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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.
Othmane Rifki, Principal Applied Scientist at super{set} company Spectrum Labs, reports from the session he led at super{summit} 2022: "When Inference Meets Engineering." Using super{set} companies as examples, Othmane reveals the 3 ways that data science can benefit from engineering workflows to deliver business value.
o11y - What is it? Why is it important? What are the tools you need? More importantly - how can you adopt an observability mindset? Habu Software Architect Siddharth Sharma reports from his session at super{summit} 2022.
The era of easy money - or at least, easy returns for VCs - is over. Tom Chavez is calling for VCs to show up in-person at August board meetings, get off the sidelines, and start adding real value and hands-on support for founders.
Gal Vered of Checksum explains his rationale for leaving Google to co-found a super{set} company.
Reflections after a summer as an engineering intern at super{set}
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