Dave Ebbelaar

In 2019 I almost started a regular data science job, fresh out of my master's.

The offer was accepted and my start date was two months out.

In that gap I joined a three-day hackathon, and through it I landed my first freelance gig. One week of paid work.

That week turned into a quarter, and then a potential extension for a full year came on the table.

So I had to make a call.

I emailed the employer to tell them I wasn't coming. They weren't happy about it. 😅

The extension came through, and I spent that year on the company's innovation team as a freelance data scientist.

I've been freelancing in tech ever since, and I never looked back.

Back then I believed freelancing was the risky option. No job security, always hunting for the next gig.

Seven years later I can tell you it doesn't have to work that way.

If you set yourself up correctly, pick a freelance model that fits your situation, and focus on longer-term contracts, it's just as reliable as a regular job.

Especially with the layoffs happening everywhere.

But you need to start small. Similar to my first one-week project.

And that's exactly where the work is changing the most.

With AI-assisted coding, small project-based work no longer means sitting behind a screen for hours banging out code.

What clients pay for is someone who understands what to build and how to deliver it.

And that changes the unit economics of freelancing.

It used to mean spending days, weeks, sometimes months on a single project. Nearly impossible next to a full-time job.

That has now completely changed.

So I'm looking for five tech professionals with a full-time job to build case studies around, for something I've been working on. 

I want to show what's possible when you start freelancing this way.

This is for you if you have at least a year of experience in tech (ideally more) and you're confident in your technical skills.

If you have that, plus some extra time next to your job, I'll show you how to land your first client in the next 90 days and how to set up an AI-first delivery system that lets you run it next to your full-time position without burning yourself out.

If that sounds interesting, check the link below to see if you qualify and book a free call with my team to see if it's for you.

Apply here: go.datalumina.com/fEF0aBs

1 week ago | [YT] | 75

Dave Ebbelaar

I failed my first Python class.

Then almost quit my AI degree because of it.

This was back in 2013, my first year at university, and I'd never written a single line of code before.

We'd sit in a big lecture hall for the theory, then get sent to lab sessions to build a snake game.

I had no clue where to even start.

After that, all I really had was some basic syntax. I could print hello world and write a simple function, but nothing I could actually build with.

Nobody showed me how to properly set up an IDE, configure my environment, or build an actual useful program.

So I gave up on it for almost two years.

It wasn't until my third year, in my first NLP class, that things finally started to click.

Now I code almost every day, and it's one of the most fun things I do.

A full semester at university couldn't get me there...

So last year I finally built the course I wish I'd had back then.

Including the whole setup most beginner courses skip. Environments, IDE, pip, uv, git.

And last week it crossed 1,000,000 views. 📈

Even with AI writing most of our code now, the foundations matter as much as ever.

Sure, you can vibe-code something on the side. But you can't vibe-code a career in AI without understanding the language underneath it.

Link to full course: https://youtu.be/ygXn5nV5qFc

1 week ago | [YT] | 240

Dave Ebbelaar

This summer I'm heading to Montenegro for a 3-day event with some of the biggest AI creators, and I'd love for you to be there.

July 29th, three days. The lineup includes Liam Ottley, Nate Herk, me, and many more other faces you'll know from YouTube.

Here's the agenda:

- Day 1 is the VIP operator day. Think being in the boardroom with all of us to ask questions, network, and dig into what's actually working right now.

- Day 2 is the main event. Presentations, insights, and the strategies people are using today.

- Day 3 is another VIP day with a private boat tour and dinners with the group.

Two ticket types: the full VIP experience for all three days, or the more affordable general access for the main event day.

We did a similar event in Cape Town earlier this year. It sold out and was honestly one of the best I've ever been to (recap video below).

Grab your spot here: workless.ai/

Would be really cool to meet you there!

3 weeks ago (edited) | [YT] | 5

Dave Ebbelaar

You have likely heard about all the recent supply attacks on package managers like npm and PyPi.

This is a serious issue right now.

And it will likely only get worse...

So I highly recommend to look into this.

In my latest video, I give you 3 practical tips you can implement today to keep your projects safe.

1 month ago | [YT] | 12

Dave Ebbelaar

Making an LLM API call is the most expensive and most dangerous operation in modern software development.

While incredibly powerful, you want to avoid it at all costs and only use it when absolutely necessary.

Most successful AI applications I've seen are built with simple, custom building blocks, not agent frameworks.

This is because most effective "AI agents" aren't actually that agentic at all.

They're mostly deterministic software with strategic LLM calls placed exactly where they add value.

The problem is that most frameworks push the "give an LLM some tools and let it figure everything out" approach.

But in reality, you don't want your LLM making every decision.

Now there are exceptions to this (e.g., Cursor)

But generally, you want it handling the one thing it's good at - reasoning with context - while your code handles everything else.

