How to set up a proper AI project for marketing

You've probably experienced this: you're working with Claude on a campaign, and halfway through you realize it's using outdated brand guidelines. Or it's referencing the wrong product positioning. Or it's completely forgotten the creative direction you established three messages ago.

The problem usually isn't the AI. It's that your project isn't set up for AI to work with it effectively.

Most marketing teams organize their files for humans. Folders named "Stuff," documents called "Final_FINAL_v3," and critical information buried in Slack threads. That works okay when you're the one navigating it, because you remember the context. But when you're trying to get an LLM to help you, that structure falls apart.

Setting up a proper AI project means organizing your marketing work so that AI tools can actually understand what you're trying to do. And the good news is that organizing for AI also makes your projects clearer for your human team members too.

What makes a project "AI-ready"

An AI-ready project has a few key characteristics. First, it's clearly structured with logical organization. Second, it includes context files that explain what things are and how they relate. Third, it uses consistent naming conventions. Fourth, it keeps related materials together in ways that make sense.

Think about how you'd onboard a new team member to a project. You wouldn't just dump 50 random files on them and say "figure it out." You'd give them a project overview, explain the folder structure, show them where to find specific types of information, and provide context about what you're trying to accomplish.

That's exactly what you need to do for AI. The difference is that you're writing this context down in a format AI can read, rather than explaining it verbally.

The foundation: project structure that makes sense

Start with a clear folder hierarchy. At the top level, organize by major project or campaign. Within each project, create logical sections.

For a product launch campaign, you might structure it like this. A main folder called "Q4_Product_Launch_Campaign" with subfolders for brand_assets, content, creative, research, strategy, and templates. Each of those folders then contains relevant files organized by type or channel.

Your brand_assets folder might include your logo files, brand guidelines, approved color palettes, and font files. Your content folder could be organized by channel: email, social, blog, paid_ads. Your research folder holds your audience insights, competitor analysis, and market data.

The key is that anyone (human or AI) should be able to look at your folder structure and understand what's where. Avoid nesting folders more than three or four levels deep, because that makes it hard to find things. If you need more than four levels, you probably need to rethink your organization.

Context files: the game changer

Here's what most people miss: you need context files that explain your project to the AI.

Create a file called PROJECT_README.md in your main project folder. This is your project overview. It should explain what the project is, what you're trying to accomplish, who the audience is, what the timeline looks like, and how the folders are organized.

For that product launch campaign, your README might say: "This is the go-to-market campaign for launching our new Analytics Dashboard feature to existing customers in Q4 2024. Goal is to drive 30% adoption within 90 days of launch. Primary audience is mid-market B2B customers who currently use our basic reporting features. Launch date is October 15. All final assets go in the 'final_deliverables' folder. Work-in-progress materials stay in their respective channel folders."

That's context an AI can use. When you ask Claude to help you write an email for this campaign, it can read that README and understand the context: who the audience is, what you're promoting, what the goal is.

Beyond your main README, consider adding smaller context files in subfolders where they're helpful. In your content folder, you might have a CONTENT_GUIDE.md that explains your content strategy for this specific campaign. In your creative folder, a CREATIVE_BRIEF.md that outlines the visual direction, key messages, and design requirements.

These context files don't need to be long. A couple hundred words is often enough. The goal is to capture the essential information that helps someone (or an AI) understand what they're looking at and what they should do with it.

Naming conventions that don't make you want to scream

Let's talk about file naming, because this is where projects often go off the rails.

Use descriptive names that explain what the file is. "Email_1.docx" tells you nothing. "Launch_Announcement_Email_Existing_Customers.docx" tells you exactly what it is.

Include dates in your filenames using a consistent format. The best format is YYYY-MM-DD because it sorts chronologically. So "2024-10-15_Launch_Email.docx" sorts properly with other dated files.

Use underscores or hyphens to separate words, not spaces. Spaces in filenames can cause problems with some systems and scripts. Pick one (underscores or hyphens) and stick with it across your entire project.

Include version numbers if you're iterating on something. But here's the key: use a simple system like v1, v2, v3. Avoid the "final_v2_FINAL_actually_final" trap. When something is truly final, move it to a "final" or "approved" folder and remove the version number.

For marketing assets, consider including the channel and format in the filename. "LinkedIn_Carousel_Product_Benefits_v2.pdf" tells you it's a LinkedIn carousel about product benefits, and it's the second version. That's useful information when you have 50 files in a folder.

Documentation that actually helps

Beyond your README files, keep running documentation of decisions and changes. This is especially valuable for marketing projects that evolve over time.

Create a CHANGELOG.md file where you note significant updates. When you revise your messaging, note it. When you shift your creative direction, document why. When you change your target segment, write it down.

This serves two purposes. First, it gives AI context about how the project has evolved. If Claude sees that you shifted from targeting IT managers to targeting CFOs three weeks into the campaign, it understands why some older materials might have different angles.

Second, it helps your team. When someone new joins the project or when you're doing a retrospective, that changelog tells the story of how decisions were made.

