A practitioner's guide to domain-specific RAG knowledge bases across finance, tech, and consulting: the five-dimension framework, chunking that lifted retrieval accuracy, embedding selection, metadata design, and the maintenance cycle that keeps answers true after launch.
Fluent answers that cannot be traced back to a provision are unusable. This build grounds generation in a fixed corpus: 8.5M words, a Markdown-plus-JSON dual layer, an 8-step retrieval workflow, and a real case run end to end.
One canonical knowledge store any MCP-aware AI tool can query: three independently replaceable tiers, eight industry templates, and per-person access you revoke with a single command. Built so the knowledge stays with the business when the person leaves.
An AI agent for business forgets rules that live only in chat. Put role, rules, and job steps in one folder—and copy a build prompt that interviews you and sets it up in any agent.
84 articles, 225 views, 0 likes. A day spent building the distribution layer that publishing alone never provides: four reusable systems for repurposing, internal linking, and resurfacing old work, plus the prompts behind each one.
Your agent isn't forgetful — it was never given a role. Define it the way you would write a job description: identity, expertise, working process, output standard, hard limits, in one file every tool loads. Portable across models, and no framework update can break it.
Building a website with AI is no longer about picking a tool, it is about picking an input method. Seven ways in, compared on cost, output quality, and where each one breaks: prompt, screenshot, Figma, video, sketch, URL, and design system.
Expertise is not extra facts. It is knowing which fact applies and where to look first — the layer no one-line role instruction has ever managed to install. These 98 packs load it into an ai agent for business from official occupational data.
When I rebuild one with AI agents, you get the write-up — including the parts that didn't work. No weekly roundup, no "5 tools you need."
A practitioner's guide to domain-specific RAG knowledge bases across finance, tech, and consulting: the five-dimension framework, chunking that lifted retrieval accuracy, embedding selection, metadata design, and the maintenance cycle that keeps answers true after launch.
Fluent answers that cannot be traced back to a provision are unusable. This build grounds generation in a fixed corpus: 8.5M words, a Markdown-plus-JSON dual layer, an 8-step retrieval workflow, and a real case run end to end.
One canonical knowledge store any MCP-aware AI tool can query: three independently replaceable tiers, eight industry templates, and per-person access you revoke with a single command. Built so the knowledge stays with the business when the person leaves.
162 Markdown documents, one cloud knowledge base, searchable by meaning from Claude Code, Cursor, or n8n — and by your teammates. One command deploys it. The payoff is that a written answer gets made once and reused, instead of re-litigated three times a quarter.
Built a skill Wednesday night, opened a different Mac Thursday morning, and it was gone. The full-mesh Syncthing setup that keeps the config behind my workflow automation software identical on 4 machines - .stignore rules for 360,000 files, an onboarding SOP, and the mistakes I made.
Your knowledge sits in dozens of folders and hundreds of chat threads, so the answers come back generic. Build a knowledge base on your file system instead: the four-layer architecture, a step-by-step build sequence, and a checklist to tick off as you go.
Vector databases are overkill. A file-system knowledge base with multi-level CLAUDE.md routing finds any file in a 1,000-file system in three seconds. Here is the complete architecture — and why structure beats search when documents have to be findable on demand.
The code licence and the weights licence are two documents, and usually only one of them gets read. Sort the field into synthesis, cloning, and conversion first, then let commercial terms cut the list before an ai assistant for business ever speaks.
Debugging ate 60% of the build time across 20+ projects. The Quality Loop cut it to under an hour per Skill and dropped post-launch issues from 40% to below 10%: dual-phase detection, four-layer verification, and isolated SubAgent self-repair.
Your agent can call Claude Code. Can it do that at 3am without crashing, hanging, or silently failing? Bridge middleware handles process management, timeouts, interactive prompts, and automatic recovery, after two months running 10 agents in production.
Delegated work without a receipt is not delegated, it is just moved somewhere you keep checking. Three ways to close the loop: Hooks for a quick script, Channels for two-way chat, and a Hermes MCP bridge for cross-device push, with config code for each.
A long conversation degrades; a plan held in a script does not. Split an objective into dozens of subtasks, run them in parallel, cross-verify, and return only validated conclusions. Six patterns, a decision table, and the cost controls workflow automation software needs before running unsupervised.
The code licence and the weights licence are two documents, and usually only one of them gets read. Sort the field into synthesis, cloning, and conversion first, then let commercial terms cut the list before an ai assistant for business ever speaks.
Sameness is not a design problem, it is a memory problem: nothing carries a decision from one article to the next. One style drawn per article, held across every image inside it.
You need one good image, not a pipeline. Pick a tool, drop one reference, paste one prompt — done in 60 seconds. Five copy-ready templates, plus a checklist for telling when a job is genuinely big enough to deserve real workflow automation instead.
Prompts drift; reference images do not. A 5-step workflow automation setup that locks palette, composition, and texture across every illustration by anchoring to a single reference image — plus custom styles, platform aspect ratios, and storage backends.
Work that nobody complains about and nobody owns is the work that never gets done. Nothing breaks when one is missing, which is exactly why a hundred go missing. That shape of task is the clearest signal to automate business processes, and 155-character descriptions are the textbook case.
A topic plus a deadline is not a brief. It is an invitation to guess, and every writer guesses differently. Settling the answerable question before anyone writes is the cheapest quality control there is, and the one input a company can standardise when it moves to automate business processes.
SEO is where workflow automation pays off fastest: 112 CLI commands covering keyword research, site audits, indexing, link checks, GEO optimization, and AI search visibility — organized by website lifecycle stage, so you run the five that matter now instead of all 112.
A one-person company powered by AI is no longer a thought experiment: 29.8 million US solo firms generate $1.7 trillion. This playbook covers the four assumptions that broke, the four pillars a durable small business runs on, six proven paths, and the cost math behind 2026.
A practitioner's guide to domain-specific RAG knowledge bases across finance, tech, and consulting: the five-dimension framework, chunking that lifted retrieval accuracy, embedding selection, metadata design, and the maintenance cycle that keeps answers true after launch.
One canonical knowledge store any MCP-aware AI tool can query: three independently replaceable tiers, eight industry templates, and per-person access you revoke with a single command. Built so the knowledge stays with the business when the person leaves.
162 Markdown documents, one cloud knowledge base, searchable by meaning from Claude Code, Cursor, or n8n — and by your teammates. One command deploys it. The payoff is that a written answer gets made once and reused, instead of re-litigated three times a quarter.
Built a skill Wednesday night, opened a different Mac Thursday morning, and it was gone. The full-mesh Syncthing setup that keeps the config behind my workflow automation software identical on 4 machines - .stignore rules for 360,000 files, an onboarding SOP, and the mistakes I made.
When I rebuild one with AI agents, you get the write-up — including the parts that didn't work. No weekly roundup, no "5 tools you need."