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.
June 7, 2026 · 4 minThe voice AI that pays back for a small business is narrow and boring: after-hours triage, booking, order status. Here is what ships and what to skip.
GuideAgent Memory From Your Task Manager May 30, 2026 · 5 minTurn your task manager into agent memory: an adapter-not-migration CLI and MCP server with hybrid RRF retrieval over TickTick or an Obsidian vault.
Pinecone vs RunPod for vector search: managed serverless against self-hosted Qdrant on a rented pod. Sep 2026 prices, break-even, residency.
Pinecone vs RunPod: a vector database and a GPU cloud, not rivals. Sep 2026 prices, EU regions, and when Qdrant on RunPod replaces Pinecone.
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.
Compare self-hosted LLM and API costs at equal quality: workload, peak load, operations and setup effort. Build a budget brief before buying GPUs.
Compare LLM API reliability by model, endpoint and service tier. Check SLA coverage, failed jobs, safe fallback and the owner who accepts production.
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.
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.
With your consent I use PostHog (EU) for usage analytics and masked session recordings to find problems. Text and input values are hidden. See the privacy policy.