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Where does the conversation history live? That one decision shapes your agent's cost, privacy, portability, and UX. Here's how service-managed and client-managed storage differ — and how Microsoft Agent Framework abstracts both behind one programming model.
Move your CrewAI projects from local scripts to reliable services. Learn deployment architectures, observability patterns, and operational guardrails for production workloads.
Cut costs and latency in multi-agent workflows. Learn token budgeting, parallel task execution, caching strategies, and model tiering to make your CrewAI crews production-ready.
Trace what your agents actually did and why. Master CrewAI callbacks, event listeners, usage metrics, and log capture to diagnose failures before they reach production.
Give agents memory across runs. Master short-term context, long-term persistence, and state isolation to build workflows that learn and adapt.
Master tool design for CrewAI. Build custom tools, integrate APIs, compose tools, and optimize performance for production agents.
Build multi-agent systems with CrewAI. Learn core concepts, structure autonomous teams, and avoid common orchestration pitfalls.
My Python pipeline worked on Windows but crashed on Linux in production. Dev Containers fixed the environment mismatch — here's how I set them up.