Agents
Production agent systems — OpenAI Agents SDK and LangGraph orchestration, tool calling, state and memory, human approval gates, and the failure modes that break demos before they reach real users.
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Context Engineering vs Prompt Engineering for Production Agents
Context engineering is the production control plane for agents. Learn when prompts matter, what context layers to ship, and what to log before traffic.
Agent Memory for Production AI Systems
Design agent memory as governed state: what to store, what to forget, how to retrieve it, and which evals catch stale or unsafe recall.
OpenAI Agents SDK vs Pydantic AI for Production Agents
Choose OpenAI Agents SDK for OpenAI-native runs. Choose Pydantic AI when typed Python, provider flexibility, and durable approvals matter.
Google ADK vs LangGraph for Production Agents
Compare Google ADK and LangGraph for production agents: state, human approval, deployment, observability, pricing, and the decision rule.
OpenAI Agents SDK TypeScript vs Python for Production Agents
Choose TypeScript or Python for OpenAI Agents SDK by production ownership: product runtime, worker path, tracing, guardrails, handoffs, MCP, and evals.
LangChain vs LangGraph for Production Agents
Use LangChain for simple agent harnesses. Use LangGraph when production agents need durable state, retries, interrupts, approvals, and deployment.
OpenAI Agents SDK vs LangGraph for Production Agents
Choose OpenAI Agents SDK for OpenAI-native loops. Choose LangGraph when durable graph state, provider freedom, and custom control matter.
One letter, every week. Working systems — not hot takes.
Build logs, agentic engineering decisions, agent failures, evals, and what survives real users. Sent weekly, never more.