The solution is simpler than most frameworks make it seem.

Here's the approach that actually works:

1. Break down what you're actually building into fundamental components
2. Solve each problem with proper software engineering best practices
3. ONLY INCLUDE AN LLM STEP when it's impossible to solve with deterministic code

But when you do make that LLM call, it's all about context engineering.

To get a good answer back, you need the right context at the right time sent to the right model.

You need to pre-process all available information, prompts, and user input so the LLM can easily and reliably solve the problem.

This is the most fundamental skill in working with LLMs.

AI agents are simply workflows - directed acyclic graphs (DAGs) if you're being precise, or graphs if you include loops.

Most steps in these workflows/graphs should be regular code - not LLM calls.

Given all of this, you only need about seven core building blocks to solve almost any business problem with AI.

Take your big problem, break it down into smaller problems, then solve each one using these building blocks chained together - that's how you build effective AI agents.

P.S. I explain all of this in more detail in the video below.

11 months ago | [YT] | 68

Dave Ebbelaar

Hey everyone, I hope you've had a lovely Christmas!

As we're wrapping up the year, I wanted to share my plans for 2025 with you to grow Datalumina.
In this video, I'll go over the master plan that the team and I created.

Here are some things I'll go into:

- The traffic system that runs 24/7, driving our leads
- The SaaS product fueling our pivot to scalable growth
- Why we’re minimizing custom development to focus on consulting and productized services

If you’re curious about how to structure a business with synergy across products and services, this behind-the-scenes look is for you.

P.S. I tried a new style of video where I show you more behind the scenes of what's going on in my life. I plan to do this more often next year. I hope you like it!

1 year ago | [YT] | 16

Dave Ebbelaar

After two years of building with GenAI, here’s what I wish I’d had from day one...

This has been a long time in the making, and I’m excited to finally pull back the curtain on what we’ve been building behind the scenes:

The GenAI Launchpad — officially launched on Product Hunt today! 🎉

For the past two years, my team and I at Datalumina have been deeply involved in the world of AI, building solutions with large language models (LLMs) for clients across industries.

Each project taught us so much about what it takes to bring AI to life in practical, high-impact ways.

But there was one recurring challenge...

We spent way too much time setting up project structures, handling integrations, and putting out fires in the infrastructure — leaving less time for the real AI work, the work that brings ideas to life.

Not only was setup eating into our time, but we also found that the agent frameworks on the market were just too optimistic.

Real-world use cases are more complex and demand reliability and precision that many frameworks simply can’t deliver.

So, we got to work! 👷🏼‍♂️

And after two years of trial and error, working with every system and structure you can imagine, we built our own solution.

The GenAI Launchpad is the result of our journey — a project repository that streamlines everything from initial setup to deployment, ready to handle the demands of production at scale.

And the time savings? ⏳

We’ve calculated that it saves us over 50 hours per project on average, so we can dive right into the creative work that actually advances AI.

Today, we’re launching the GenAI Launchpad to share that time-saving power with you — our community of fellow AI enthusiasts and builders.

This is more than just a repository; it’s a battle-tested, engineer-approved blueprint that I wish I’d had when we started.

It’s here to help you skip the headaches, bypass the boilerplate, and focus on what matters: building innovative AI solutions for real-world problems.

If you’ve ever spent weeks fighting project setup, only to finally reach the real work, then you’ll understand why I’m so excited to share this.

👉🏻 Check it out on Product Hunt today:
www.producthunt.com/posts/genai-launchpad

If you’re curious to see what it’s all about or just want to support our work, I’d love for you to check out the page.

And if you’re already active on Product Hunt, it would mean a lot if you’d drop by to share your feedback or leave a comment!

1 year ago (edited) | [YT] | 86

Dave Ebbelaar

When I hit ‘record’ for the first time, I had no idea it would lead to this...

But it was one of the best decisions I've made.

It’s hard to believe, but I've just hit 100,000 subscribers on YouTube! And I want to share a bit of that journey with you.

My love for making videos started way back when I was just 10 years old. Me and my friends would grab whatever camera our parents had laying around and started creating all kinds of short movies.

By the time I was 16, I turned that passion into my first “business” as a freelance videographer.

But then, as I transitioned into full-time freelancing as a data scientist, I started to miss making videos.

And that’s how this YouTube channel was born, about 2.5 years ago.

It started with the idea of filling a gap I had noticed for a long time.

So many AI/ML tutorials out there were either overly complex, boring, or poorly produced.

I wanted to create practical, simple-to-follow tutorials that get straight to the point.

Now here we are, 100K strong.

I’m grateful for every single one of you who’s been part of this journey.

How long have you been following the channel? And what keeps you coming back to watch my videos?

I’d love to hear from you!

1 year ago | [YT] | 234