Guides
Comparison guides and decision frameworks for AI automation. Each one leads with a verdict, then shows the numbers, the tradeoffs and the edge cases that change the answer.
Automate YouTube Shorts end-to-end: pick segments, write hooks with Claude, build CapCut drafts via CLI. Open-source pipeline + my paid blueprint.
Run Claude Code on a local LLM via ANTHROPIC_BASE_URL. Native Anthropic endpoints for Ollama, LM Studio, llama.cpp, vLLM. 32K context floor.
How to choose an LLM for production workloads. 7 selection criteria, a decision tree, an evaluation process, and a requirements checklist from real deployments. Download the free AI Automation Checklist.
Self-hosted LLM vs Claude API in September 2026: current GPU and token prices, recomputed break-even, and when the API still wins.
LLM API comparison for production, September 2026: Claude, GPT, Gemini, Mistral on cost, EU data residency, uptime SLAs and lock-in for IT leaders.
Compare n8n executions, Zapier tasks, and Make credits on the same workflow. See how loops, retries, and self-hosting change the real bill.
Claude vs ChatGPT for developers in 2026. Chat, CLI, IDE, and API compared by a practitioner running ten agents in production. Download the free AI Automation Checklist.
LLM API cost comparison for 2026. Model your real workload costs with prompt caching, output tokens, reasoning, and batch API factored in. Download the free AI Automation Checklist.
Claude API vs OpenAI API, September 2026: prices converged, caching at parity. EU residency and procurement decide. Verdict for IT leaders.
Should you build a custom AI agent or buy off-the-shelf? Cost analysis, hybrid approach, and when to hire a freelancer vs building in-house. Download the free AI Automation Checklist.
Production AI agent architecture patterns: router-planner-executor, ReAct, Reflexion, tool design, state, and testing. The playbook for agents that survive real traffic.
Hetzner vs AWS for AI workloads in 2026: where each wins, price-per-spec comparison, GPU reality, egress traps, and a realistic decision framework. Download the free AI Automation Checklist.
Your agents answer from whatever the retriever finds, and too often that is last quarter's truth. I build the context layer they answer and act from: a temporal knowledge graph that keeps every fact with its source and the time it held, reads with each person's own permissions, and writes nothing without a person's approval. On your own tenant, billed by the hour, step by step.
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