Tag: AI Agent
All the articles with the tag "AI Agent".
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Loop Engineering: From Writing Prompts to Designing Loops That Run Agents for You
The "Loop Engineering" term Addy Osmani popularized in June isn't a replacement for prompt engineering — it's about swapping you out as "the person who hits enter" and turning you into "the person who designs the loop". Walks through the five components plus a state, and the three debts Osmani is really worth remembering for (verification debt / comprehension debt / cognitive surrender) — and along the way, why I disagree with him placing loop above the harness.
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Prompt, Context, Harness, Agentic: The Four Nested Layers of LLM Apps — and Knowing Which One You're Stuck In
Prompt engineer, context engineer, harness engineer, agentic engineer — these aren't four competing job titles. They're nested layers of concern, from a single instruction to an entire autonomous system. Understand how the four layers relate, and you'll know exactly which one you're optimizing every time you get stuck.
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Letting Claude Code Touch My Real-Money Trading Code: The Lines I Refused to Cross
I've spent 10 months using Claude Code on a real-money futures trading project. This is an honest retrospective: the AI never touched the money directly (I'm not that bold), but it did write code on the critical order/stop-loss/close-position paths. Here are the boundaries I held, where AI genuinely helped, and the moments I had to take over.
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AI Tooling Supply Chain Security Checklist: 8 Defense Principles Distilled from the Vercel and Nx Console Incidents
Neither the Vercel breach nor the Nx Console incident was a protocol vulnerability—both were credential governance failures. This post distills these two AI tooling supply chain attacks into 8 defense principles plus a 1-hour audit checklist, covering OAuth least privilege, secret tiering, managed device isolation, and IDE extension credential isolation—a security playbook indie developers and small teams can act on immediately.
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Claude Code Multi-Agent Orchestration Plugins Compared 2026: Choosing Between Ruflo, Maestro, Claude Octopus, and Codex Peer Review
A head-to-head comparison of multi-agent orchestration plugins: Ruflo calls itself the "leading Claude orchestration platform" but underdelivers in execution, Maestro stays lightweight, Claude Octopus runs reviews across 8 models in parallel, and Codex Peer Review gates merges behind three sequential reviewers. From architecture to measured token costs — a decision framework for indie developers.
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Claude Code Workflow Plugins Compared (2026): Superpowers, Shipyard, Ralph Loop, Maestro, or Karpathy CLAUDE.md?
The Claude Code ecosystem has splintered into 100+ plugins as of May. This post zooms in on the "workflow methodology" category—Superpowers, Shipyard, Ralph Loop, Maestro, and Karpathy CLAUDE.md. Design philosophy, context overhead, fit, and combination strategies, plus a decision tree for indie developers.
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AI Agent Persistent Memory Architectures Compared: File-Based vs Vector Retrieval, Benchmarked with a blog-preflight Subagent
I hooked the same Subagent up to both Claude Code's built-in file-based memory and mem0's vector retrieval, then compared token cost, recall quality, and cross-session learning. The result: concrete thresholds for which approach fits which data scale, plus a look at procedural memory—the weakest but most promising direction.
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Claude Code's Five-Layer Architecture Explained: How MCP, Skills, Agent, Subagents, and Agent Teams Work Together
Anthropic officially describes Claude Code as a five-layer architecture: MCP for connectivity, Skills for task knowledge, Agent as the main worker, Subagents for parallel isolation, and Agent Teams for coordination. This post breaks down each layer's role and collaboration patterns, with a real-world example from my blog's blog-preflight Skill showing three layers working together.