06.12.2025 –, Main Stream Sprache: English
Abstract
Don't Be Everything to Everyone: The Case for Career and Model Specialization (Small Language Models)
We’ve all heard the advice: “Be versatile, keep your options open.” But here’s the twist — whether you’re building a career or building a language model, trying to be everything to everyone is a recipe for burnout and bloat. The real magic happens when you specialize.
This keynote makes parallels between professional growth and AI design:
- 🎯 Sovereignty of your stack: Just like owning your career path, owning your open-source tools gives you freedom, resilience, and a little swagger.
- 🔄 Small iterations, big wins: Careers aren’t built in one giant leap, and neither are models. Iteration is the secret sauce that compounds into mastery.
- ⚡ Efficiency through expertise: Specialists — human or machine — don’t waste energy chasing every problem. They focus, optimize, and deliver outsized impact.
Think of it as a pep talk for both your résumé and your repo. By the end, you’ll see why the future belongs to those who go deep, not wide — and why small, sharp models (and careers) punch way above their weight.
Why specialize? Because neither your résumé nor your language model should try to do everything. This keynote makes the case for going small and going deep — showing how sovereignty, iteration, and expertise create careers (and models) that not only meets the brief, but helps uncover innovations in your career and your domain analysis.
Think of it as a pep talk for both your résumé and your repo.
It draws on my personal experience as a consultant, software engineer, analyst, developer relations engineer, manager, self-taught programmer and self-proclaimed "jack of all trades" -- now deeping expertise in data science and machine learning, where I can share what I've learned in the value of specialization.
Dawn Gibson Wages is a software engineer, ethical open source advocate, and community leader. She is the former Chair of the Python Software Foundation (volunteer) and currently works as Director of Community and Developer Relations at Anaconda, the largest scientific Python distribution in thr world. Her deep investment in the community is spent championing inclusive practices and sustainable growth in open source ecosystems. Dawn’s work bridges technical expertise with a commitment to equity, sovereignty, and collaboration in the developer community.
When she's not working in the Python ecosystem, she is watching Star Trek in Philadelphia with her wife and two dogs.