Phase 1: Remote Instruction (Weeks 1–3) — Foundations of AI-First Engineering
- AI-first development practices (coding agents, MCP, real-time collaborative tools)
- Retrieval-Augmented Generation (RAG), embedding techniques, and vector database implementation
- Fast-paced project sprints emphasizing delivery under constraint
Phase 2: Onsite Training in Austin (Weeks 4–10) — Production-Scale AI Systems
- Agent architectures, evaluation frameworks, verification methods, and observability tooling (LangChain/LangSmith/LangFuse/CrewAI)
- Enterprise-grade system delivery: quality assurance, reliability engineering, and high-standard execution
- Fine-tuning techniques and deployment strategies (LoRA/QLoRA + production-level integration)
- Multi-agent approaches to modernizing legacy codebases
- Multimodal AI system development (image/video/voice processing) and scalable cloud infrastructure (AWS/Azure)






