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This case study demonstrates how integrating commercial AI IDEs like Cursor into a forced rewrite allowed a 12-person team to deliver nine months of work in five and a half months. By shifting from manual migration to AI-assisted generation, the organization effectively doubled its engineering output while maintaining critical workflow stability for internal developer tools. The results provide empirical evidence that AI can significantly compress SDLC timelines during mandatory infrastructure overhauls without requiring custom-built models.

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Rebuilding PubHub: How AI-assisted development shipped a mandatory rewrite 3.5 months early – Part 1

Cisco Blogs19 octombrie 20266 min de cititArticolul și perspectiva sunt în engleză.

A security mandate forced a PubHub rewrite. AI-assisted development helped 12 engineers deliver nine months of work in about five and a half. Here is the sequence that worked.

Part 1 of a short series on rebuilding PubHub with AI-assisted development. This part covers the decisions and results; the engineering detail lives in the companion AI for SDLC series. In early 2026, a security mandate forced the PubHub team to rebuild on a new stack, and the plan allowed nine months. It shipped in about five and a half using AI-assisted development: 12 engineers producing the output of about 20. PubHub is the publication tool behind Cisco DevNet’s developer content: API documentation, Learning Labs, DevCenters, and Microsites, for the teams who create it and the developers who use it. Authors depend on it daily. Nobody asks for a rewrite of something that already works, and nobody forgives one that breaks…

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