
Let's dig into your AI architecture decisions.
In 30 minutes, we'll cover:
AGENT ARCHITECTURE
- Single agent vs multi-agent design
- State management and memory
- LangGraph patterns that work in production
TOOL & FRAMEWORK SELECTION
- LangGraph vs LangChain vs CrewAI — when to use what
- LLM selection (Claude, GPT-4, Gemini, open source)
- Vector databases for your use case
PRACTICAL DECISIONS
- Build vs buy for AI infrastructure
- Where to start vs what to defer
- Common pitfalls I've seen (and made)
I'll share what I've learned from building AI systems and my certifications in LangGraph, Claude Code, and CrewAI.
Best for: CTOs, founders, and senior engineers making AI architecture decisions.
You'll leave with clear next steps, not just theory.