There’s an irony running through the edtech sector right now. We’re building products powered by AI, pitching adaptive learning platforms and intelligent tutoring systems to schools – yet when it comes to using AI in our own businesses, many are barely scratching the surface.

More specifically, we’re using AI as an answer machine when we should be using it as a thinking tool.

Open any edtech founder’s ChatGPT history and you’ll likely see a familiar pattern:

“Write me a blog post about [topic]” “Create an email sequence for [campaign]” “Draft a job description for [role]” “Summarise this market research report”

These are answer machine prompts. You ask a question, AI spits out an answer, you copy and paste (maybe with light editing), and move on.

Don’t get me wrong – there’s nothing inherently wrong with this. It’s faster than doing it yourself. It can be useful for getting past blank-page syndrome. For repetitive tasks, it’s genuinely efficient.

But if this is all you’re doing with AI, you’re missing the point entirely.

 

What a Thinking Tool Actually Does

A thinking tool doesn’t give you answers. It helps you think better.

It challenges your assumptions. It reveals blind spots. It asks questions you hadn’t considered. It explores alternatives you wouldn’t have generated alone. It helps you stress-test ideas before you commit resources to them.

The difference is philosophical, but it’s also practical and profound.

 

Answer machine approach: “Write a product positioning statement for our new literacy platform” → AI generates something generic → You use it or tweak it slightly → You move on

Thinking tool approach: “I’m positioning our literacy platform as ‘AI-powered reading intervention for struggling learners.’ What assumptions am I making? What might I be overlooking? What questions should I be asking myself before finalising this positioning?” → AI highlights assumptions about your target market → Points out that ‘AI-powered’ might not resonate with primary teachers → Asks whether you’ve validated that schools see ‘struggling learners’ as a distinct segment worth targeting → Questions whether ‘intervention’ frames your product too narrowly → You end up with sharper, more thoroughly considered positioning

The difference here is that in the first approach, you outsourced thinking. In the second, you amplified it.

 

Where Edtech Businesses Actually Need Better Thinking

Here’s where using AI as a thinking tool rather than an answer machine can genuinely transform your edtech business:

1. Product Strategy and Roadmap Planning

Answer machine: “Create a product roadmap for our edtech platform”

Thinking tool: “I’m planning our next 12 months of product development. Our current roadmap prioritises [features X, Y, Z] based on [these assumptions]. What strategic questions should I be asking? What risks am I not seeing? What customer segments or use cases might I be overlooking?”

The thinking tool approach forces you to interrogate your own logic – it surfaces the assumptions you’re making unconsciously. It helps you think through second-order effects – what happens if you build Feature X but competitors respond by doing Y?

 

2. Go-to-Market Strategy

Answer machine: “Write a go-to-market plan for selling to academy trusts”

Thinking tool: “We’re targeting academy trusts with 5+ schools. Our sales cycle is typically 6-9 months. We’re assuming the key decision maker is the CEO with input from the CFO and Trust Education Director. Challenge these assumptions. What are we likely getting wrong? What dynamics in multi-academy trusts might we be missing?”

The thinking tool approach helps you pressure-test your understanding of the market before you’ve wasted months pursuing the wrong strategy.

 

3. Competitive Positioning

Answer machine: “Analyse our competitors and tell me how to differentiate”

Thinking tool: “Here’s how we currently differentiate from competitors: [your differentiation]. Now play devil’s advocate. Why might this differentiation not matter to customers? What would make this advantage disappear? How might competitors neutralise this? What am I assuming about what customers actually value?”

This kind of adversarial questioning helps you build more defensible positioning before you’re confronted by actual market resistance.

 

4. Pricing Strategy

Answer machine: “What should we price our platform at?”

Thinking tool: “We’re considering pricing at £X per student per year. Walk me through the economic logic from a school’s perspective. What budget does this come from? What are we displacing? At what price point does this become a ‘board-level decision’ versus a department decision? What assumptions am I making about willingness to pay?”

Pricing is psychology and strategy, not maths. A thinking tool approach helps you understand the second-order implications of your pricing decisions.

