Before building an AI feature, ask one question: could this ship free in a model update next year? If yes, it is not the product.
For anyone deciding what to build next, capstone or company. A creator's post makes the case: most agents and workflows being built now will arrive as ordinary features within a year, from the model makers. Yet there is still value in building AI features fitting exactly your needs. Creating your own AI assistant from scratch captures nuances that mix-and-mashing commercial AI products can't always catch.
In response to strong demand, we are running the NVIDIA AI Developer Bootcamp, an NVIDIA-certified workshop, in partnership with De La Salle University, Manila.
It runs three days and stays hands-on throughout:
1. Deep learning fundamentals. The core techniques and tools, worked through rather than lectured.
2. Data types and model architectures. Practice with the kinds you will actually meet at work, not textbook cases.
3. Transfer learning. Building a model by starting from one that has already learned the general patterns and adapting it to your own data, which is how most working models get built today.
Participants who complete all three days receive an NVIDIA certification.
When: 9 to 11 October 2026, Friday to Sunday, 9 AM to 6 PM
Where: De La Salle University, Manila
What does not get absorbed. Your data and your customers' history, organised for a model. The rules of your industry. No update ships with those.
A quick test. For each of the next three roadmap items, ask what a competitor needs to copy it. If an API key and a weekend, it is a feature. If data someone spent years collecting, it is a product. Expect one item to fail, often the one with the nicest demo.
A capstone is allowed to be a feature. A company's product is not.