Technical guides and step-by-step instructions on building cloud-native applications, engineering thought leadership, and scaling Agentic AI.
When a single agent reviewing 23 files is too slow and too context-heavy, you need subagents. Learn how to dynamically spawn isolated child agents, run them in parallel with thread pools, handle failures gracefully, and aggregate findings — all without context pollution between files.
The harness is the execution engine of a deep agent. Learn how to build a production-ready LangChain harness with Pydantic-validated tools, multi-model fallbacks, and a middleware layer for caching, rate limiting, and audit logging — all wired into the DevPulse code review system.
Deep agents are not just smarter chatbots — they plan, delegate, persist state to files, and resume work across sessions. Learn the architectural principles that make them viable in production and build the foundations of DevPulse, a real AI-powered code review system.
Every time you open social media, there’s someone screaming about AI. Here is what it actually means for everyday jobs and how to start today without a headache.
In the previous parts, we built the brain, the hands, and optimized the engine for cost. But in an enterprise setting, “it usually works” is...
In Parts 1 and 2 , we built an agent that can think and act. But in a production environment, an agent that “loops” is an agent that “spends...