How to Set Up AI Projects That Actually Deliver Results

The Work Before the Work

The difference between an AI project that delivers real results and one that costs you a month of frustration isn’t the tool you choose or how clever your prompts are.

After building my own business growth tool and implementing AI workflows across content creation and development, I’ve learned something that took me a while to properly understand: most AI projects fail because the foundation work never gets done. I’ve written about this same principle in building an AI marketing strategy — the planning is where the real leverage lives.

Why Most AI Projects Fail Before They Start

The most common mistake I see is people jumping straight into AI tools without any planning framework. They start every conversation from scratch, re-explaining context, objectives, and requirements each time. Then they wonder why the results are inconsistent.

I’ve done this myself. I’ve opened ChatGPT, typed a vague instruction, got something back that was almost but not quite right, spent twenty minutes trying to refine it, and ended up thinking “I could have just written this myself.” That’s not an AI problem. That’s a setup problem.

If you’ve tried creating content with ChatGPT or Claude.ai, you’ll know what I mean. Without proper context, the result is often a bland, generic mess that takes longer to clean up than it would have taken to write from scratch.

The Foundation That Makes AI Actually Work

After building my own tools and running marketing projects with AI over the past year, I’ve landed on something that sounds obvious but almost nobody does: AI projects need scaffolding, just like any other professional project.

Here’s what I mean by scaffolding: a set of reference documents that give your AI project context, constraints, and clarity from day one. I create these documents once, and I reference them throughout the entire project lifecycle. The AI reads them, understands the boundaries, and produces work that actually fits.

Let me show you exactly how this works with two real examples from my own business.

But first, I have a confession.

Unless you rein AI in with solid documentation, you’re going to spend a long time wrestling with output that doesn’t sound like you and doesn’t serve your business.

What you need is a structured foundation behind every prompt.

I see a lot of people who think the art of working with AI is developing one perfect, magical prompt that produces exactly what they want first time.

Example 1: Setting Up a Writing Project

When I work on content creation for We Build Stores, I don’t just open a chat window and start typing. Every project starts with proper documentation that I’ve built up over time, and that documentation ensures consistency and quality across everything I produce.

Here’s my standard setup:

(For context: Markdown is a lightweight way of formatting text that’s designed to be easy to write and read. It’s what I use for all my planning documents because it’s simple, portable, and works with every AI tool.)

PLANNING.md

This is where I answer the fundamental questions before I write a word:

• What am I trying to achieve with this piece?
• Who am I writing for?
• What business objective does this content serve?
• What are my key milestones and timeline?
• How will I measure whether it worked?

For my blog strategy, my planning document includes my target audience — business owners, typically in their fifties and sixties, who are mostly technophobes and didn’t grow up with this stuff. I include my content themes, and I map out how each post connects back to my business growth tool.

STYLE_GUIDE.md

This captures my voice, my tone, and my brand guidelines:

• Signature phrases I actually use (“But here’s the kicker…”, “That’s the bit people miss…”)
• Words I favour (practical, straightforward, proven)
• Words I avoid (corporate buzzwords, marketing jargon, anything that sounds like a LinkedIn post)
• My writing patterns and structures
• British English standards and business communication requirements

CONTENT_BRIEF.md

For each individual piece of content, I define:

• The specific objectives and key messages I need to hit
• The target audience’s pain points and motivations
• Required research and reference materials
• Content structure and format requirements
• Success metrics and conversion goals

REVIEW_PROCESS.md

This outlines my quality assurance workflow:

• Content review criteria and quality standards
• The approval process and feedback loops
• Version control and revision tracking
• Publication procedures and distribution

The result? Every piece of content I create sounds authentically like me, serves my business objectives, and builds towards measurable outcomes. I’m not starting from scratch every time. I’m not explaining the same context again and again. I set it up once, and it compounds.

Example 2: Setting Up a Development Project

When I built my business growth tool, I followed the same structured approach for the coding side. This methodology is what enabled the kind of rapid web development that I’ve written about elsewhere.

PRD.md (Product Requirements Document)

I start by defining what I’m building and why:

• Core functionality and feature specifications
• User personas and use cases
• Business requirements and success criteria
• Technical constraints and requirements
• Integration points with existing systems

TECHNICAL_SPEC.md

This document covers the technical implementation details:

• System architecture and technology stack
• Database design and data flow
• API specifications and integration requirements
• Security and performance considerations
• Development environment and deployment procedures

USER_STORIES.md

I capture functionality from the user’s perspective:

• Detailed user journey mapping
• Feature requirements written as user stories
• Acceptance criteria for each feature
• Priority ranking and development phases

ROADMAP.md

This outlines my development timeline:

• Project phases and milestone dates
• Feature delivery schedule
• Testing and quality assurance phases
• Launch procedures and post-launch support
• Success metrics and monitoring requirements

The benefit? When I sit down with Claude Code to build something, it immediately understands the context, the requirements, and the quality standards. I don’t waste time explaining what the project is. I point it at the documents and I start building.

The Compound Effect of Proper Planning

Your Action Plan

Don’t make the mistake I made early on — diving into AI tools without proper preparation. Here’s how I’d set up your next project for success:

1. Define your project scope. What exactly are you trying to achieve? I’d be specific about objectives, deliverables, and what success looks like. If you can’t describe the outcome in one sentence, you’re not ready to start.

2. Create your planning documents. I’d adapt the templates I’ve described above to your specific project. I know it feels like overhead, but I promise you it saves weeks of confusion later.

3. Establish quality standards. I’d define what “good” looks like for your project outputs. I include examples and criteria that the AI can reference — because without a target, it’s just guessing at what you want.

4. Set up review processes. I’d plan how you’ll evaluate and refine the AI’s output. Even with good scaffolding, the first draft is rarely the final draft. I build in review loops from the start.

5. Document everything. I keep detailed records of what works, what doesn’t, and what I’ve learned for next time. This is the compound effect in action — every project makes the next one better.

Ready to Set Up Your AI Project Properly?

The difference between AI that delivers results and AI that delivers frustration almost always comes down to the work you do before you start. If you want to implement AI in a way that actually moves your business forward, I can help you set it up correctly from day one.

My business growth tool can audit your current digital foundation and identify the best opportunities for AI to make a real difference. More importantly, I can help you plan and implement AI projects with the same professional standards I use for my own business.

I’ve already navigated the pitfalls. I’ve already made the mistakes and documented what I learned from them. You don’t have to go through that yourself.

Ready to build AI projects that actually work? Get in touch and I’ll help you set up your next project properly from the start.

Want to see exactly how I use these planning principles in practice? Read about Claude Code for web development — my AI-powered development workflow that runs on these exact scaffolding principles.

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