A Thought-Provoking Perspective on the Future of Coding

Aadit Sheth posted the following Twit on July 22:

"trend: 90% of your code will be written by ai.

the best coders of tomorrow won't know how to code.

sounds crazy, right? but hear me out.

the future of coding isn't about knowing every syntax or algorithm. it's about knowing how to guide AI to do it for you.

think about it:

• we don't memorize phone numbers anymore. we let our phones do it.
• we don't navigate with maps. we let gps do it.soon,
• we won't write most of our code. we'll let AI do it.

BUT: this doesn't make coders obsolete. it makes them more powerful.

the best coders of tomorrow will be:

1. prompt engineers: crafting the perfect instructions for AI
2. architecture visionaries: seeing the big picture AI can't grasp
3. AI collaboration experts: knowing when to code and when to delegate to AI
4. creative problem solvers: tackling issues AI can't comprehend

in this new world:

• coding bootcamps might teach "AI whispering" instead of python
• github repositories could be filled with prompts rather than code
• debugging might mean refining prompts, not fixing syntax

it's not about knowing how to code. it's about knowing how to think.

the irony? by "not coding," these future coders will build more complex, powerful systems than ever before."

Interesting thought!

I wanted to hear the honest opinion of the latest Llama AI model about this statement. And this is its answer:

A Thought-Provoking Perspective on the Future of Coding

The statement presents a compelling argument about the evolving role of coders in an AI-driven world. Here's my honest opinion:

Key Takeaways:

• AI will indeed write a significant portion of code: With advancements in AI, a large percentage of code will likely be generated by machines.
• Coders will focus on higher-level tasks: The best coders will concentrate on guiding AI, architecting systems, and solving complex problems that require human creativity and intuition.
• New skills will emerge: Prompt engineering, AI collaboration, and creative problem-solving will become essential skills for coders.
• Coding boot camps and education may need to adapt: The focus might shift from teaching specific programming languages to instructing students on how to effectively work with AI.

Strengths of the Argument:

• Analogies to other industries: The comparisons to phone numbers and GPS navigation effectively illustrate how technology can augment human capabilities.
• Emphasis on human-AI collaboration: The statement highlights the potential for AI to enhance coders' productivity and capabilities.

Weaknesses and Considerations:

• Overemphasis on AI capabilities: While AI will undoubtedly play a significant role, it's crucial to acknowledge the limitations and potential biases of AI-generated code.
• Need for foundational knowledge: Understanding the basics of coding and computer science will still be essential for effective AI collaboration and troubleshooting.
• Potential job displacement: The statement downplays the risk of job displacement for some coders, particularly those who focus on routine or repetitive tasks.

Conclusion:

The statement presents a thought-provoking vision of the future of coding, where AI and humans collaborate to build complex systems. While there are valid points and potential benefits, it's essential to consider the limitations and challenges associated with this transition. By acknowledging both the opportunities and risks, we can work towards a future where AI enhances the capabilities of coders, rather than replacing them.

Amazing!