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Developing a mature AI-first software development (AIFSD) practice involves shaping how AI participates in engineering work. Models provide capabilities, while agent harnesses support tool use, context management and execution. Developers also define their engineering practices: how requirements are understood, knowledge is captured, implementation proceeds and results are verified. We call these practices workflows.
In April 2021, our China-based team working on an Australian project discovered that the E2E test deployed in AWS Sydney was giving out a lot of time calculation errors. Day.js, the Datetime Utils calculation tool that had been stable for six months, had started behaving abnormally overnight. Turns out that Day.js had stopped working when time changed to AEST (Australian Eastern Standard Time). Strict time format requirements only compounded our problems.
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