You're sitting in front of an idea, a new offer, a content plan or a strategic decision - and you realize that you're actually going round in circles.
Not because you lack knowledge.
But because you lack distance.
This is exactly where AI can be extremely valuable: not just as an answer machine, but as a thinking partner. As a sparring partner. As a system that shows you new perspectives, makes blind spots visible and forces you to think more precisely.
The crucial point is: AI doesn't do the thinking for you. But it can sharpen your thinking.
And that is often much more valuable in practice.
Many still use ChatGPT, Claude or Gemini too superficially. They enter a simple prompt like:
"Give me 10 ideas for LinkedIn posts."
Then they get 10 useful but rather generic suggestions - and then say:
"AI is quite nice, but also kind of interchangeable."
The problem is not the AI.
The problem is usually the way we work with it.
Typical mistakes are:
There is also something very human: we often get in our own way.
We have reservations.
We have fears.
We don't want to prompt "wrong".
We want perfect results straight away.
We doubt the quality before we have even tested it properly.
And that's exactly why we block ourselves.
Instead of simply doing, testing, iterating and learning from the process, we keep our distance. This is understandable - but also dangerous in the context of AI. Because the companies and people who learn quickly are currently building up a massive head start.
If you want to use AI not just for quick ideas, but for real in-depth thinking, this simple model will help you:
The first phase is not about perfection, but about breadth.
AI should open up options for you:
Here you use AI as a creative opener.
Now it gets interesting.
You're not just asking the AI to provide ideas, but to question them:
This is where brainstorming becomes strategic thinking.
At the end, you bring the best approaches into an implementable form:
This is where loose thinking becomes real implementation.
You know that your market has a specific problem. But your offer still sounds too general. It lacks focus.
Many entrepreneurs then go straight to formulating a solution. The result: an offer that wants to be "everything for everyone".
Instead of just asking the AI for ideas for offers, use it to broaden your perspective and make your thinking errors visible.
I am currently developing a new offer for [target group].
My goal is to formulate an offer that doesn't sound
sounds general, but solves a concrete, urgent problem.
problem.
Please help me in 3 steps:
1. analyze what typical problems this target group
target group really has in everyday life - even those that they often
often cannot clearly formulate themselves.
2. show me 10 possible approaches that are
are positioned differently:
pragmatic, strategic, premium, beginner-friendly,
results-oriented.
3. critically question my way of thinking: What typical
typical mistakes I am probably making when developing
developing the offer?
Important:
Do not answer generically, but as if you were working with
working with me on a marketable offer.
Before:
"I help companies with AI."
After:
"I help sales teams in SMEs to reduce administrative tasks with AI and reclaim several hours per week for real customer work."
That's the difference between an idea and a marketable positioning.
AI doesn't just deliver texts. It forces you to make fuzzy thoughts precise. It shows you blind spots and alternative directions. This is exactly how you think more deeply.
Many teams produce content, but the content remains superficial. Topics are collected, but no real thoughts are developed.
Then everything sounds similar, interchangeable and not very relevant.
You can use AI not only to generate content ideas, but also to work out theses, counter-theses and deeper levels.
I would like to develop content on the following topic:
[topic].
Please work with me not just on the level of ideas, but
at the depth of thought.
Work on the topic in 4 levels:
1. what obvious statements do almost everyone make about
on this topic?
2. which deeper or more uncomfortable truths are often
often overlooked?
3. what misunderstandings or errors in thinking do
people typically make in this area?
4. which 5 strong content approaches can be developed
from this develop that do not seem interchangeable?
Formulate the results in such a way that I can turn them
into blog articles, LinkedIn posts or workshop impulses.
Before:
"AI is changing marketing."
After:
"The real problem in marketing is not a lack of content, but a lack of quality of thought. AI does not automatically scale relevance - it first scales what is already there: clarity or arbitrariness."
That's a completely different lever.
AI takes you away from general statements and towards differentiated thoughts. You don't use the system as a copywriter, but as a reflection amplifier.
You are faced with a decision, for example:
Many people make such decisions on instinct - or spend too long discussing familiar patterns.