Keep a RESOURCES.md file that links to external resources relevant to the project. If you're referencing specific market research reports, competitor websites, customer interview transcripts, or internal wiki pages, link them here. This creates a centralized place where anyone working on the project can find background information.

How tools like Claude Projects fit into this

Several AI tools now offer project features that let you organize your work and give AI persistent context. Claude Projects is one example. These tools let you upload files, add instructions, and have conversations within that project context.

Here's how this integrates with proper project setup. When you've organized your files well, uploading them to a Claude Project becomes straightforward. Your README files give Claude the context it needs right away. Your clear folder structure means you can easily find and upload the specific files relevant to what you're working on.

In a Claude Project for your product launch, you might upload your project README, your brand guidelines, your product positioning document, your competitor analysis, and your content guide. Now when you ask Claude to write an email or create a social media post, it has all that context without you needing to explain it every time.

The same principle applies to other AI tools with project features. The better organized your source material is, the more effectively you can work with AI tools.

Keeping marketing assets organized and accessible

Marketing projects generate tons of assets. Images, videos, copy documents, design files, data reports. If these aren't organized, you'll spend half your time hunting for the right version of the right file.

Create an assets folder with clear subcategories. Images might be sorted by type: product_screenshots, team_photos, stock_images, infographics, social_graphics. Videos could be organized by purpose: product_demos, customer_testimonials, explainer_videos.

For copy, consider organizing by stage and channel. Your email folder might have subfolders for drafts, in_review, approved, and deployed. Within each stage, files are named by what they are: "Welcome_Series_Email_1_Draft.docx."

Design files need special attention because they often come in multiple formats. A social media graphic might have a Figma file, a PNG export, and a PDF version. Keep these together in a folder named for what the asset is, like "LinkedIn_Launch_Announcement" with all three file types inside.

When working with AI on these assets, this organization matters. If you ask Claude to review your email copy, you can point it to the specific file in your approved folder. If you want help optimizing your social graphics' accompanying text, you know exactly where those graphics live and can reference them easily.

Version control for marketing materials

Marketing content goes through lots of revisions. Keeping track of versions without drowning in files requires a system.

The simplest approach: use a drafts folder for work in progress, and only move files out when they're approved. Within your drafts folder, version your files clearly (v1, v2, v3). When something is approved, move it to an approved folder and drop the version number.

For larger campaigns with lots of stakeholders, consider using actual version control tools. Google Drive's version history works for documents. For design files, many teams use Figma or similar tools that handle versioning automatically.

The key is having one source of truth. If your email copy lives in three different places, and you've edited two of them but not the third, you've created confusion for yourself and for any AI trying to help you. Pick one location for each asset and stick with it.

Structuring information for AI to understand

AI works best when information is structured and explicit. This means being more formal and clear in your documentation than you might be for human-only consumption.

Instead of "we're targeting the usual audience," write "we're targeting mid-market B2B companies with 50-500 employees in the technology and professional services sectors." The specificity helps AI understand exactly who you mean.

Instead of "use the brand voice," include your brand voice guidelines in the project or link to where they exist. Don't assume AI knows your brand voice. Give it the information it needs.

When you reference other documents, use clear paths or links. "See the competitive analysis in /research/competitor_analysis_2024.pdf" is better than "check the competitive stuff." AI can follow explicit paths. Vague references just create confusion.

Templates and frameworks for consistency

Marketing teams often use the same structures repeatedly. Email templates, social media post frameworks, blog post outlines, campaign briefs. Turn these into actual template files that live in your project.

Create a templates folder with reusable structures. Your email template might include sections for subject line, preheader text, hero image, body copy with specific character counts, CTA, and footer. Your social media template could outline the hook, the value prop, the call to action, and hashtag strategy for each platform.

When these templates are in your project, you can tell AI to use them. "Write an email using the template in /templates/promotional_email_template.md" gives Claude a clear structure to work with. This ensures consistency across your marketing materials and saves you from having to explain your format every time.

For campaign planning, keep a campaign brief template that prompts you to answer all the key questions: objective, audience, key messages, channels, timeline, budget, success metrics. Fill this out at the start of every campaign and include it in your project folder. It becomes your north star document that keeps everything aligned.

Collaborative projects with both humans and AI

Most marketing projects involve multiple people. Your project structure needs to work for human collaboration and AI assistance simultaneously.

Use a shared workspace where your team can access files. Google Drive, Dropbox, or similar platforms work well because they're accessible to both your team and uploadable to AI tools.

Establish clear ownership and editing permissions. In your README, note who owns which parts of the project. "Brand guidelines are owned by the brand team and should not be edited without approval. Content drafts in the content/drafts folder are open for editing by content team members."

This clarity helps when you're using AI to help with the project. If Claude suggests edits to your brand guidelines, you'll know that's not something to implement without the brand team's review. But if it suggests improvements to a draft blog post, you can evaluate and apply those freely.

Keep communication logs relevant to the project in the project folder. Major decisions made in meetings, feedback from stakeholders, approval notes. These can live in a communications folder as simple text files. When AI has access to this context, it can understand why certain decisions were made and work within those constraints.

