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Why every personality test you've taken has failed you (and what actually works)
I've been obsessed with personality psychology for years. I've taken MBTI probably 15 times (different results each time, which tells you something). I've done Enneagram deep dives. I own actual Big Five assessment books.
After all of it, I kept running into the same problem: the results describe a type. They don't describe me.
Here's what I mean.
When MBTI tells you you're an INFJ, it gives you a description that applies to every INFJ who has ever lived. Your specific relationship with chaos, your particular brand of empathy, the exact way your shadow shows up in your life — none of that is in there. Can't be. It's a category, not a person.
The Enneagram is better at motivation but still pre-written. Big Five is the most scientifically valid but the feedback is almost uselessly abstract ("you scored 73rd percentile on Openness").
What would actually work is a test that:
Asks about real behaviour, not theoretical preferences
Weighs your specific answers against each other
Writes a result that has never been written before — because your combination of answers has never existed before
That's what AI makes possible. And that's what I built.
SoulPrint asks 10 questions about how you actually live. It scores your answers across 6 archetypes using a weighted algorithm. Then GPT-4 reads your exact answers and writes something specific to you — not to your "type."
The shadow section alone has made people stop mid-read.
It's free. It takes 90 seconds. thesoulprint.com
I'm not claiming it's scientifically validated. It's not therapy. It's a mirror. And sometimes a mirror is exactly what you need.
What's your experience with personality tests? Do you find them accurate or frustrating? Genuinely curious.
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"Non-technical people are now shipping production code."
That's a line the CEO of Coinbase buried in his company-wide tweet yesterday, in the middle of announcing layoffs for a "AI-native" restructuring.
And as much as I don't want to add to the AI fear spiral... this one is worth paying attention to.
Companies are moving toward smaller, hyper-focused pods. One person who's deep in their role, plus AI woven into every part of how they work. Not someone who chats with GPT occasionally. Someone who actually problem-solves through it.
Which means the bar for what "valuable" looks like is shifting. Knowing tools like Claude Code might not be optional much longer, it might just be the baseline.
At the same time, my co-founder and I talked about this and we don't think it ends in fewer jobs. we think it ends in a billion small companies.
Hiring shifts from buying a person to buying their IP, their agents, their workflows.
The generalist who can get 80% of the way there across everything starts to beat the specialist who owns 100% of one thing. Specialists still win at the frontier, deep engineering, AI labs, but everywhere else, range is becoming the advantage.
So the people who come out of this okay aren't the ones who panic.
They're the ones who get curious and may start building something of their own.
That's probably always been true. It's just more urgent now.
What do you think about this?
I tested the same cinematic prompt across multiple AI image models to compare how each system interprets character, lighting, realism, and mood.
No predefined face.
Just pure AI interpretation.
Tools included:
ChatGPT, Kling AI, Higgsfield, Hunyuan, Wan 2.7 Pro, Reve, Meta, Morphic, Flux 2 Pro, Seedream 5, Nannobanna, Recraft V4 Pro, and more.
The result became less of a comparison…
and more of an AI personality experiment.
Part 2: real identity consistency test 👀
Looks quite impressive!
Title: Your data is not the problem. The structure is.
Most business owners I speak to are not short on data.
They have spreadsheets. Exports. Reports sent every month. Numbers sitting in three different files that nobody looks at after the first week.
The real problem is not missing data — it is data that cannot be read quickly enough to change a decision.
A 5,000 row export tells you nothing at a glance. But a single dashboard showing revenue by channel, top performing SKU, and pending payments — that changes how a founder spends the next hour.
I have seen this pattern across CA firms, D2C brands, and small businesses. The data exists. The structure does not.
Clean structure means:
One place for all numbers
Metrics linked to actual decisions
Flags that tell you when something needs attention — not just what the current state is
If your data lives in scattered sheets and nobody is acting on it, the issue is not the data. It is the system around it.
That is exactly what I fix.
Great definition of your niche!
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