The $200K Skill Everyone Has Now

In 2014, I decided to go to college for Mechanical Engineering. I studied at Stevens Institute of Technology (go Ducks), a degree that cost some people over $200k to get.

And despite NEVER working as a Mechanical Engineer, it was worth it.

Not because it taught me how to design bridges and HVAC systems for buildings, but because it made me an expert at problem-solving.

And with AI eliminating the need for deep technical skills in almost every domain, this problem-solving skill is what becomes your differentiator.

So today - I’m walking through a problem-solving methodology that can turn anyone into a Modern Engineer.

Everyone is an engineer of something

As a Mechanical Engineer turned Software Engineer turned Operational Engineer turned Business Owner…I have quickly learned that for any engineering discipline, the process IS the job. The domain just changes the job title.

And if you’ve solved problems (you have), you've already engineered a solution to something, but may not understand how to best use AI to create a repeatable problem-solving methodology.

The process to engineer solutions is 5 repeatable steps:

1. Identify a Problem
2. Plan a Solution
3. Build
4. Review the Results
5. Repeat

That's it. And it works on anything multi-step; the domain just changes. Pre-AI, the Build step was the technical part, which required the $200k degree and thousands of hours to learn. Post-AI…you can let the robots do it for you.

Let’s use an example of something with zero code in it: a marketing plan.

Step 1: Identify A Problem. What is the problem you’re looking to solve? A good technique to identify a problem is called “The 5 Whys.” You ask Why 5 times to really understand the root of the issue. In this case: “We need more customers through social media marketing.”

Step 2: Plan a Solution. 
Iterate through what your hypothesis for a solution is. "To generate 10 new customers in 30 days, we need to create 30 pieces of organic content."

If you’re not sure where to start, open a new Claude project and run /buildpartner:expert-advice [INSERT PROBLEM] , so in this case run:

/buildpartner:expert-advice We need more customers through social media marketing

Once you understand the direction you want to go, you can say,

“Interview me to create a step-by-step plan on how to solve this problem.”

Now you have a plan, and it’s about executing.

Step 3: Build (The previous blocker)

The Build step was where you gave up and said, "I'm not technical” or “I don’t have that skill set.” But this is now what robots can do for you.

In our example, let’s assume the key problem was we didn’t have a way to MEASURE success.

So take the plan from Step 2 and give it to Claude. Have it make a system that keeps track of all the data that will measure the success of your plan. Something like this:

Now: "Using this plan, build a tracker that logs each post, pulls in likes, comments, and DMs, and shows me which ones are actually converting into booked calls." 

You're not writing the formulas or entering the data. You're writing the brief to include what you want tracked and what "converting" means for your business. AI builds the tool.

Step 4: Review the Results. Don't decide whether the tracker "looks good." Open it and check it against exactly what you asked for. You told it a "conversion" means someone booked a call, not just liked a post. So check if it’s actually counting that, or did it default to counting DMs as conversions?

Step 5: Repeat. Say the tracker says none of your 30 posts converted, but you know for a fact two people booked calls after DMing you directly. When you notice this in the review stage, go back to Claude and give it more information: what a booked call actually looks like in your calendar, how to match a DM to a name, what counts and what doesn't.

Figuring out why it's wrong, and fixing the actual cause instead of the symptom, is debugging.

And if you take one thing from me today, it's this:

You should never fix the same problem more than twice. After the second time, you codify it. Bake the fix into the system so it stops happening, instead of manually correcting it every time.

The domain changes, but the process remains the same.

Tools will change. What you work on will change. But your ability to problem-solve will travel with you no matter what domain you're working in.

That’s the skill that Stevens actually sells for $200k, not the technical training. JP Morgan bet on that skill over my ability to write code. And AI is giving you the same offer for free.

So stop saying you're not an engineer. You already are, because the technical part you were missing is now handled by AI.

Pick a problem you need to solve. Plan the solution. Hand the build to AI, then review and debug on repeat like it's the most valuable work you do, because now it is.

Let me know how it goes and what you're the engineer of. If you're stuck, just shoot me a reply. I'll point you in the right direction.

See you next newsletter, y’all.

Whenever you're ready, here’s how I can help:

For Business Owners & Operators:
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