We spoke with 3 engineers to ask the blunt question: is AI making junior developers better or just faster at shipping code?
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Jordan Topoleski (COO, Cursor) and Pallavi Mahajan (CTO, Nokia) made the case that the next real breakthrough in AI development is agent orchestration.
AI agents are already being trusted with real work, but handing them raw credentials is a dangerous shortcut. That's why the next security challenge is controlling what an agent can do once it gets access.
Dana Lawson argues that AI has lowered the barrier to software development so much that the best way to learn is by building, shipping imperfect apps, and improving them along the way.
We make many mistakes with MCPs, but one of the biggest is treating them like a 1:1 REST API mapping - when in reality, an MCP tool should be a capability, not just another endpoint.
Mike Chambers, Developer Advocate at AWS, says the real test of AI is not whether a demo looks smart, but whether the system around it can survive real-world use.
Engineering teams are starting to resemble legacy Java apps hitting thread exhaustion. I believe change is unavoidable, and we need a better way to organize the work.
Everyone is busy asking how big the model is, but the real question is what you fed it first - because if your PDFs are mangled and your OCR is sloppy, even the smartest LLM starts from the wrong answer.
The jump from mid-level to senior engineer is often framed as a technical one. Michelle Brenner says the real difference is judgment: understanding the business, making pragmatic trade-offs, and knowing when to ask for help.
I let the dust settle, and this is what I think: regular apps usually need teams of dozens to ideate, build, and test before they ship. Odysseus, PewDiePie’s new AI platform, doesn’t - at least, not in the usual way.