How to Choose an Open-Source AI Agent Framework for Production
Evaluate open-source agent frameworks with a real workflow: state, tool contracts, testing, recovery, deployment, licensing, and maintenance ownership.
The build journal
From an AI idea to a working product.
Implementation guides for teams building agents, connecting business systems, and making software dependable enough for everyday work.
Human Approval, Retries, and Recovery: Designing Reliable Agent Workflows
Build approval and recovery into agent workflows with explicit action proposals, version checks, idempotency, durable status, and exception handling.
Single Agent vs Multi-Agent Systems: When Is the Extra Complexity Worth It?
Decide whether multiple agents improve a workflow by examining task independence, shared state, handoffs, verification, latency, and total cost.
AI Agent Memory: What to Store, What to Forget, and What Can Go Wrong
Separate agent conversation history, durable task state, and reusable memory, with practical rules for provenance, expiration, access, and correction.
MCP for Business Applications: Connecting Agents to Tools and APIs
Understand what MCP standardizes, what your business integration still needs, and how to expose useful agent tools with identity, validation, and clear errors.
How to Evaluate an AI Agent Before Giving It Real Work
Create an agent evaluation suite with realistic tasks, observable outcomes, failure cases, repeated runs, and release criteria matched to the workflow.
Context Engineering for AI Agents: What They Need Beyond a Good Prompt
Design an agent's context around task state, current evidence, tool results, and provenance, with a practical example of conflicting business policies.
How Much Does an AI Agent Cost? Development, Integrations, and Ongoing Operations
Estimate an AI agent's full cost with a transparent example covering engineering, model usage, retries, infrastructure, maintenance, and human review.
Why AI Agents Work in Demos and Fail in Production
Understand the gap between an agent demo and a dependable service: tool failures, permissions, state, evaluation, operating costs, and recovery.
AI Agent or Automated Workflow? How to Choose for Your Business Process
Choose between a fixed workflow, an LLM-assisted step, and an AI agent using a support-request example, failure cases, and a practical decision checklist.