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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
May 15, 2026 · Artificial Intelligence

AI‑First Architecture Constraints: Tool Limits, Refactor Triggers, and Context

The article examines six practical challenges of AI‑First development—oversized tool libraries, when to trigger refactoring, propagating newly extracted methods, duplicate code from parallel sub‑agents, context aging, and the lack of a unified framework—while presenting concrete solutions such as three‑layer loading, sub‑agent isolation, semantic search, consolidation agents, persistent context files, and adaptive compression strategies.

AI agentsContext ManagementRefactoring
0 likes · 24 min read
AI‑First Architecture Constraints: Tool Limits, Refactor Triggers, and Context
AI Step-by-Step
AI Step-by-Step
May 13, 2026 · R&D Management

Agentic Development Cycle: Real‑Time Validation with AI Agents

The AC/DC framework reimagines software development by moving verification from post‑commit CI pipelines to the moment code is generated, letting AI agents write, check, and fix code in a self‑correcting loop, while redefining human engineer responsibilities.

AI agentsTechnical debtautomation
0 likes · 14 min read
Agentic Development Cycle: Real‑Time Validation with AI Agents
AI Step-by-Step
AI Step-by-Step
May 11, 2026 · R&D Management

Why AI‑Driven Development Must Be Spec‑Driven to Reach Production

The article explains how Spec‑Driven Development (SDD) transforms AI‑generated code from risky demos into production‑ready features by defining executable specifications, enforcing review, injecting context, and automating verification, illustrated with a concrete order‑export example.

AI codingSpec-Driven Developmentautomation
0 likes · 17 min read
Why AI‑Driven Development Must Be Spec‑Driven to Reach Production
AI Step-by-Step
AI Step-by-Step
May 8, 2026 · Artificial Intelligence

How LLM Wiki Transforms Personal Agent Knowledge Management

LLM Wiki, proposed by Andrej Karpathy, replaces repetitive RAG retrieval for personal agents with a three‑layer markdown‑based knowledge base that separates raw sources, curated wiki pages, and schema constraints, enabling durable, auditable memory, structured updates, health checks, and a hybrid Wiki‑RAG workflow.

AIKnowledge BaseLLM Wiki
0 likes · 17 min read
How LLM Wiki Transforms Personal Agent Knowledge Management
AI Step-by-Step
AI Step-by-Step
May 7, 2026 · Artificial Intelligence

How Claude Code’s Coordinator‑Worker Architecture Enables Native Concurrency

Claude Code tackles the bottleneck of overloaded main sessions in complex code tasks by splitting work into a Coordinator that keeps the overall goal and independent Workers that handle research, implementation, testing, and review in isolated contexts, returning only essential evidence for synthesis.

AI concurrencyAgent ArchitectureClaude Code
0 likes · 13 min read
How Claude Code’s Coordinator‑Worker Architecture Enables Native Concurrency
AI Step-by-Step
AI Step-by-Step
May 5, 2026 · Product Management

How to Convert Rough PRDs into Structured AI‑First Specifications

The article explains why feeding vague PRDs to AI coding tools leads to unstable code, and presents a step‑by‑step workflow that rewrites rough requirements into a structured AI‑First PRD covering goals, boundaries, states, acceptance criteria, and feasibility checks before implementation.

AIPRDproduct-management
0 likes · 15 min read
How to Convert Rough PRDs into Structured AI‑First Specifications
AI Step-by-Step
AI Step-by-Step
May 4, 2026 · R&D Management

How to Give AI Coding Agents a Global Constitution

The article explains why teams using multiple AI coding agents need a top‑level CONSTITUTION.md to capture stable engineering principles, decision hierarchy, autonomy boundaries, quality gates, and revision processes, and shows how to structure, write, and propagate it across tool‑specific files.

AI agentsCONSTITUTION.mdR&D Management
0 likes · 16 min read
How to Give AI Coding Agents a Global Constitution
AI Step-by-Step
AI Step-by-Step
May 1, 2026 · Artificial Intelligence

How Claude Code’s Agentic Loop Works: Four Layers from QueryEngine to UI

The article breaks down Claude Code’s persistent agentic loop into four layers—QueryEngine, Tool System, Permission/Hook, and React + Ink—explaining how each turn gathers context, makes model decisions, executes actions, verifies results, handles errors, and renders a terminal UI.

Agentic LoopClaude CodeError Handling
0 likes · 14 min read
How Claude Code’s Agentic Loop Works: Four Layers from QueryEngine to UI
AI Step-by-Step
AI Step-by-Step
Apr 29, 2026 · Artificial Intelligence

Implementing a Harness in Hermes: Tool Registry, Plugin System, and Context Engine

The article dissects Hermes’s extension layer, showing how the Tool Registry converts functions into runtime assets, how AST‑based auto‑discovery and availability checks keep tool lists accurate, and how the unified dispatch, Plugin System, Hook System, and replaceable Context Engine together form a robust, governable agent platform.

Agent FrameworkAuto-discoveryContext Engine
0 likes · 20 min read
Implementing a Harness in Hermes: Tool Registry, Plugin System, and Context Engine