ai 51
- The Engineer Who Owns the Outcome
- CI Gates, Test Result Caches, and the Code Graph That Might Tell Us What to Test
- The One-Person Company Is a Coordination Problem
- When Productivity Turns Against Its Purpose
- When the Report Button Becomes a Competitive Weapon
- Hermes vs OpenClaw, NanoClaw, ZeroClaw, IronClaw: Agent Architecture
- Could AI Simulate Billions of Possible Human Lives?
- Codebase Memory for Coding Agents: Graft, Graphify, and codebase-memory-mcp
- Testing Small Local LLMs on Modest Hardware: A Portable Workflow
- Local Gemma with Hermes: Cheap Delegation for Rails Maintenance
- Agent 基建的三层爆发：电脑、运行时、技能方法论
- Golden Rules for Cheaper, Safer LLM Agents
- Loop Engineering and Graph Engineering: Working With LLMs
- Life Is Not Git
- Tightening Hermes Secrets with Bitwarden
- Don't Leave Good AI Workflows in Chat
- Shared AI Artifacts Aren't Private From a Hard-to-Guess URL
- Voice Control for Hermes Agent over Telegram
- The Hard Part of AI PR Review Is Not Reading the Diff
- Tightening Hermes Agent Security for Local Sensitive Work
- Securing Hermes Agent with OpenShell
- Durable codebase context for Hermes: GitNexus, LSP, AGENTS.md
- Giving Hermes Read-Only Access to GCP, AWS, and Kubernetes
- Building an AI English Conversation Practice App
- Cloud Run as a Gemini proxy for an unsupported region
- Running Hermes on a Cloud Machine as a Daily Routine Assistant
- LM Studio Local Agent Runbook: Pi and OpenCode Step by Step
- Tiny Puzzles for Testing and Debugging AI Agents
- How an LLM Coding Agent Actually Builds Software
- Using LM Studio and Gemma as a Local Engine for Coding Agents
- Building a Local Coding Agent (Codex/Claude Code Style) in Gemma
- A Local, Multi-Tenant Graph RAG System with LightRAG
- Token Efficiency for AI Coding Agents in 2026
- What Subagents Are Actually Good For in Codex
- MCP, Skills, Agents, Rulesets, and Hooks: A Practical Map
- Git Worktree for Parallel AI Development
- Intelligent Applications and the Personal OS
- I Let an AI Agent Write Code for a Week. Here's What Actually Worked.
- AI Employees: Building Your Digital Workforce
- The One-Person Company: AI as Force Multiplier
- The AI-Era Developer: From Coder to AI System Architect
- AI's Impact on the Software Development Lifecycle
- From Logic-Driven to Context-Driven Software
- Context Engineering: The New Software Engineering
- Why AI Applications Are Ecosystems, Not Software
- AI Application Architecture: LLM + Memory + Tools
- LLM Strengths and Limitations: A Practical Framework
- Generalization: Why AI Looks Smart
- What is LLM: The Nature of Language Models
- Self-Hosted Whisper: A Speech-to-Text API with Ruby and Kubernetes
- Whisper: An Open-Source Alternative to Cloud Speech-to-Text