Hey!

Chris here. Welcome to Blueprint—the newsletter to help you build a winning engineering team.

Over the past 6 months, I've watched hundreds of founders and engineers alike make the same mistake with AI.

They think success comes from crafting the perfect prompt. Hours of tweaking questions, trying different phrasings, and hunting for the perfect structure that will unlock better responses.

But they're solving the wrong problem.

The real difference maker is context. And building it requires a completely different approach than most people realize.

Here's what actually works. 👇️ 

📒 DEEP DIVE

Context is Everything

Why building knowledge infrastructure matters more than perfect prompts.

Let's start with the "duh" idea. At their core, LLMs are pattern completion machines. So if you prompt them without sufficient background, they'll fill in the gaps with assumptions.

Even the smartest models struggle when the context window runs out or there isn't enough relevant information loaded in. They'll forget things you already told them, make contradictory suggestions, and give you generic answers that miss the nuances of your specific situation.

But when you build comprehensive context—when you feed the system structured information about your problem, your constraints, your goals, and your domain knowledge—that's how you use AI to its full potential and minimize hallucinations.

Take a codebase: feed an AI agent raw code files with no documentation, and it'll give you surface-level suggestions.

But layer that same codebase with structured summaries, system explanations, and contextual notes, and you'll get solutions that actually understand the deeper architecture and business logic.

This is why I'm always preaching about documentation.

Documentation Gets Functional

For years, we've been told documentation is important.

But when it only had a chance of future value, most people discounted that and moved on.

But AI changes the fundamentals of this calculation. Now, documentation provides immediate value rather than just promising future benefits.

When I need AI to solve problems in a complex system, the first step is documentation.

I have them study different parts of the system and create layered explanations—file-level documentation, then system-level overviews that tie everything together.

This process feels backward at first. You're solving problems by...not solving problems. But that's exactly what you need to do if you want AI to be genuinely helpful rather than just occasionally useful.

Your Castle of Context

Think of effective AI usage as building a castle of context, brick by brick.

Each document you create, each structured summary, each layered explanation becomes part of a foundation that makes every subsequent interaction more powerful.

This means you have to go slow to go fast. The upfront time investment in context creation pays dividends when downstream problem-solving becomes exponentially more effective.

Want to know what this looks like in practice? Here's the process I use (and you should, too) when I need AI to solve real problems in complex systems.

How to Actually Build Context

A prerequisite to doing this well is an expert-level understanding of the domain. Without this, you won't know enough about what you're documenting to structure it properly and point AI toward the right pieces when you need answers.

That said, let's dive in.

I start by telling AI agents to study the relevant files and build documentation. I'll say something like: "Go look at this file and study it in immense detail, and then come out with a file that describes it like this. And you store it in this location."

Then I layer it. I have one AI agent analyze individual files and another that takes all those individual analyses and builds system-level overviews.

The goal is to build novels of documentation so that when I need to solve an actual problem, I can go in and say: "Go read this document first. And then I want you to solve this problem."

This approach is admittedly meta. You have to think about what someone would need to know to solve the problem, how to help the AI gather that same information, and then work backwards to figure out the best first step.

But it produces excellent results when executed correctly.

The New Elite Skill

The winners in the AI era will be the people who master three critical abilities:

1. Extracting knowledge from complex systems, whether that's codebases, business processes, team expertise, or industry experience.

2. Structuring that knowledge as usable content by turning scattered information into organized, layered documentation that AI can actually work with.

3. Feeding it back to AI systems most effectively by knowing how to point AI toward the right context and combine it with specific problems to solve.

Here's the tough truth: People who can't think systematically struggle to build the context AI needs to be effective.

This flips the traditional skill hierarchy. The ability to organize knowledge logically and present it in layers becomes more valuable than raw technical ability alone.

The best communicators are poised to become the best builders because they understand how to create the knowledge foundation that makes AI genuinely useful.

🎙 EPISODE OF THE WEEK

Selling without being sleazy isn’t just possible—it’s the fastest way to build trust, win clients, and grow your business.

In this week's episode of the Build Your Business Podcast, Matt and I break down a founder-tested approach to sales that replaces pushy tactics with authentic problem-solving. We discuss how to lead with trust, diagnose real client needs, and close deals without feeling “salesy.”

If you’re a founder, entrepreneur, or business owner, this episode will help you stop pitching, start solving, and build long-term client relationships. Whether you’re selling a service, product, or software, selling without the sleaze can become your most powerful competitive advantage.

Check it out: Spotify | Apple Podcasts | YouTube

BEFORE YOU GO…

The knowledge economy is changing.

The people who figure out how to build context—how to document their expertise, structure their domain knowledge, and create systems that AI can meaningfully engage with—are going to have an enormous advantage.

Because while everyone else is trying to perfect their prompts, they'll be building the knowledge infrastructure that makes AI actually work.

So starting today, document everything. Act like your livelihood depends on it.

Because with the rate AI is accelerating, it just might.

Talk soon,

Chris.