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AI Step-by-Step

Sharing AI knowledge, practical implementation records, and more.

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Latest from AI Step-by-Step

42 recent articles
AI Step-by-Step
AI Step-by-Step
Apr 6, 2026 · Artificial Intelligence

Why Single Agents Fail: Embracing Multi‑Agent Microservice Architecture

When a single AI agent’s logic hits bottlenecks, the article explains how breaking responsibilities into bounded microservice agents, using pipelines for deterministic steps and supervisors for dynamic routing, yields clearer contracts, shared state, easier debugging, and more stable, scalable task execution.

AI ArchitectureAgent FrameworksOrchestration
0 likes · 12 min read
Why Single Agents Fail: Embracing Multi‑Agent Microservice Architecture
AI Step-by-Step
AI Step-by-Step
Apr 5, 2026 · Artificial Intelligence

How Context Engineering Powers Dynamic Business Data Assembly for LLM Agents

The article explains why relying solely on handcrafted prompts leads to hallucinations in LLM agents and presents six concrete context‑engineering practices—XML isolation, hierarchical ordering, KV caching, vector reranking, async memory compression, and minimal few‑shot examples—illustrated with a full e‑commerce refund‑handling case study.

AgentContext EngineeringKV Cache
0 likes · 10 min read
How Context Engineering Powers Dynamic Business Data Assembly for LLM Agents
AI Step-by-Step
AI Step-by-Step
Apr 3, 2026 · Artificial Intelligence

Why Building AI Agents Requires a Full System‑Engineering Harness

The article explains that simply scaling large language models cannot sustain long‑running, production‑grade AI agents, and that a dedicated Agent Harness—acting as an operating system with orchestration, memory, governance, tool execution, and feedback loops—is essential for reliable, industrial‑scale automation.

AI agentsAgent HarnessGovernance
0 likes · 9 min read
Why Building AI Agents Requires a Full System‑Engineering Harness
AI Step-by-Step
AI Step-by-Step
Apr 1, 2026 · Artificial Intelligence

When to Use Which Model in an Agent: Beyond the “Strongest Model” Myth

The article explains why routing every request to the most powerful LLM hurts cost, speed, and throughput, and presents a three‑layer task decomposition that assigns execution‑level tasks to cheap small models, intermediate tasks to mid‑size models, and high‑risk judgment tasks to large models, with concrete examples and a minimal routing strategy.

Agent DesignLLMModel routing
0 likes · 8 min read
When to Use Which Model in an Agent: Beyond the “Strongest Model” Myth
AI Step-by-Step
AI Step-by-Step
Mar 31, 2026 · Artificial Intelligence

Designing Effective Human-in-the-Loop AI Workflows: When to Automate and When to Involve Humans

The article explains how to avoid the extremes of fully automated AI or no AI at all by defining clear Human-in-the-Loop patterns, identifying irreversible, high‑responsibility, and high‑exception steps, and applying tailored approval, edit, and escalation nodes in finance, contract, and other critical business processes.

AI assistanceAI workflowHuman-in-the-Loop
0 likes · 9 min read
Designing Effective Human-in-the-Loop AI Workflows: When to Automate and When to Involve Humans
AI Step-by-Step
AI Step-by-Step
Mar 30, 2026 · Artificial Intelligence

How to Keep LLM Agents in Check with Guardrails

The article explains why LLM agents can over‑promise or execute unauthorized actions, and outlines a three‑layer guardrail system—prompt review, output validation, and tool‑action interception—plus concrete rules, examples, and test cases to ensure safe deployment.

AI safetyLLM AgentsPrompt Engineering
0 likes · 11 min read
How to Keep LLM Agents in Check with Guardrails
AI Step-by-Step
AI Step-by-Step
Mar 29, 2026 · Artificial Intelligence

How RAG Quickly Gives Your Agent Real Business Knowledge

The article explains why agents often lack business understanding, describes Retrieval‑Augmented Generation (RAG) as the fastest way to provide correct, up‑to‑date business context, outlines eight practical RAG patterns, and offers a step‑by‑step checklist for building enterprise‑ready agents.

AgentEnterprise AIGraphRAG
0 likes · 10 min read
How RAG Quickly Gives Your Agent Real Business Knowledge
AI Step-by-Step
AI Step-by-Step
Mar 28, 2026 · Artificial Intelligence

How to Evaluate Agent Performance Across Different Scenarios

The article proposes a four‑dimensional framework—task result, output structure, behavior boundary, and long‑term stability—to systematically validate AI agents in varied business contexts such as e‑commerce, manufacturing, insurance, and HR, emphasizing concrete evidence over subjective impressions.

AI AgentEvaluation FrameworkR&D Management
0 likes · 10 min read
How to Evaluate Agent Performance Across Different Scenarios
AI Step-by-Step
AI Step-by-Step
Mar 22, 2026 · Artificial Intelligence

Why Harness Engineering Is the Key to Stable Agent Loops

The article explains that while an Agent Loop can execute tasks, long‑running stability depends on a well‑designed Harness engineering layer that organizes knowledge, enforces rules, provides verification, and automates cleanup, turning a functional prototype into a reliable production system.

AI agentsAgent LoopAutomation
0 likes · 10 min read
Why Harness Engineering Is the Key to Stable Agent Loops