Google Skills: Free AI Education at Scale

Google made waves today by launching Google Skills, a platform consolidating over 3,000 AI courses from DeepMind, Google Cloud, and Google Education—completely free for Google Cloud users.

As one observer put it:

"Google just made every $50K master's degree look like a scam."

The platform includes content from DeepMind itself, offering the kind of cutting-edge AI education that universities typically charge tens of thousands of dollars for. This move signals Google's aggressive push to democratize AI knowledge and likely grow their cloud ecosystem by creating a generation of developers trained on their tools.

Why this matters: The traditional higher education model for tech skills has been under pressure for years, but having a major AI lab offer their internal training materials for free could accelerate the shift toward alternative credentialing. Companies may increasingly value practical skills demonstrated through projects over expensive degrees.

Karpathy's GPT-5 Pro Workflow

Andrej Karpathy, former Tesla AI Director and OpenAI researcher, shared insight into how he uses frontier models in his daily work:

"State-of-the-art model that I go to is the GPT-5 Pro...a very powerful model. If I have 20 minutes, I will copy-paste my entire repo and I go to GPT-5 Pro, the oracle, for some questions. Often it's not too bad and surprisingly good compared to what existed a year ago."

Karpathy's description of GPT-5 Pro as "the oracle" is telling—it suggests a workflow where the most capable models serve as high-context consultants rather than line-by-line coding assistants. The ability to ingest an entire repository and provide coherent answers represents a significant capability jump.

The takeaway: Even AI researchers at the frontier are finding practical value in these tools. The "copy-paste my entire repo" approach shows that context window improvements have fundamentally changed how developers can interact with AI assistants—moving from small snippets to holistic codebase understanding.

Looking Ahead

Today's posts highlight two parallel trends: the democratization of AI education and the increasing sophistication of AI as a development tool. As training becomes more accessible and tools become more capable, the barrier to entry for AI development continues to drop while the ceiling for what's possible keeps rising.