INBOX INSIGHTS, July 9, 2025: Is AI Use Cheating, Context Engineering - Trust Insights Marketing Analytics Consulting

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INBOX INSIGHTS: Is AI Use Cheating, Context Engineering (2025-07-09)

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Are We Cheating When We Use Generative AI?

Last month, I was deep in the weeds developing our AI-Ready Marketing Strategy Kit – you know, the one we just released. I’d spent months researching, years developing frameworks, and weeks pulling together everything I know about building marketing strategies that actually work in an AI-driven world. The TRIPS framework, the 5Ps, the 6Cs – it was all swimming around in my head in various stages of completion.

I had all these pieces of expertise, but I was struggling to put them together in a way that felt coherent and actionable. And then I did something that made my stomach twist with guilt.

I opened Claude.

Not to create the frameworks for me (those came from decades of experience and research), but to help me organize my thoughts and see how all these pieces fit together into a logical flow. And you know what happened? I felt like I was cheating. Like I was somehow less of a professional because I used an AI tool to help me structure what I already knew.

Turns out I’m not alone in this feeling.

The Great AI Shame Spiral

When Chris and I recorded our podcast episode about generative AI this week, we also asked our Analytics for Marketers community about the stigmas they’re seeing around AI use. The responses? Chef’s kiss – and way more nuanced than I expected.

The Academic Hangover Chuck A. nailed something I hadn’t even considered: “Noticing some younger folks (especially graduated college within last 3 years) have negative associations with using at work after 4 years of college where there was a lot of negativity on AI (Eg, ‘Cheat with AI and you could get kicked out of school’).”

Oof. No wonder we’re all feeling guilty. An entire generation was literally taught that using AI = academic dishonesty.

The Pressure Cooker Problem But then there’s the flip side. Chalsea-Blaze pointed out: “One stigma I see is that if you’re not using generative AI, you’re falling behind or resisting progress. But I think there’s still a healthy space for skepticism and thoughtful adoption.”

And Stephanie S. added: “One stigma I see is if you don’t accept the company’s ChatGPT-plus invitation right away it’s perceived that you’re resistant to change.”

Wait, so we’re damned if we do and damned if we don’t?

Here’s What Actually Happened When I Built That Strategy Kit

When I used AI for that strategy kit, here’s what I didn’t do:

Skip the research
Let AI create the frameworks
Avoid developing my own methodologies
Stop thinking critically about the strategy components

Here’s what I actually did:

Used deep research to better understand marketing strategy best practices
Expanded the TRIPS, 5Ps, and 6Cs frameworks based on my expertise
Identified gaps where additional strategic elements were needed
Used AI to help me see how all these pieces connected logically
Refined, tested, and validated every framework and process

The AI saved me time in seeing the big picture, not in building the expertise.

Turns out, that’s exactly how Joy S. uses it too: “I typically only (actively) use AI to reorganize my writing or thoughts when I need to see it differently, or when I don’t like what I’ve come up with and want a different presentation.”

The “Other Set of Eyes” Revelation

Lisa K. absolutely nailed it with this perspective: “In college, among my group of friends, we would all read and proofread each other’s work because you need more than one set of eyes. I work from home alone. AI is my other set of eyes.”

She also shared something that made me feel so much better about my own AI use: “And Claude has done a great job of rewriting my direct, American emails into a format appropriate for the culture of my Indonesian coworkers… I am still learning and will probably never fully grasp the nuances of Indonesian business culture, and I greatly appreciate the help.”

This is the reframe we all need: AI as a collaborator, not a replacement.

As Tony L. put it: “The biggest stigma I see is getting people to treat AI like a junior staffer. In my work with nonprofits, I’ve found AI is most effective when I approach it as a collaborator, someone who needs context and direction to get the job done right.”

The Real Problems We’re Not Talking About

While we’re all worried about whether we’re “cheating,” there are some bigger issues bubbling up:

The Solution-in-Search-of-a-Problem Issue: Todd B. hit this one hard: “It’s often a solution in search of a problem.” And honestly? He’s not wrong. Not every task needs AI intervention.

The Environmental Concern: Joy S. brought up something I hadn’t considered enough: “I have a real problem with its impact on the planet, so I feel that it is used waaaaay more broadly than it needs to be.”

The Job Security Reality: Tony L. observed: “In smaller nonprofits, there’s real anxiety about job security. For many, the hesitation isn’t just about workflow changes, it’s about wondering if AI makes their work less unique or even obsolete.”

And Todd B. delivered the gut punch: “The challenge will be that, given the choice between doing your job better and doing a worse job at a lower cost, businesses will often choose the latter.”

