grade RAG systems
- Developing agentic AI workflows
- Building evaluation and observability infrastructure
- AI in regulated industry environments
Ideal For
- Experienced backend developers (3+ years)
- AI engineers looking to level up
- Tech leads building AI-first teams
Not Ideal For
- Complete beginners to programming
- Non-technical participants
- Those seeking theory-only education
Deliverables
Deliverables
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01Complete production RAG project
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02Agentic workflow implementation
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03Full evaluation infrastructure
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04Certificate of completion
Technology Stack
Timeline
8 weeks (self-paced)
Estimated project duration
Related Case Studies
RAG Document Processing System
At Insly, I led development of a RAG (Retrieval-Augmented Generation) system that gives insurance brokers fast, context-aware answers about policy details. The system combines traditional search with vector embeddings to handle complex queries across 23 different insurance providers.
Challenge
Insurance brokers needed to quickly find relevant information across thousands of policy documents from 23 different insurers, each with unique formats and terminology.
Microservices Migration
CloudAcademy needed to migrate their content authorization service from Kotlin to Go as part of a broader standardization effort. I led this migration while ensuring zero downtime and creating new microservices following DDD patterns.
Challenge
Legacy Kotlin service had performance bottlenecks and was difficult to maintain. Team needed to standardize on Go for better consistency across microservices.
Ready to Transform Your Business?
Let's discuss how I can help you achieve your goals. The first consultation is free.