Marketing-specific project setups

Different types of marketing projects benefit from slightly different structures. Let's look at a few common scenarios.

For a content marketing program, organize by content type and production stage. You might have folders for blog_posts, case_studies, whitepapers, and videos. Within each, subfolders for research, outlines, drafts, in_review, and published. Include a content calendar document that shows what's planned, what's in progress, and what's live. When you're working with AI to write a blog post, it can see what other content you've published recently and avoid repetition.

For a demand generation campaign, structure around the funnel. Top-of-funnel, middle-of-funnel, and bottom-of-funnel folders containing appropriate content and offers for each stage. Include your lead scoring criteria, your nurture sequences, and your conversion optimization notes. This helps AI understand the buyer journey and create content appropriate to each stage.

For social media management, organize by platform and content pillar. A folder for each social platform (LinkedIn, Twitter, Instagram) with subfolders for each content theme (thought_leadership, product_updates, customer_stories, industry_news). Keep your posting schedule and engagement guidelines accessible. When AI helps you create social content, it can ensure you're balancing your content mix appropriately.

For product launches, organize around launch phases: pre-launch, launch, and post-launch. Each phase has its own assets, messaging, and activities. Include your launch checklist, your go-to-market strategy, and your success metrics. As you move through phases, AI can help you ensure you're hitting all your milestones and creating content appropriate to each phase.

Making your project easy to navigate

Even with great structure, projects can get complex. Make navigation easier with a few simple additions.

Create an index file that lists all major documents and what they contain. Think of it like a table of contents for your entire project. "Brand guidelines: /brand/brand_guidelines_2024.pdf. Product positioning: /strategy/product_positioning.md. Competitor analysis: /research/competitive_landscape.pdf." When you need something, you can check the index rather than hunting through folders.

Use consistent README files at each folder level explaining what's in that folder. Your content folder's README might say: "This folder contains all marketing content for the Q4 launch. Email subfolder has all email campaigns. Social subfolder has platform-specific content. Blog subfolder has articles and supporting assets."

Consider including a getting started guide if your project is large or involves multiple team members. This guide walks someone through how to use the project: where to find things, how to add new materials, what the workflow is, who to contact for different issues. Both new team members and AI benefit from this orientation.

Maintaining project hygiene over time

Projects get messy. Files pile up, folder structures break down, documentation gets stale. Schedule regular project cleanups to maintain order.

Once a week, do a quick review. Are files in the right folders? Are draft versions that should be deleted still hanging around? Are new files named according to your conventions? Fix any issues before they multiply.

Monthly, review your documentation. Is your README still accurate? Has your strategy changed in ways you haven't documented? Are there new team members who need to be added to your contact list? Update as needed.

When a project or campaign ends, create a final archive. Move everything to an archive folder with a date. Create a final summary document that captures what you did, what worked, what didn't, and what you learned. This makes the project useful for future reference without it cluttering your active workspace.

Why this matters for marketing specifically

Marketing projects have some unique characteristics that make good AI project setup especially valuable.

First, marketing involves lots of iteration. You create multiple versions, test different approaches, and refine based on data. Without good organization, you lose track of what you've tried and what worked. With good structure, AI can help you analyze your iterations and suggest improvements based on what's worked before.

Second, marketing is cross-functional. You work with design, product, sales, maybe customer success. Information comes from multiple sources and needs to be synthesized. When your project is well-organized, it's easier to bring AI into that synthesis process. Claude can review your customer feedback, competitive research, and product information to help you develop messaging that addresses all the relevant factors.

Third, marketing is deadline-driven. You're often working fast under time pressure. Hunting for files or re-explaining context to AI wastes precious time. A well-structured project means you can jump in, get AI help quickly, and keep moving.

Fourth, marketing creates a lot of related but distinct assets. One campaign might include emails, social posts, blog articles, ads, landing pages, and sales collateral. These all need to be consistent with each other while being optimized for their specific channels. When your project organizes all these assets clearly, AI can help you maintain consistency across channels while still tailoring each piece appropriately.

Getting started without overwhelming yourself

Reading all of this might feel like a lot. You don't need to implement everything at once.

Start with your next new project or campaign. Before you create any assets, spend 30 minutes setting up a proper structure. Create your main folders, write a basic README, and establish your naming convention. As you work on the project, maintain that structure.

See how it feels. You'll probably find that you spend less time hunting for files, your team has an easier time finding what they need, and working with AI is smoother because it has context.

Once you've done this with one project and seen the benefits, apply the same approach to your next project. Gradually, you'll build the habit of setting up projects properly from the start.

For existing messy projects, you don't need to reorganize everything. But if you're actively working on something and finding the disorganization frustrating, spend an hour doing a cleanup. Create proper structure, move files where they belong, add a README. The time investment pays off quickly in reduced frustration and improved productivity.

The goal isn't perfection. It's having enough structure that both you and AI can work effectively without constant confusion. That's achievable without enormous effort, and the return on that small time investment compounds every time you work on the project.