Large Language Models (LLMs) have the potential to fundamentally change software engineering. They are highly useful in programming, providing autocomplete, generating code, and improving documentation. Working with LLMs can lead to shifts in software architecture, system architecture, programming practices, communication patterns, and organizational structures. The use of LLMs allows for faster code development, exploration, and prototyping, as well as continuous code review and tool building. However, there are also concerns around the quality and validity of code generated by LLMs.

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My background is in system programmingCopilot my uncanny autocompleteStochastic parrots, valid code?Aside #1: Helping Copilot output valid codeMethodology shift #1: writing documentationMethodology shift #2: Whiteboarding and rubberduckingMethodology shift #3: Build more prototypesMethodology shift #4: Build more toolsAside #2: Fundamentals will probably be just as criticalMethodology shift #5: Continuous code reviewMethodology shift #6: Cognitive impact of using LLMsConclusion
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