| ▲ | curt15 5 hours ago | |||||||||||||
The people reaping AI's benefits today generally developed their skills as juniors through old-fashioned struggling in the pre-ChatGPT era -- actually reading docs and articles, trial and error, puzzling over mysterious bugs, and generally doing lots of mental lifting. How will skill building happen when LLMs and coding harnesses seemingly provide all the answers at one's fingertips? | ||||||||||||||
| ▲ | sieve 2 hours ago | parent | next [-] | |||||||||||||
> How will skill building happen when LLMs and coding harnesses seemingly provide all the answers at one's fingertips? They don't provide all the answers. And are often wrong/mistaken. But they also produce stuff faster than you can consume it. This is great for when you know exactly what you want and can cheaply test the output and guide the LLM to the right solution. It is expensive (in developer hours) in other cases. I have been building a new PL+VM this year and had to pause development on a few occasions because I have not had the time to go through the implementation because there are so many modules. But smaller tools (5-10KLOC), you can judge fairly quickly. So, the answer to your question is: people need to discover the strengths and weaknesses of the tool on their own, decide what kind of expertise they want to attain, and if it is worth the effort. | ||||||||||||||
| ▲ | __mharrison__ 4 hours ago | parent | prev | next [-] | |||||||||||||
That's a great question. I don't know what the future will be like, but looking into my crystal ball, I'm not seeing much hand-generated code. Very little (or no) human code review. Having the taste and business sense to develop the right thing will be important. If it stops working, ask the AI to fix it. | ||||||||||||||
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| ▲ | OroPla 3 hours ago | parent | prev [-] | |||||||||||||
How will people learn to ride horses, when everyone drives a car? They generally won't, because that is now obsolete. | ||||||||||||||
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