AI gives generic advice because it starts every conversation knowing nothing about your business. The right fix depends on where you are today with AI tools. At the simplest end, a five-minute business brief fixes most of it. At the most connected end, AI reads your documents automatically, the way an assistant would check the files before answering a question.
Why does AI give generic answers?
AI tools have no memory between sessions. Every conversation starts fresh. When you ask how to price a project, the tool knows nothing about your rates, your clients, or how you work. It answers the generic version of the question, which is the only version it can answer without information about you. The tool is not broken. It just has nothing to work with.
What is the fastest way to give AI your business context?
Write a short description of your business: who your clients are, what you charge, and how you like to work. Save this inside the AI tool once, and it loads automatically into every new conversation. ChatGPT calls this Custom Instructions. Claude calls it a Project. Both take about five minutes to set up. This is the right starting point for anyone using AI occasionally who wants better answers straight away. If your business changes, update the brief. A slightly out-of-date brief still outperforms no brief at all.
Can AI read the files I already store in Google Drive or SharePoint?
Yes, if you use the right AI tool. Gemini for Workspace, Google's AI assistant, reads your Drive, Docs, and Sheets natively. Microsoft 365 Copilot connects to SharePoint, OneDrive, Teams, and Outlook. Once connected, AI reads your files where they already live. You do not upload copies. ChatGPT Business and Enterprise plans support connectors to Google Drive and Microsoft services as well. This approach takes about 30 minutes to configure and suits teams whose documents already live in one of these platforms. You get AI that knows your business without creating any new files.
What is a knowledge base and how does AI search through it?
A knowledge base is a collection of your important documents: past proposals, pricing guides, service descriptions, and notes on how decisions get made. You upload them to a dedicated space and AI searches through them when you ask a question. The technical name for this is RAG, short for retrieval-augmented generation. In plain terms: AI searches your documents first, then answers from what it finds, rather than guessing from memory. Think of it as an assistant who checks the filing cabinet before replying. This is the right approach when your business knowledge spans dozens of documents and a short brief cannot cover it all. Documenting your business processes for AI is how you prepare the material a knowledge base needs.
What is a file system on GitHub and is it worth the setup?
At the most capable end, your business knowledge lives as plain text files in a shared, versioned folder. Every file is readable by AI. Every change is recorded with who made it and when, so nothing gets lost or silently overwritten. GitHub is a platform for storing and sharing these versioned folders. AI agents like Claude Code read every file in the folder, search for what they need, and update documents as part of their work. Teams running this way have AI that already knows the business context before any task starts. This approach requires at least one person comfortable with plain text files and basic technical setup. For most small businesses, one of the first three options gives you the same practical benefit with far less effort.
Which approach should you start with today?
Pick the simplest option that solves your current problem. If you use AI occasionally and want better answers today, the brief is enough. If your team already uses Google Workspace or Microsoft 365, connect AI to those tools next. Once you have more than a few dozen documents AI should know about, a knowledge base setup pays off. The file-system approach becomes worth it once your team is comfortable with one of the earlier options. Starting with one tool beats overplanning.
- Brief (5 minutes): Write your business description once. ChatGPT saves it as Custom Instructions; Claude saves it as a Project. Works on any plan.
- Drive or SharePoint connector (30 minutes): Connect Gemini, Copilot, or ChatGPT Business to your existing Google or Microsoft files. AI reads them where they live.
- Knowledge base with search (a few hours): Upload your key documents. AI searches them before answering. This is called RAG. Good for businesses with dozens of files.
- File system on GitHub (a day or more): Store your business knowledge as plain text files in a versioned folder. AI agents read and update them automatically. Best for technical teams.
Frequently asked questions
Do I need to pick just one option, or can I combine them?
You can combine them. Many teams start with a saved brief and add a Drive connector a month later. Each option adds a layer without replacing the previous one. Start with whichever fits your current situation and add the next level only when you have a specific gap the current setup cannot fill.
What if most of our team knowledge lives in Slack?
Slack has its own AI feature, Slack AI, that searches your channel history. It requires a paid Slack plan and works separately from the four approaches above. If you do not have Slack AI, the practical workaround is to copy important decisions and notes into a Drive folder or Notion and use the Drive connector or knowledge base approach instead.
Can I use a saved brief on the free version of ChatGPT?
Custom Instructions in ChatGPT are available on the free plan, with a 1,500-character limit on the stored instructions. Claude Projects are available on the free plan as well, capped at five projects. Check the current plan page of whichever tool you use, since these features change with platform updates.
How do I keep a knowledge base accurate as my business changes?
Assign one person to a quarterly review: update any document that has changed, remove anything outdated, and add any new guides or decisions. If no one owns this step, the knowledge base drifts and AI starts giving wrong answers again. A quarterly review takes roughly an hour and keeps answers accurate.
Is GitHub realistic for a small business with no technical staff?
For most non-technical teams, no. Option 2 or Option 3 gives almost all the same benefit without requiring anyone to learn version control. GitHub becomes worth exploring when you already have someone comfortable with it, or when you are working with an AI consultant who sets it up and maintains it for you.
Not sure which approach fits your business? We can walk you through each option and set up the right one in a working session.