You can use AI specifically as a critical sparring partner.
I am faced with the following decision: [decision
describe].
I don't want you to simply make a recommendation,
but to structure my thinking.
Please work in 5 steps:
1. formulate the actual core question behind my
decision.
2. show me 3 possible perspectives on the topic:
Operational, strategic and customer-centric.
3. name the most important assumptions that I am
currently am making.
4. show me what risks arise if these assumptions are
assumptions are wrong.
5. give me a clear recommendation at the end as to
which small test decision I could make within the next
7 days to replace uncertainty with learning.
Be direct, analytical and calmly critical.
Before:
"We need to think more first."
After:
"We're defining a clear pilot process this week, testing AI-powered support there and making decisions based on real learning outcomes rather than guesswork."
That's strategic progress.
The good news: you don't need a special tool for this type of work.
Claude, ChatGPT and Gemini can all work as thinking partners - if you manage them correctly.
What matters:
The clearer your starting point, the stronger the results.
Bad:
"Give me ideas for my business."
Better:
"I advise medium-sized companies on AI implementation. Many decision-makers understand the potential, but don't know where to start. I'm looking for ideas for an entry-level offer with low risk and visible benefits."
Most people use AI too affirmatively.
They want ideas, but not friction.
But it is precisely this friction that is valuable.
Additional prompt:
Please don't confirm me too quickly.
Show me where my thinking is too simple, too convenient
or too too fuzzy. Give me counter-arguments, alternative
perspectives and potential weaknesses.
Good thoughts rarely arise in the first prompt.
Use follow-up questions such as:
This is often the point at which real quality emerges.
A small consulting firm wanted to sharpen its positioning. So far, the message had been very general: digitalization, innovation, sustainability.
The problem: the statements were correct, but not effective.
Instead of writing claims directly, AI was initially used as a sparring partner:
The result was not a "magic AI answer", but a better thought process.
Before: broad, abstract positioning.
After: clear focus on specific transformation projects with visible business effects.
Manually → vaguely discussed
AI-supported → structured reflection
Individual opinion → systematic sparring
This is exactly where the strength lies.
The real obstacle with AI is rarely the technology.
It is much more often these points:
We think too long instead of testing properly.
We evaluate too early instead of exploring with curiosity.
We seek certainty where learning is actually required.
This is particularly true when brainstorming with AI. Because it quickly becomes clear that AI is not only useful, it is also revealing. It reveals how blurred our own formulations sometimes are, how quickly we think in standard patterns and how often we remain on the surface.
This can be irritating.
But that is precisely why it is so valuable.
If you use AI sensibly, you don't just get more output.
You get better questions.
More clarity.
More depth.
More movement in thinking.
And this is often the beginning of real change.
If you want to try this out straight away, proceed as follows:
Don't use an artificial exercise.
Take a real challenge from your everyday life:
Don't just use "Give me 10 ideas", but ask for:
Don't leave after the first answer.
Keep working with questions.
Not everything AI says is strong.
But there are often 2 to 3 thoughts that have real relevance. Record these.
For example:
Because thinking only becomes valuable when it results in movement.
Companies, teams and freelancers who only view AI as a text generator are only using a fraction of its actual potential.
The greater leverage often lies in using AI as a thinking tool:
Those who don't do this often get stuck in old patterns of thinking and working - while others start to learn faster, communicate more precisely and test more boldly.
And this is precisely what becomes a competitive advantage.
Not because AI alone changes everything.
But because it can help people, teams and companies to think better and act more consistently.
This example is from the AI B2B Playbook. Click and download.
In addition to manual research, we have developed automated processes for you:
bloo.research - Find the right B2B companies in minutes
bloo.bid - Create offers in the time of an espresso.
If you not only want to understand AI, but also use it in a structured way in your company, then:
👉 Find out more about our AI training:
https://bloo.school
👉 Find out about our Smart Market Fit offers:
https://bloola.com/smf - The Smart Market Fit course
https://bloola.com/smf-system - The Smart Market Fit system for companies
👉 Or find out more about our consulting and automation solutions:
https://bloola.com