Guides
Playbooks
Field notes for shipping with LLMs. English primary; Chinese pages under each card labeled 中文.
A lean AI tool stack for solopreneurs: writing, research, coding, publishing, and cost control — with selection criteria and a no-hype setup path.
What tokens are, how counting differs by model family, why estimators disagree, and how to budget LLM usage without treating vendor docs as mythology.
A 2026-ready AI SEO workflow: intent mapping, outline freeze, draft assist, on-page packs, internal links, and measurement — without black-hat tricks or fake test claims.
How to write system prompts for research agents: roles, tool use, citation rules, stop conditions, and anti-hallucination constraints that hold up in production.
Design a practical AI content pipeline: intake, outline freeze, section drafts, fact audit, SEO pack, publish — with tools, owners, and SLAs.
A practical comparison framework for ChatGPT, Claude, and Gemini on writing tasks — strengths, failure modes, and when to route work — without fake bake-off scores.
A practical playbook for capping LLM spend: token budgets, model routing, caching, retry policy, and monthly forecasting without a finance PhD.
Reusable prompt templates for briefs, outlines, drafts, SEO packs, and edits — designed for content teams that need consistency, not one-off chat magic.
How to write and maintain system prompts for product features: contracts, tool use, refusals, and change control.
A decision checklist for picking an AI coding assistant: privacy, IDE fit, context, pricing, and failure modes — skip the fake bake-offs.
A concrete pipeline for briefs → drafts → edits → publish using LLMs as assistants, with human gates where quality and liability live.
A practical method to forecast token spend: count inputs, model rates, retries, and caching — so your AI feature does not surprise finance.
A field checklist for writing prompts that hold up in production — roles, constraints, output schemas, and failure modes — without hype.
中文
2026 可用的 AI SEO 流程：意图映射、大纲冻结、辅助起草、On-page 打包、内链与更新节奏——不做黑帽，不编造实测。
面向内容团队的可复制 Prompt 模板：Brief 扩写、大纲、分段起草、事实核对与 SEO 打包，强调人工把关与可复用。
给小团队的 LLM 费用控制手册：计量、预算、模型路由、压缩上下文、重试策略与月度估算，避免账单失控。
从选题到发布的可复用 AI 辅助流程：Brief、大纲、草稿、事实核对与 SEO 打包，强调人工把关。
面向实操者的 Prompt 清理方法与 Token/费用估算步骤，避免上线后账单失控。