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The Context Engine: How to zmistify your content

The Context Engine: How to zmistify your content

The complete playbook (final Context Engine newsletter)

Last week, I broke down the Results-Forward model we use at Zmist & Copy to write the best case studies in the industry. This week, we're diving into part 5 of our Context Engine: How to zmistify your content.

I'm writing a 5-part series on this topic. Here's where we're at:

  1. ✅The Context Engine: Keyword-led content era is gone
  2. ✅The Context Engine: Guide the reader toward your worldview
  3. ✅The Context Engine: Jobs To Be Done content, enhanced 
  4. ✅The Context Engine: How we write the best case studies in the industry 
  5. The Context Engine: How to zmistify your content (your strategy playbook) ← You are here

In today's newsletter:

  • Search changed. Your strategy should too
  • Full overview of the Context Engine and how the three models work together
  • How we zmistified Flyaps' content strategy
  • Your 90-day zmistification roadmap

The game has changed.

Creating content used to be hard. Now it's easy. Everyone has access to the same AI tools. 

Doing SEO used to be costly. Now it's much costlier. Your competitors have been building domain authority for years. Catching up requires a big SEO budget.

And if you do have strong authority, you’ve probably seen your highest-performing pages lose traffic anyway. That’s because users no longer click. They get their answers from AI.

If you're still in the 2020 mindset, you need to face the reality: 

Modern search is multi-dimensional, AI-native, and changing fast.

How exactly is it changing? After reading every playbook on GEO I could find, I added my own spin to make it even easier to digest.

Here are the 3 biggest shifts you need to know about.

If the way people find information has changed, that means your strategy has to change as well.

Ryan Law nailed it: create brand demand, not just content

Ryan Law, Director of Content Marketing at Ahrefs, recently posted something that echoes exactly what I’ve been saying all along:

"create brand demand. publish more studies, frameworks, and "coined concepts" - 'The Ahrefs Framework for X', 'The Ahrefs Study on Y'. get people searching for your brand, everywhere.

That's exactly what the Context Engine does.

It helps you create a system that makes your brand the reference point for your category.

The Context Engine: Full overview

If you've been reading my previous 4 newsletters in this series, you know that the Context Engine has 3 models. Here's how they work together as a funnel strategy to make your brand top of mind in your industry:

1. Teach & Tilt (TOFU) → Build category authority

Purpose: Establish your unique perspective on industry concepts

  • Define key concepts in your space 
  • Add your own angle or challenge conventional wisdom with your POV
  • Create frameworks and "coined concepts" that get referenced
  • Establish yourself as an authority in that space

What it looks like: 

"Checkbox marketing" by Brendan Hufford 

Read about the Teach & Tilt model.

2. See It Solved (MOFU) → Demonstrate your methodology

Purpose: Show exactly how you solve customer problems, illustrating your methodology with mini case studies 

  • Define the problems your customers are struggling with
  • Walk through your specific approach to solving them 
  • Build trust with a mini-case study showing your product or expertise in action
  • Offer a playbook or a template so the reader can act immediately

What it looks like: 

How The HubSpot Blog Is Combatting SERP Volatility

Read about the See It Solved model.

3. Results-Forward (BOFU) → Prove your impact

Purpose: Prove your claims and convert your prospects 

  • Pick claims you need to prove and case studies that prove them
  • Lead with metrics and measurable outcomes
  • Tell how you achieved those specific results, reinforcing your positioning in every section
  • Show before/after scenarios 

What it looks like: 

"Frotcom Ships Mobile Features at Scale: 70% Fewer Bugs, 99.94% Crash-Free Sessions"

Read about the Results-Forward case study model.

How all 3 models work together

Your Teach & Tilt content serves as Attention in AIDA. It generates awareness by establishing your unique POV on industry challenges.

Interest: Prospects intrigued by your perspective want to understand how you actually solve problems. Your See It Solved content demonstrates your methodology in action so the prospects can evaluate whether you can deliver.

Desire: When prospects are considering you, they check out your Results-Forward case studies that show the exact outcomes you've achieved for others. That builds confidence in their decision.

Action: By the time prospects reach out, they've already been educated by your frameworks, impressed by your methodology, and convinced by your results. The sales conversation becomes about your capacity and timeline. You don't have to prove anything to them. They arrive pre-educated, pre-qualified, and pre-sold on your approach.

