AI-DLC: Frequently Asked Questions
Frequently asked questions about AI-DLC — harnesses, compaction-survivability, stage routing, knowledge intake, installation and multi-repository layouts.
Read MoreAI-DLC: AI-Driven Development Life Cycle
AI-DLC (AI-Driven Development Life Cycle) is a methodology and deterministic engine that turns AI coding assistants into structured, auditable software-delivery workflows from one harness-neutral core.
Read MoreAI Artifact Report Cards: Grading What AI Builds
A high-level vision for a portal that grades AI-generated artifacts against reference context using configurable evaluation policies, and emits a report card with per-category scores and a thin human-review loop.
Read MoreHermes Agent: From Zero to Expert
A complete learning path for Hermes Agent — architecture, each component deep-dived from beginner to expert, and a working Telegram personal assistant bot with voice calls.
Read MoreSpec-Driven Development With AI
Spec-Driven Development (SDD) is a 2026 software engineering workflow where structured specifications become the source of truth and AI agents derive implementation, tests and documentation from them.
Read MoreLangChain Deep Agents
Comprehensive reference for building long-running, multi-step AI agents using LangChain’s Deep Agents SDK — covering planning, file systems, subagents, memory, skills, sandboxes, backends, context management, human-in-the-loop, and deployment.
Read MoreClaude Agent SDK
Reference for building production AI agents with the Claude Agent SDK, the agent loop, sessions, tools, MCP, hooks, subagents, permissions, context management, structured output, streaming and deployment.
Read MoreGitHub Copilot Notes.
GitHub Copilot and customization instructions together unlocks a structured, repeatable way to guide AI assistance across your codebase—covering custom instructions, reusable prompt files, agent mode and extensible skills for end-to-end AI-driven workflows.
Read MoreLangchain Gen-AI Patterns
Reusable design patterns and best practices for building robust, efficient and scalable LLM applications, covering retrieval, memory, agents, RAG and orchestration.
Read More