Learning path · 4 parts
Building Agentic AI Systems
A practical path from why agents matter to building your first multi-agent pipeline: the landscape, the key design decisions, and the hands-on build.
- 1
The Agent Revolution Is Here, and Most Organizations Are Not Ready
Gartner says 40%+ of agentic AI projects will be cancelled by 2027, and only ~130 of thousands of "agentic" vendors are real. Here's what the research actually shows, and what separates the teams shipping from the ones stuck in pilot purgatory.
7 min read
- 2
State of Coding Agents: Who Actually Wins on Real-World Tasks?
Agents score 90%+ on SWE-bench. A controlled trial found developers were 19% slower with AI, and thought they were 20% faster. Why both are true.
7 min read
- 3
RAG vs. Fine-Tuning: A 2026 Decision Framework for Practitioners
Stop arguing. Here's a decision tree grounded in cost, latency, and drift.
8 min read
- 4
Building Multi-Agent Pipelines with LangGraph: A Practical Guide
LangChain now recommends the tool-based supervisor over create_supervisor. Here's the pattern to build, the three context decisions that decide if it works, and published benchmarks on which architecture actually costs less.
6 min read