Why 90% of AI Projects Go Unnoticed (And How to Fix It)

Includes a step-by-step Google Doc to turn your idea into a career-making AI project.

PART 1: The Diagnostic (Why Most Projects Stay Invisible)

The Illusion of Value

You spent weeks (or months) building your AI project. You cleaned the data, tried five models, built a UI. But when you publish it, there's no reaction. Why?

Most AI projects fall into what I call the illusion of value. You think it’s valuable because it’s complex, technical, or clever. But value isn’t determined by you. Value is determined by the pain it solves for someone else.

You don’t get hired because you know Hugging Face or can fine-tune a transformer. You get hired because someone believes you can help solve their real problems,

faster, better, or cheaper.

And here’s the kicker: if you don’t start with the pain, you won’t accidentally land on something valuable. You’ll just build a beautiful toy.

The 3 Visibility Killers

1. Model-first Thinking: You start with a model you want to try, not a problem that needs solving. This turns projects into demos, not solutions.

2. Portfolio FOMO: You build what others are building (e.g., movie recommenders, sentiment classifiers), hoping it will "look good." But hiring managers have seen these 100 times. They blur into the noise.

3. Tech-as-Signal: You use tools as proof of skill, instead of using projects as proof of impact. Recruiters don’t remember your tech stack they remember whether you solved something real.

All three create projects that say: "Look what I built!" instead of: "Look what problem I solved."