Mastering Context Collection and Formatting for AI: The Key to Getting High-Quality Outputs

Today

Getting AI to Actually Do What You Want

Look, if you've ever been disappointed by an AI response, I can almost guarantee the problem wasn't the AI—it was your context.

Here's the thing about AI: it's really really good at pattern matching and synthesis, but it's only as good as the information you feed it. And yeah, "garbage in = garbage out" might be a cliche in data science, but it's just as true for prompting.

Working with AI isn't just about asking good questions (though that's part of it). It's about making sure the AI has the right context to actually understand what you're talking about and generate something useful. That means two things: collecting the right information and formatting it in a way that AI can actually use.

Let me break down how to collect and format context for AI effectively, so you can stop getting vague, hallucinated responses and start getting crisp, accurate outputs that actually help you ship.


Step 1: Understanding Context Collection

AI Doesn't "Know" Anything—Like, At All

This is the first thing you need to get: unlike humans who have lived experiences and common sense and can remember conversations from 5 minutes ago, an AI model is basically starting fresh every time. It doesn't have any context outside of what it was trained on and what you explicitly give it.

So if you want good results, you need to supply high-quality examples, structured data, and relevant context.

Think about context collection like research (because that's basically what it is). You wouldn't write a report without gathering supporting materials and examples first, right? Same thing with AI.

What Counts as Good Context?

Think about the last time you asked AI to generate something—maybe a report, some code, or even just a summary. Did you just assume it knew what you were talking about? Or did you actually give it something to work with?

Here are three types of high-quality context you really really need before you even start prompting:

  1. Exemplars – If you want an AI to make you a great pitch deck, give it an example of what "great" means to you. Want a well-written blog post? Show it one you like. AI is basically just really good at pattern matching, so give it patterns to match.

I always return to the same few decks for their tone or argumentative structure! I should probably save those snippets somewhere...

  1. Raw Data – Building a client proposal? The AI needs the actual details—budget, scope, all that stuff. The more concrete data you feed it, the better stuff you'll get back.

  2. Style and Constraints – Want a specific tone? A certain length? Just say so! If you need formal writing, show it what formal means to you. Don't make it guess.


Step 2: Formatting Context So AI Can Use It

Once you've collected the right materials, the next step is to format them in a way that is structured, labeled, and free of noise. Raw information is often messy—spanning across PDFs, Google Docs, Slack threads, and emails. AI needs clarity to function effectively.

How to Format Context for AI

Here's a simple rule that'll save you a ton of headaches: AI responds best to labeled, structured inputs. If you just dump a wall of text into the prompt box, you're basically asking the AI to play a guessing game about what's important. Instead, be super explicit about what everything is.

Let me show you what I mean:

Example of Poor Formatting: (This is what most people do—don't be most people)

"I need a pitch deck for a mental health app. Here's some info: The app helps users track their emotions and get AI-driven journaling prompts. It's designed for Gen Z. I want it to feel modern and trustworthy. Also, here's a deck I liked [pastes link]. Can you generate one for me?"

What's wrong with this?

Example of Well-Formatted Context: (This is how you get AI to actually do what you want)

Objective: Generate a pitch deck for a new mental health app.

Intended Audience: Investors interested in mental health tech for Gen Z.

App Description: An AI-powered journaling app that helps users track emotions and generate personalized reflection prompts.

Key Features:

  • AI-generated journal prompts based on mood tracking
  • Integration with mindfulness exercises
  • Secure, private journal storage

Brand Tone: Modern, warm, and trustworthy—similar to Calm or Headspace.

Example Deck for Reference: [Insert link]

  • Using this because it nails the problem → solution → market size flow
  • Really good at telling a compelling story without getting lost in the details

Slide Structure:

  1. Title & Hook
  2. Problem Statement
  3. Market Context
  4. Solution Overview
  5. Product Features
  6. Business Model
  7. Team
  8. Call to Action

See the difference? The second version:

NOTICE SOMETHING THOUGH!!

I am not smart enough to come up with that structure immediately on my own. Thinking about a pitch deck and what you want to say about it is a completely different work flow than actually writing the deck. One is unstructed, exploratory, and iterative. Once you know basically what you want to say, THEN you can use that second prompt. So often I'll use a first quick prompt to help my thinking (a lot of the times using voice mode to just brain dump) and then when I have a general idea of what I want to say, THEN I'll use the second prompt to actually start building the deck.


Step 3: Context Awareness & Maintenance

Watch Out for Context Limits

Here's something most people don't get: not all AI models are great at remembering stuff. Like, some of them literally forget what you said at the start of the conversation by the time you get to the end. So if you're working with a lot of information, you need to keep restating the important bits.

Working on something big? Break it down into smaller chunks. Instead of dumping everything into one massive prompt, try this:

  1. Extract the key insights first
  2. Format those insights clearly
  3. Then generate your final output

Spotting When AI Goes Off the Rails

Even with really good formatting, AI can still mess up. Watch out for:

If you see any of these happening, you probably need to reformat your input, restate the important stuff, and be super explicit about what you want.


Final Takeaways

Look, here's what you really need to remember:

  1. Context is everything – AI doesn't magically know what you mean. You gotta tell it.
  2. Be picky about your context – Not all information matters. Focus on the good stuff.
  3. Format for clarity – Use labels, structure, and clear instructions to guide the AI.
  4. Watch those context limits – AI can lose track of things, so keep an eye on it and repeat the important stuff.

The difference between getting mediocre AI outputs and really really good ones usually comes down to how well you handle context. Get this right, and everything else gets way easier.


Want to see this in action?

Next time you're working with AI—whether you're writing, coding, or whatever—take an extra 60 seconds to structure your context properly. Trust me, it's worth it.

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