Architecture decisions, trade-offs, and the code behind them.
A deep technical guide to Human-in-the-Loop (HITL) engineering patterns using LangGraph interrupts. Learn how to implement production-grade approval workflows, checkpoint-backed state management, and async human feedback loops for AI agents.
Prompt engineering is not enough for production AI agents. This deep-dive covers context engineering -- the architectural discipline of designing, curating, and dynamically managing LLM context windows at runtime with token budgets, memory hierarchies, and retrieval patterns.
A principal engineer's guide to building production-grade AI agent systems with security guardrails, governance controls, and full observability.
A strategic guide to data products. Explore 5 powerful blueprints (Curator, Matchmaker, Oracle, Guide, Gatekeeper) and the key algorithms used to build them.
A deep-dive playbook for product teams. Learn our 4-step process: diagnose with cohort analysis, investigate with funnels, understand with ML, and validate with A/B tests.
A framework for structuring your data team into two functions: an 'Insight Engine' and a 'Value Engine' to maximize business impact and ROI from your data.
A practical agent engineering guide covering AI agent architecture, frameworks, orchestration patterns, production reliability, and the systems discipline required for real deployments.
Learn how to build an AI agent CI/CD and deployment pipeline with GitHub Actions, Docker, Kubernetes, and production release discipline for agent systems.
How Temporal makes long-running AI agents recoverable through workflow history, deterministic replay, Activities, retry policy, and idempotency.
Hierarchical AI agents in CrewAI are useful only when manager-worker delegation solves a real coordination problem. Use this framework before adding `allow_delegation`.
A practical CrewAI tutorial covering your first agent, `from crewai import Agent, Task, Crew, Process`, and when to use sequential or parallel crews.
A practical CrewAI tutorial for building an autonomous agent crew for competitor analysis, covering specialist agents, orchestration, structured outputs, and report generation.