🤖 AI Summary
Atlassian CEO Mike Cannon-Brookes told the 20VC podcast that despite the rise of “vibe coding” (AI-assisted coding), his company is planning to hire more — not fewer — engineers over the next five years. He argued that technology creation isn’t output‑bound and that new ideas will continue to generate demand for human builders. Atlassian, known for Jira, reported about 13,813 full‑time employees as of June (roughly 14% growth year‑over‑year) and is hiring more new grads this year than in 2023 or 2024 to staff R&D and engineering teams.
The broader implication for AI/ML and software orgs is pragmatic: AI tools can boost developer efficiency but don’t eliminate the need for engineers who design, review, test, debug and maintain systems — especially as AI-generated code can introduce complexity and technical debt. Other industry voices (Windsurf’s cofounder, former OpenAI research chief Bob McGrew) echo this view, stressing that understanding and owning a codebase remains critical. For teams, that means investing in developer talent, onboarding, and governance to reap AI productivity gains while managing risks around maintainability, correctness and long‑term system design.
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