How to Set Up AI Projects That Actually Deliver Results

The scaffolding and planning that separates successful AI implementation from expensive frustration.

Here's the thing about AI projects: the difference between success and disaster isn't the tool you choose or how clever your prompts are.

It's the work you do before you ever type a single prompt.

After building the WBS Business Growth Tool and implementing AI workflows for content creation and development, I've learned something crucial: most AI projects fail because you fail to do the foundation work.

Why Most AI Projects Fail Before They Start

The most common mistake is jumping straight into AI tools without any planning framework and starting every conversation from scratch, re-explaining context, objectives, and requirements each time.

No wonder you get inconsistent results.

Without proper project scaffolding, even the best AI tools will produce random outputs rather than strategic business results.

If you've tried creating content with ChatGPT or Claude.Ai, the result is often a mess that takes longer to clean up than if you had written it yourself from scratch

The real problem isn't the AI's capability. It's the lack of a structured project setup.

The Foundation That Makes AI Actually Work

After building the WBS Business Growth Tool and working on marketing projects with my AI team (Mike, Brian, Claudia, Sophie, Elon Musk, and Leanne), I've learned something crucial: AI projects need scaffolding just like any other professional project.

You wouldn't start building a house without architectural plans. You wouldn't launch a marketing campaign without a strategy document. So why would you start an AI project without proper planning documents?

Here's what I mean by scaffolding: a set of reference documents that give your AI project context, constraints, and clarity from day one. Documents that you create once and reference throughout the entire project lifecycle.

Let me show you exactly how this works with two real examples.

But first of all, I have a dirty little secret.

You can tell AI to improve itself.

My first attempts at writing with Claudia were abysmal. She was all over the place!

Hallucinating fantastic customer success stories and making up information to suit her narrative.

This is the thing with AI writing, : unless you rein it in with solid documentation, you're going to spend a long time on the struggle bus.

What you need is a solid structure to back up your prompt.

Most people think the art of working with AI is developing a hit it out of the park one-shot prompt.

But that's not true. The prompt is one part of the overall orchestration.

Example 1: Setting Up a Writing Project

When Claudia and I work on content creation for We Build Stores, we don't just jump into writing.

Why Claudia, you ask? If you've ever seen "West World", you'll know that Dr Robert Ford creates the narratives. By giving your AI agent character identification, it becomes more natural to work with them.

Every project starts with proper documentation that ensures consistency and quality.

Here's our standard setup:

(Markdown is a lightweight markup language that lets you format text using simple, readable syntax. It's designed to be easy to write and read in plain text, then converted to HTML for web publishing.)

PLANNING.md

This document answers the fundamental questions:

• What are we trying to achieve?

• Who are we writing for?

• What business objectives does this content serve?

• What are our key milestones and timeline?

• How will we measure success?

For our blog strategy, the planning document includes our target audience (business owners aged fifty to sixty-five who are mostly technophobes - you can insert your customer avatar), our content themes, and how each post connects to our Business Growth Tool.

STYLE_GUIDE.md

This captures voice, tone, and brand guidelines:

• Signature phrases I use ("Here's the thing...", "But here's the kicker...")

• Words to favour (practical, straightforward, proven)

• Words to avoid (corporate buzzwords, marketing jargon)

• Writing patterns and structures

• British English standards and business communication requirements

  
  

CONTENT_BRIEF.md

For each piece of content, we define:

• Specific objectives and key messages

• Target audience pain points and motivations

• Required research and reference materials

• Content structure and format requirements

• Success metrics and conversion goals

REVIEW_PROCESS.md

This outlines our quality assurance workflow:

• Content review criteria and quality standards

• Approval process and feedback loops

• Version control and revision tracking

• Publication procedures and distribution

The result? Every piece of content we create sounds authentically like We Build Stores, serves our business objectives, and builds towards measurable outcomes. No more starting from scratch or explaining the same context repeatedly.

Example 2: Setting Up a Development Project

When Mike and I developed the WBS Business Growth Tool, we followed a structured approach for our coding project.

PRD.md (Product Requirements Document)

Defining what we're 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

Planning.md

This document covers the technical implementation:

• System architecture and technology stack

• Database design and data flow

• API specifications and integration requirements

• Security and performance considerations

• The Development environment and deployment procedures

USER_STORIES.md

This captures functionality from the user 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 our 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? Mike can pick up any development task and immediately understand the context, requirements, and quality standards. No confusion, no scope creep, no miscommunication.

The Compound Effect of Proper Planning

Here's what happens when you set up AI projects correctly:

Consistency: Every output aligns with your brand, voice, and business objectives because the AI has consistent reference points.

Efficiency: You stop wasting time re-explaining context and can focus on refinement and results.

Quality: Clear standards and criteria ensure higher quality outputs that effectively serve your business needs.

Scalability: Once the scaffolding is in place, you can tackle bigger projects and multiple workstreams without losing control.

Measurable Results: Defined objectives and success metrics mean you can track ROI and business impact.

Your Action Plan for Project Success

Don't make the mistake of diving into AI tools without proper preparation. Here's how to set up your next project for success:

1. Define Your Project Scope: What exactly are you trying to achieve? Be specific about objectives, deliverables, and success criteria.

2. Create Your Planning Documents: Adapt the templates I've shared above to your specific project needs. Invest time upfront to save weeks of confusion later.

3. Establish Quality Standards: Define what "good" looks like for your project outputs. Include examples and criteria that the AI can reference to ensure accuracy.

4. Set Up Review Processes: Plan how you'll evaluate, refine, and approve AI outputs to ensure they meet your business standards.

5. Document Everything: Keep detailed records of what works, what doesn't, and lessons learned for future projects.

The businesses that succeed with AI aren't the ones with the fanciest tools or the cleverest prompts. They're the ones who treat AI like any other professional tool: with proper planning, clear objectives, and structured processes.

Ready to Set Up Your AI Project Properly?

The difference between AI success and AI frustration often comes down to the work you do before you start. If you want to implement AI that delivers results for your business, let us help you set it up correctly from day one.

Our Business Growth Tool can audit your current digital foundation and identify the best opportunities for AI enhancement. More importantly, we can help you plan and implement AI projects with the same professional standards we use for our business growth.

Don't waste months learning these lessons the hard way. Work with someone who's already navigated the pitfalls and perfected the process.

Ready to build AI projects that work? Contact us today, and let's set up your next project for success from the start.

Want to see exactly how we use these planning principles? Next week, I'll introduce you to Elon, Mike, Claudia, Sophie, Leanne and Brian – the AI team members who help run We Build Stores using these exact scaffolding principles.