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LLMs are all the vibe… but what’s next?
- The writer reminisces about starting with BASIC programming language before moving on to Pascal, C, and later Java.
- Programming languages allow for different forms of expressiveness and design choices.
- With the shift to AI-native development, coding is moving away from traditional methods.
- AI and large language models (LLMs) are excelling at generating code efficiently.
- Prompting is becoming an alternative to traditional coding, blurring the lines between human input and machine output.
- The predictability and determinism of LLM-generated code differ from traditional programming, posing challenges and opportunities.
- The evolution towards prompting frees humans to work at higher levels of abstraction.
- As LLMs become more autonomous, the intimate relationship with code may change, leading to potential shifts in code generation methods.
- There is a growing focus on energy-efficient LLM-generated code and the optimization of code generation processes.
- The future may see a transition to LLM-optimized code, potentially marking a significant shift in human-computer interactions.
- The transformation towards LLM-optimized code raises questions about trust, human understanding, and the implications for society.
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