This is how you compress sales cycles.

Our Context Engine is a perfect content funnel that allows you to focus your content efforts on what matters.

Now, let me show you how we did this for one of our clients.

Case study: How we zmistified Flyaps' content strategy

Challenge 

Flyaps needed to stand out in a crowded software development market by showcasing their unique AI and data engineering expertise.

Solution

TOFU: Teach & Tilt content: Big Data Engineering: It’s No Longer Just About “Big”

  • Defines the concept: Explains what big data engineering means 
  • Adds their tilt: "Big data is no longer just about 'big'" 
  • Introduces framework: Shows how the focus has shifted from size to context, real-time processing, and AI integration
  • Establishes authority: Positions Flyaps as experts who understand this evolution

MOFU: See It Solved content: Why We've Used Python for Data Engineering for 12 Years (And Still Do)

  • Shows methodology: Walks through exactly how they use Python across data engineering stages
  • Step-by-step process: Breaks down each stage with specific tools and frameworks
  • Mini case study: CV Compiler + 5 more real-world applications demonstrate their approach in action

BOFU: Results-Forward content: Bavovna AI’s RNN AI Model Achieves 99,98% Accuracy to Help Drones Navigate Without GPS

  • Leads with impact: Client raised $2.7M in funding after working with Flyaps
  • Quantifies results: 99.98% accuracy on 7.8km autonomous UAV mission without GPS
  • Shows transformation: From manual data processes to an automated MLOps pipeline
  • Proves claims: Complex ML project where they built a custom AI model trained on telemetric data

Result

Flyaps became the reference point for Python data engineering.

Based in Ukraine with an office in New York, they specialize in custom AI solutions and Python development. When you ask ChatGPT to “list Python development companies with data engineering expertise in New York,” here’s what comes up:

"Flyaps (NY & Dnipro, Ukraine) - Delivers custom AI-driven and cloud-native development in NYC. Offers Python development along with big data and BI services."

That AI-generated description nails their positioning.

Our content strategy worked. 

When AI references Flyaps, it mentions exactly what they want to be known for: AI development, Python expertise, big data, and cloud-native solutions.

Your 90-day zmistification roadmap

Month 1: Audit your content

  • Write your positioning statements: "This is who we're for, this is why we're better, here's the proof"
  • Identify your 3-5 core positioning pillars
  • Score your existing content using my Content Scorecard
  • Map content gaps across TOFU, MOFU, BOFU
  • Define your "coined concepts" and frameworks

Month 2: Create your context foundation

  • Publish Teach & Tilt pieces, establishing your POV
  • Publish See It Solved deep-dives showing your methodology
  • Create templates and tools people can use (they can be your lead magnets)
  • Publish Results-Forward case studies with real metrics

Month 3: Distribute and grow 

  • Repurpose top content into videos, social posts, and newsletters
  • Build partnerships for co-marketing and guest content
  • Invest in digital PR and brand mentions in industry publications and “Best X for Y blogs”
  • Start tracking brand mentions and AI citations

Here is the Lovable version of it.

The zmistification checklist

Before you publish anything, ask:

✅ Does this establish our POV? (Teach & Tilt) 

✅ Does this show our methodology? (See It Solved)

✅ Does this prove our impact? (Results-Forward) 

You want AI to cite you as a reference and make people remember our brand.

Stop creating content. Start building context.

The Context Engine is a way to create demand for your brand.

  • When prospects research your category, they find your frameworks.
  • When they evaluate solutions, they see your methodology. 
  • When they need proof, they read your case studies.

That's how you zmistify your content. And win in the AI era.

See you next week

This is the final newsletter in The Context Engine series. Next week, I'm diving into something completely different. Don't miss it.

Kate

P.S. Want our help zmistifying your content strategy? Contact us here.

P.P.S. If you missed any part of this series, here are all 5 newsletters:

  1. The Context Engine: Keyword-led content era is gone
  2. The Context Engine: Guide the reader toward your worldview
  3. The Context Engine: Jobs To Be Done content, enhanced
  4. The Context Engine: How we write the best case studies in the industry
  5. The Context Engine: How to zmistify your content (your strategy playbook)
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