About this episode

The episode explores the insights gained from small language models in understanding AI, featuring a discussion with Gwyneth Peña-Sigüenza about her journey and the implications for education.

What can small language models teach us that the largest AI models cannot? Kelly and Julian are joined by Microsoft Cloud Advocate Gwyneth Peña-Sigüenza to explore why working with small language models (SLMs) may be one of the best ways to understand AI. Rather than relying on increasingly capable models that hide complexity, Gwyneth argues that constraints build stronger fundamentals. From prompt engineering and context management to deployment and security, SLMs force learners to think more carefully about how AI actually works. The conversation extends beyond AI models into learning itself. Gwyneth shares her self-taught journey from growing up on a remote farm in Ecuador with limited internet access to becoming a Microsoft Cloud Advocate and creator of the Learn to Cloud platform. Along the way, the group discusses productive struggle, mentorship, cloud engineering, Python, security, and what educators should prioritize as AI becomes part of every student's learning experience. The episode closes with a thoughtful discussion about AI dependency, judgment, and whether we would actually flip the switch and turn AI off if given the choice. Show Notes Wins of the Week Gwyneth…

People in this episode

Hosts: Kelly Paredes, Julian

Guest: Gwyneth Peña-Sigüenza

Topics covered

• small language models
• AI understanding
• learning journey
• cloud engineering
• education
• AI dependency

Keywords

• small language models
• AI
• cloud engineering
• education
• mentorship
• Python
• security

Mentioned in this episode

Organizations: Microsoft

Places: Ecuador

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