AI Agent Guides, Automation Comparisons & Workflow Playbooks
For non-technical professionals, solopreneurs, and lean teams who want to offload digital busywork with AI.
- 301 Research Run Kimi K3 Locally: The 0.8 Token Reality
Run Kimi K3 locally on CPU with ~55GB RAM? The binary exists, its license grants no permission to use it, and decode runs at 0.8 tokens per second.
- 302 Guide What Compound Engineering Actually Compounds
Compound engineering makes each unit of agent work easier than the last. What Every's 23,900-star plugin does, how the loop closes, and where it breaks.
- 303 Research AI Agent Sandbox: What It Is and Isn't
An AI agent sandbox is where your agent's code actually runs. How Cloudflare Computer builds one on Durable Objects, what its benchmarks show, and the limits.
- 304 Guide Running Claude Code Agents in Parallel
Running Claude Code parallel agents needs worktrees for isolation and status you can trust. How git worktrees and the new macOS app diri handle both.
- 305 Research LoopX: A Control Plane for Agent Loops
LoopX is a local state kernel that keeps objectives, gates, evidence and quota stable while Codex or Claude Code runs. What it does, and what it refuses to do.
- 306 Comparison AI Copilot vs AI Agent for Recurring Work
Compare AI copilots, agents, fixed automation, and hybrid workflows to decide what recurring work to delegate and where people should stay involved.
- 307 Guide Grok 4.5 Agent Workflows: Tools and Fallbacks
Grok 4.5 agent workflows explained: tool approval, reasoning effort, context compaction, prompt caching, the 200K price step, and region-aware fallbacks.
- 308 Guide What an AI SEO Agent Can and Cannot Run
An AI SEO agent can diagnose indexing, map redirects, and fix code. It cannot invent your search volume. What qiaomu-seo gets right about the boundary.
- 309 Research AI Agent Evaluation: The 56% Pass Ceiling
AI agent evaluation on 107 real business tasks: the best model passes 56.1%, and the same model shifts 7 points depending on which harness runs it.
- 310 Guide Context Engineering for AI Agents, Beyond RAG
Context engineering for AI agents is shifting from prompt stuffing to ontologies. What AWS open sourced, how it differs from RAG, and when it is overkill.