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[ARTICLE · art-89547] src=laurentiugabriel.github.io ↗ pub= topic=generative-ai verified=true sentiment=↑ positive

How I use LLMs to learn complex topics

Laurentiu Gabriel, an engineer, developed ChipTycoon, an interactive low-poly simulation that teaches chip manufacturing by guiding a cart from sand collection to final chip delivery, using LLMs to build and review the knowledge base and generate the animation. The tool, available at https://laurentiugabriel.github.io/ChipTycoon/, aims to make learning complex topics more engaging and accurate, with plans for enhancements like 3D object mapping and interactive challenges.

read3 min views1 publishedAug 9, 2026

LLMs are used for any things. Learning new things is one of the top use cases.

Many engineers I know use generative AI for many functions, like building PoCs, internal tools or dashboards, or even learning new stuff. I personally find the style used by LLMs to explain things difficult to follow. It's just too simplistic and depending on the number of emojis used, a bit annoying too.

While I was analyzing new AI bottlenecks that might slow down data center buildup, I realized there are many aspects of chip production that I do not know. Surfing the web, I asked myself what if there would be a game to get you through the process of building a chip at a fab? For sure learning this way will stick, since you can map concepts with objects within the game. This is when I decided to try it, and it actually turned out really well.

The flow #

Instead of just asking AI to explain a topic, I use the following flow:

  • In plan mode (using CC, or OpenCode) I ask a model to build the foundational knowledge for X topic.
  • I ask it to review the accuracy of the knowledge base it built in the previous step.
  • I proceed asking it to build a simulation of that topic in a low-poly, Rollercoaster Tycoon-like animation. I add some UX elements as well, like the page needs to be visible on both large and small screens, have controls to stop the flow whenever I want etc.
  • I then push it to a new repo and enable GitHub Pages for it.

The result #

What you get is a beautiful animation that is 100% accurate and free of hallucinations. For me, this method works a lot better than just reading endless materials that I find on Google, or trying to digest a bulleted list that is spat by a language model.

I've done this specifically for learning chip building and launch it under this website: ChipTycoon. You get to follow a cart from the moment when sand is collected, to the moment when a chip is finalized and delivered to a data center.

Visually, you can follow the cart and see how it changes too. Since it's low-poly, the details might be missing, but it's still a good indicator for showing how the product changes once it goes through the many steps required in the manufacturing process.

How to improve it further #

Let's say that the low-poly design requires to much immagination to actually visualize what happened to the quartz sand pile after it left the furnace. To transform this into a more realistic representation, you can use my skill for transforming pictures into 3d objects, and map the resulting objects to your simulation. This way you get more accurate design.

Also, you can add challenges to your simulation too. Trying to answer questions about a previous step in the chip manufacturing process will help you retain the knowledge tremendously. Add intuitive puzzles too that will help you learn even better.

Check out what other pages I created:

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