 

5. Customer Discovery and Research

Answer machine: “Create a customer interview script for schools”

Thinking tool: “I’m trying to understand why schools aren’t adopting our phonics platform as quickly as expected. What hypotheses should I be testing? What questions might reveal hidden objections or misaligned assumptions? What am I likely to miss if I only ask direct questions about the product?”

The thinking tool approach helps you design better research that uncovers what customers aren’t telling you explicitly.

 

Using AI as a thinking tool requires different prompting discipline. Here are six patterns that work:

 

1. Challenge Me: “Here’s my plan: [plan]. Challenge the core assumptions. What am I likely wrong about?”
2. Explore Alternatives: “I’m considering approach X. Generate five meaningfully different alternative approaches I should consider, and explain the trade-offs of each.”
3. Pressure Test: “Here’s our value proposition: [proposition]. Steel-man the argument against it. Why might schools decide this doesn’t actually matter?”
4. Reveal Blindspots: “What questions about [topic] am I not asking but should be? What dimensions of this problem am I likely overlooking?”
5. Play Scenarios: “If we pursue strategy X, how might competitors respond? Then how would we respond to that? Walk through three iterations of competitive moves and counter-moves.”
6. Interrogate Assumptions: “I’m assuming [assumption]. What data would disprove this? What would have to be true for this assumption to be wrong?”

 

These prompts have something in common in that they’re not asking for content to copy and paste. They’re asking for thinking that sharpens your own.

 

Why Edtech Founders Especially Need This!

The edtech sector has some unique characteristics that make thinking tools especially valuable:

• Long sales cycles mean you can waste months pursuing the wrong strategy before you get market feedback. Better thinking upfront prevents this.
• Complex stakeholder dynamics (teachers, SLT, IT, procurement, governors) mean what seems obvious often isn’t. Pressure-testing your assumptions reveals hidden complexity.
• Rapid market evolution means yesterday’s winning strategy might be tomorrow’s dead end. Scenario planning helps you anticipate shifts.
• Limited runway for most edtech startups means you can’t afford to learn entirely through expensive trial and error. Better thinking reduces costly mistakes.
• Founder blind spots are inevitable when you’re deeply immersed in your product. An adversarial thinking partner helps surface what you’re missing.

Common Mistakes (And How to Avoid Them)

Mistake 1: Treating First Output as Final When you ask AI to challenge your thinking, the first response is just a starting point. Follow up. Push back. Ask it to go deeper.

Mistake 2: Only Using AI for Execution, Not Strategy It’s tempting to use AI for the “doing” work (writing, summarising) and keep the thinking to yourself. Reverse this. Do more thinking with AI, less execution copying.

Mistake 3: Not Creating Constraints “Help me think through X” is too vague. Give context, constraints, and specific aspects you want interrogated.

Mistake 4: Forgetting It’s a Tool, Not an Oracle AI can help you think better, but it doesn’t know your customers, your market position, or your constraints like you do. Its role is to sharpen your thinking, not replace it.

 

Practical Implementation: Start Small

You don’t need to transform your entire workflow overnight. Start with one area where better thinking would have high leverage:

This week: Before finalising one significant decision, spend 30 minutes using AI to challenge your assumptions about it.

This month: Pick one strategic area (product roadmap, pricing, positioning) and use AI to explore alternatives and pressure-test your current approach.

This quarter: Build a habit of adversarial thinking – whenever you’re confident about a decision, deliberately ask AI to steel-man the case against it.

 

Honestly though, using AI as a thinking tool is uncomfortable. It challenges your assumptions. It reveals flaws in your logic. It suggests you might be wrong about things you were confident about.

An answer machine is much more pleasant. It agrees with your framing and gives you what you asked for.

Comfort isn’t what you need when you’re building an edtech business. You need sharper thinking, pressure-tested strategies, and the ability to spot problems before they become expensive failures. Leave your comfort zone at the earliest opportunity!

 

The next time you’re about to ask AI to write something, draft something, or create something for you – pause.

Ask yourself: “What if instead of asking for an answer, I asked for help thinking through the problem more thoroughly?” It might be the thing that helps you make decisions you won’t regret six months from now.

 

What’s your experience? Are you using AI as an answer machine or a thinking tool in your edtech business? What prompts or approaches have you found most valuable? I’d love to hear your perspective.