You built a movie recommendation system because you love movies, and then you almost let three LinkedIn posts convince you it wasn't enough. That's the real problem here, and it's not your coding skills. You saw other people's projects labeled "AI" and immediately assumed your work was lesser, when in fact you had already implemented collaborative filtering, content-based filtering, popularity-based ranking, and a preference-based interactive mode. That's not a toy. That's a portfolio piece with genuine technical range.
Here's what you need to hear: the label "AI" on someone else's project doesn't automatically make it more impressive than yours. Many of those projects are shallow wrappers around a pre-trained model or a single API call. You built a system from the ground up, using matrix factorization, TF-IDF, cosine similarity, and a weighted ranking formula. You made design decisions. You solved real problems, like how to blend different recommendation strategies. That's the kind of work that demonstrates understanding, not just usage. And when you post about it, that understanding is what you lead with.
The demotivation you felt comes from comparing your project's surface-level buzzwords to someone else's. But your project has something those flashy posts often lack: a clear user problem. You like movies. You built a tool that helps you find more of what you like. That's not a small thing. It's the difference between building for a checklist and building for a person. When you share this on LinkedIn, you don't need to apologize for not calling it "AI." You need to explain the thinking behind your choices. Show the trade-offs between collaborative and content-based filtering. Explain why you used TF-IDF on metadata instead of a neural network. That's what makes someone look like a capable developer, not the word "intelligence" in a title.
So, is your project decent enough to showcase? Yes, and you already know that. The question you're really asking is whether you should chase whatever you think recruiters want. Don't. Instead, take what you have and make it better in a way that only you can. Add a feature that reflects your taste in movies. Write a short breakdown of one algorithm and how you tuned it. That kind of depth will do more for your confidence and your credibility than pivoting to a generic AI project just to keep up. You already did the hard part. Now own it.