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How Software Engineers and Students Use AI to Move Faster than Ever (without breaking things)
The “AI revolution” is really augmented intelligence: humans + tools. super{set} backs teams that are AI-native—putting AI at the core, not as an add-on. For students, the risk is either over-relying on AI (and skipping fundamentals) or under-using it (and falling behind). Universities should teach both rigorous reasoning and modern AI workflows. For developers, agentic tools (e.g., Cursor, Copilot) turn one engineer into a mini dev team—automating boilerplate, tests, docs, and legacy audits—so humans can focus on architecture, edge cases, and creative problem-solving. AI won’t erase jobs; it shifts them, rewarding those who adapt. The near future belongs to builders who pair deep software craft with AI fluency.

The prettifying and securing of downtown San Francisco, where super{set} is headquartered, should be the norm - not just for special state visits from the world's dictators. Here are 3 things the city of San Francisco should be doing all year round to make the city better to live, work, and invest in. Read Tom Chavez' latest in Forbes.
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Pankaj Rajan, co-founder of MarkovML, joins super{set} Chief Commercial Officer Jon Suarez-Davis (jsd) to discuss the role of data in gaining a competitive advantage in the AI revolution. Learn the difference between optimizing models and optimizing data in machine learning applications, and why effective collaboration will make or break the next-gen AI applications being created in businesses.

It's still early for the startup studio asset class - and we hear misconceptions about the studio model every day, ranging from the basic confusion of accelerators versus studios to downright incorrect assumptions on our deep commitment to the build-out of every company. Read Tom Chavez' latest in Forbes.
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