5 Claude Projects That Can Run Your Whole Business
A 5-project setup for Claude that gives you persistent context for content, clients, emails, research, and finances. Notes from running this for a few months.
Most people use Claude like a chatbot.
Open a tab. Type a question. Close the tab. Repeat.
That works, but it wastes the most useful feature inside Claude. Projects.
Projects give Claude a persistent layer of memory tied to a specific area of your work. You set the context once, and every conversation inside that project starts with it already loaded. Anthropic ships them with a 200K-token context window, custom instructions, a knowledge base for files, and on paid plans, RAG that expands capacity by up to 10x when the knowledge base outgrows the window. (Source: Anthropic support docs.)
After running this setup for the last few months, I have settled on five projects that each cover one part of my business. It is the closest thing to a real second brain I have used inside an AI tool.
Here is what each project does and the instructions to drop in.
What Projects actually do
A Project is a workspace with three things attached to it.
First, a system prompt that runs on every message you send inside the project.
Second, a knowledge base where you upload files. PDF, DOCX, CSV, TXT, HTML, RTF, EPUB, and a few more. Each file can be up to 30MB, with no cap on the number of files as long as the total stays inside the context window.
Third, conversation history kept inside the project, so threads stay separate from your other work.
That combination is what makes Projects different from a regular chat. You stop re-explaining your business, your tone, your audience, and your goals on every message. Claude already has the context.
The catch is that the system prompt counts against your context window. Keep it tight. Anthropic’s own guidance is to use it for general context and reserve task-specific instructions for the chat itself.
1. Content
The first project I set up was Content.
This is where every post, caption, newsletter, and thread gets drafted. The point is consistency. If I write in three different tones across LinkedIn, X, and my blog, I sound like three different people. So the system prompt locks in one voice.
My brand is [name].
My audience is [describe].
My tone is [3-5 words].
Platforms I post on: [list].
My content style: [describe or paste examples].
Every piece of content should sound like me, not AI.
I also drop 4 to 5 of my best-performing posts into the knowledge base. Claude pattern-matches off them. The output is closer to my actual writing than anything I get from a fresh chat.
2. Clients
The Clients project handles every outbound message that goes to a real person paying me money.
Proposals, onboarding emails, scope clarifications, follow-ups. The instructions cover what I sell, who buys it, and how I move someone from a first reply to a signed contract.
My business offers [services].
My ideal client is [describe].
My pricing: [list].
My process from inquiry to delivery: [describe].
When writing to clients, match this tone: [professional / casual / friendly].
The reason this saves time is not the typing. It is the thinking. I no longer have to reconstruct my own pricing logic or scope language every time a new lead lands in my inbox.
3. Emails
Email is its own project because the tone is different from client work.
Newsletters, replies to readers, cold outreach, and personal email all live here. The trick is being specific about what you do not want. Vague instructions produce vague output.
I write emails for [business / personal / both].
My tone is [describe].
I prefer emails that are [short and direct / warm and detailed].
Never use: [words or phrases you hate].
Always include: [sign-off, CTA style, formatting preferences].
I have a “never use” list with about a dozen entries on it. Phrases like “I hope this finds you well”, “circle back”, and “just wanted to check in”. Banning them once, inside the project prompt, fixes them forever.
4. Research
The Research project is the one I underestimated at first.
Default Claude is good at research but it gives you everything. You ask a small question and you get six paragraphs. This project trims that down.
When I ask you to research something, give me facts first, opinions second.
Include sources when possible.
Summarize in bullet points.
Flag anything that is uncertain.
My industry is [industry].
Focus on information relevant to [your niche].
The “flag anything uncertain” line is the one that matters. Claude will sometimes give you an outdated number or a half-correct claim with full confidence. Asking it to flag uncertainty up front catches a lot of those before they reach a draft.
For deeper work, I pair this with web search and a few uploaded reference PDFs in the knowledge base.
5. Finances
This one I treat with more caution. Claude is not a CPA. But it is good at math, ranges, and sanity checks if you give it the real numbers.
My business revenue is approximately $[range].
My main expenses: [list].
My currency is [currency].
When I ask about money, assume my tax situation is [country / filing status].
Help me find savings, optimize spending, and plan ahead.
I use this for monthly reviews, expense categorization, and “if I cut X, what happens to Y” scenarios. Anything that touches an actual tax filing still goes through a human professional. But for the routine stuff, having a context-aware sounding board has been useful.
One note on privacy. Anthropic does not train on your data by default for paid plans, but read the policy yourself before uploading anything sensitive.
Where to start
Pick one. Not all five.
Content is the easiest to feel value from quickly because you generate output every day. Set up the project, drop your tone notes and a few sample posts in, and use it for a week before adding the next one.
The mistake people make is doing all five on day one and never adjusting any of them. The system prompts in this post are starting points. The version that actually runs your business is the one you have edited four or five times after seeing what Claude got wrong.
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