NELL AI Labs Shows UTD Students What’s Worth Building in AI

Last week, NELL AI Labs visited UT Dallas for a workshop that gave students a practical framework for creating AI projects with real-world impact. The session was not about hype or abstract concepts; it was about turning curiosity into action and understanding why some ideas are worth building while others are not.

NELL AI Labs: https://nellailabs.ai/

NELL AI Labs is an AI-native operating company built on four key pillars: engineers who embed with partners to ship production systems, a community of builders learning from real customer signals, in-house SaaS products that double as live laboratories, and a strategic portfolio that improves outcomes through their operating work. These pillars are not just buzzwords; they are the foundation of how NELL approaches building and validating ideas.

The session began by tackling the most overlooked question in AI development: what is worth building? Students learned that while it has never been easier to build thanks to tools like GitHub and AI coding assistants, the real challenge is deciding what deserves your time. NELL shared key data to back this up. GitHub now hosts over 225 million developers, and by 2026, 90% of professionals will use AI coding tools weekly. Despite this accessibility, many projects fail because they lack market need or are packed with features that users rarely touch.

NELL’s framework breaks down the process into four clean steps:

1. **Find a real pain and score it before you build** Start with a problem you already live with and pressure-test it across five dimensions: problem, market, competition, demand, and timing. This ensures you know your biggest unknowns before diving in.

2. **Get a build brief as a paste-ready prompt** NELL helps write the specs, tailored to the hours you have and your academic schedule.

3. **Build it in your own tool** The brief works with whatever platform you already use, such as Claude Code, Cursor, Replit, or v0, and pushes the project to a repository you own.

4. **Put it in front of real users and log their feedback** The goal is not a polished demo but evidence that people actually want to use what you have built.

This framework resonated with students, especially one detail that got a visible reaction. Every brief NELL provides tells the AI tool, “I am a student, so do not build all of this for me.” Certain parts are deliberately marked for the student to complete themselves. The goal is to ensure students understand their projects deeply enough to explain them without relying on an internet connection.

The session also struck a chord with students because NELL grounded its advice in numbers that reflected the realities they face. Entry-level hiring at major tech companies has declined sharply since 2019. Certificates and toy projects are plentiful proof of knowledge, but they rarely stand out. A live product with logged user interactions and real testers is proof of doing, which is significantly rarer. This kind of tangible evidence is exactly what NELL helps students produce, and you could see students doing the math on how it would strengthen their internship applications or first job prospects.

By the end of the session, students left with more than just ideas; they left with a clear path forward. A student who completes a term with NELL walks away with:

- A live product users can interact with - 10+ user conversations, 5+ testers, and 3 iterations, all documented - A case study, demo video, and build-in-public posts - A shareable completion record with a certificate ID - Prepared answers to recruiter, engineer, and investor questions

This is not theoretical. It is a portfolio, a story, and proof that the work was real. These deliverables are exactly what the data suggests the first rung of opportunity now demands.

The energy in the room after the session said it all. Students stayed behind to discuss their own ideas, shared the tools they already use, and asked how soon they could start testing their first projects. Several were already sketching out problems to validate. That kind of momentum is what you want in a room full of builders — not “that was interesting,” but “how do I start?”

Starting is refreshingly simple. NELL offers a free Playbook that lets students bring a problem, run it through their Quick Validate tool, and take the brief into their AI platform of choice in a single sitting. Scoring an idea and refining an existing Playbook are free as well, making it easy for students to get moving without financial barriers.

We are grateful to the NELL AI Labs team for sharing their time and insights with our students. They offered something far more valuable than hype: a clear-eyed view of where opportunities in AI have shifted and how to meet them. We are excited to see what this group of students builds and look forward to having NELL back for future sessions.