The New AI Stack
Understanding Models, Agents, and Skills as the new computing paradigm
Showing 37-48 of 56
How AI Builds Apps 20x Faster
A first-person account of building a full-stack application with AI in 3 days instead of 60. What worked, what failed, and the real multiplier.
MCP and Skills: Two Complementary Layers of the AI Stack
MCP connects to external services. Skills encode domain expertise. Together they form the complete AI extensibility stack. Learn when to build each.
The agentskills.io Standard: Why Hermes, Claude Code, and Cursor All Speak It
How agentskills.io became the markdown-native skill format shared across Hermes, Claude Code, Cursor, and Codex — and what it means for portability.
MCP in Hermes vs MCP in Claude Code: Same Servers, Different Runtime
Model Context Protocol is identical in both runtimes. What differs is the host lifecycle. Compare filesystem, GitHub, and Postgres MCP servers side by side.
CLI-First Architecture for AI Tools
Why CLI-first beats MCP-only for AI tool design. Build tools that work everywhere, not just inside a specific AI framework.
Self-Hosting AI After Usage Limits Hit
What to do when Claude Pro limits cap out. A practical guide to running local models as fallback without losing your workflow.
Agent vs Skill vs Workflow: The Differences
A clear taxonomy of the three AI building blocks: agents, skills, and workflows, with concrete examples and when to use each.
113 Workflows That Run Your Digital Life
ClawFlows ships 113 open source automation workflows for OpenClaw — focus mode, standups, backups, security audits, and more. Here's the full overview.
The No-BS Guide to Agentic Engineering
Cut through the agentic AI hype. Practical patterns for building AI agents that actually work, from tool design to error recovery.
KAIROS: Why Persistent Memory Changes AI Skills
Persistent memory in AI agents creates entirely new categories of skills. Analyze what KAIROS-style systems mean for skill builders and the AI skills market.
Why Skills Beat Fine-Tuning: Economics of AI Customization
Fine-tuning costs $50K+ and depreciates monthly. Skills cost $500 and improve over time. The economics are clear—here's why.
The New AI Stack: Why Models, Agents, and Skills Are Reshaping Software
Understanding the three-layer AI stack (Models = Chips, Agents = OS, Skills = Apps) and why this paradigm shift matters for every developer.