AI has evolved from extracting information, like in image recognition, to creating new content, which is a fundamental shift for technology.
ChatGPT is a large language model that predicts text but cannot perform actual computations, making it a powerful yet fallible tool for developers.
ChatGPT can quickly analyze obfuscated code, refactor it for readability, and even convert it from JavaScript to TypeScript.
The model can deconstruct and explain existing regular expressions and generate new ones for tasks like validating phone numbers, though with varying accuracy.
While ChatGPT can generate standard algorithms like quicksort, it often makes mistakes with implementation details like memory complexity and struggles with novel logic problems.
Providing a unit test as a prompt can guide the AI to generate the correct function implementation, demonstrating a test-driven development workflow.
Advanced prompting techniques can make the AI act as a prompt engineer to refine your requests or even simulate complex systems like a SQL database server.
AI capabilities are integrated into developer tools like GitHub Copilot for IDE assistance, AIaC for generating Terraform code, and even a new version of Clippy.
To use AI effectively, be specific with prompts, always validate the output for correctness and security, and treat it as a powerful but fallible tool.
58:06Anna Fritsch-Weninger
31:39Rainer Stropek
25:17Scott Hanselman
39:11Thomas Dohmke
32:26Krzysztof Cieślak
41:06Pascal Reddig, TJ Griffiths, Fabian Schmidt, Oliver Winzenried & Matthias Niehoff & Mirko Ross
35:37Liran Tal
24:51Simon Müller
Jobs that call for the skills explored in this talk.
DTS Systeme GmbH
GUS Germany GmbH