Here’s My Mind Shift for AI Use

Instead of asking “Am I cheating?” let’s start asking these questions:

Am I still the expert in the room? If you’re using your knowledge to guide, validate, and improve the AI output, you’re not cheating.
Am I solving a real problem? Using AI to reorganize thoughts or format content? Great. Using it just because it exists? Maybe not.
Would I stake my reputation on this output? If you’re comfortable putting your name on it after review and refinement, you’re probably using AI appropriately.
Am I being honest about the value exchange? AI helps with process efficiency, but the strategic thinking and expertise are still yours.

What I’m Doing Differently Now

I’m using AI for the organizational stuff – seeing connections, structuring complex ideas, reformatting
I’m keeping the strategic thinking – framework development, methodology creation, real-world applications
I’m being selective – not every task needs AI; sometimes the manual process is actually better
I’m setting boundaries – AI helps with process, but doesn’t replace my professional judgment

It boils down to this. I’m using generative AI to cover my blindspots. We could all use that kind of support, right?

Because honestly? We’ve got bigger problems to solve than feeling bad about using tools that make us more efficient when used thoughtfully. Let’s focus that energy on doing better work instead.

P.S. – Yes, I used AI to help organize some of the thoughts in this post. And no, I don’t feel guilty about it anymore. But I also didn’t use it for everything. Progress.

What stigmas are you seeing or feeling around AI use? Reply to this email or join our free Slack group, Analytics for Marketers.

– Katie Robbert, CEO

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In this episode of In-Ear Insights, the Trust Insights podcast, Katie and Chris discuss the evolving perception and powerful benefits of using generative AI in your content creation.

You’ll discover why embracing generative AI is not cheating, but a strategic way to elevate your content. You’ll learn how these advanced tools can help you overcome creative blocks and accelerate your production timeline. You’ll understand how to leverage AI as a powerful editor and critical thinker, refining your work and identifying crucial missing elements. You’ll gain actionable strategies to combine your unique expertise with AI, ensuring your content remains authentic and delivers maximum value. Tune in to unlock AI’s true potential for your content strategy!

Watch/listen to this episode of In-Ear Insights here »

Last time on So What? The Marketing Analytics and Insights Livestream, we looked at creating bonus content for your podcast. Catch the episode replay here!

This week on So What?, we’re digging into generating video with generative AI tools. Are you following our YouTube channel? If not, click/tap here to follow us!

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In this week’s Data Diaries, let’s break down a new AI term that you’ve probably seen the nerds talking about if you hang out in the various AI-forward chats: context engineering.

What, you might ask, is this fresh new hell? What does it mean, and is it something you should care about?

Context engineering states that what separates great AI results from mediocre ones is not prompting, but context. Coined by OpenAI cofounder Andrej Karpathy, context engineering is… not new. In fact, it’s something we’ve taught in our Generative AI for Marketers courses for over a year now, just under a different name: knowledge blocks.

What is a knowledge block? In prompt engineering, knowledge blocks are exactly what they sound like – blocks of information that you have on hand when you’re using your favorite AI tools.

Why? Because – and this has been true since the earliest days of generative AI, since GPT-2 back in 2020 – the more relevant, specific words you use in a prompt, the better AI performs. The very nature of the tools dictates this; at their hearts, today’s language models are prediction engines. The more relevant information they have to predict with, the better their predictions tend to be.

The easiest way to provide a lot of relevant words? To build them in advance, like Legos, and then add them to prompts as you need them, from ideal customer profiles to how you do your marketing to SWOT analysis of your competitive space.

And today’s AI models can hold enormous amounts of information in a single prompt. ChatGPT can accommodate an entire business book of 50,000 words in a prompt easily. Google’s Gemini can handle the collected works of William Shakespeare, all 800,000 words, in a prompt.

The key takeaway here is that you should be building these knowledge blocks, storing them in an accessible place for you and your team, and dropping them into prompts any time you’re doing work where precision and correctness are important. The more data you bring to the party, the better AI tends to perform.

And if you’d like to learn how to build knowledge blocks that are robust and powerful, we teach that in our Generative AI Use Cases For Marketers course.

Here’s a roundup of who’s hiring, based on positions shared in the Analytics for Marketers Slack group and other communities.

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Imagine a world where your marketing strategies are supercharged by the most cutting-edge technology available – Generative AI. Generative AI has the potential to save you incredible amounts of time and money, and you have the opportunity to be at the forefront. Get up to speed on using generative AI in your business in a thoughtful way with our workshop offering, Generative AI for Marketers.

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