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An example of LLM prompting for programming

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Re: An example of LLM prompting for programming

#31

Post by ben_w »

notacoward wrote: post #22
nextworddev wrote: post #18

Earlier quoted context omitted.

The opposite might be true, and here’s why - 1) by using English as spec, the barrier of entry has gone lower, 2) LLMs can also write prompts and self introspect to debug.

> LLMs can also write prompts and self introspect to debug. Why should we assume that won't lead to a rabbit hole of misunderstanding or outright hallucination? If it doesn't know what "correct" really is, even infinite levels of supervision and reinforcement might still be toward an incorrect goal.

To which the normal response[0] is: that's just like humans.

Of course, it's still bad that humans do it; but despite the scientific method etc., even successful humans often work towards an incorrect goal.

[0] I am cultured, you're quoting memes, that AI is just a stochastic parrot: https://en.wikipedia.org/wiki/Emotive_conjugation

Re: An example of LLM prompting for programming

#32

Post by SanderNL »

themodelplumber wrote: post #25
SanderNL wrote: post #19

Earlier quoted context omitted.

Except you now have a way “upwards” from an abstraction POV. Regular code is severely limited and highly surgical, by design. This is not. All these abstraction layers were invented to serve old style manual coders. Why bother explaining in great detail about “Konva” layers and react anymore? Give it a few years and let it finetune on IT tech and I see this being reduced to “I want whiteboard app with X general chara…

That "upwards" excludes a lot of relevant systems design logic that won't go away though, insofar as it is abstraction ad infinitum in the direction of fewer-relevant-details. What'll happen is, details will continue to be relevant as tastes adjust to the new normal. Like for my work, today, React is enterprise-ready, which is not good for me. It means it will likely dip my projects in unnecessary maintenance costs a…

Fair enough, but don’t we abstract “upwards” all the time? Assembly won’t go away, but do you deal with it?

Re: An example of LLM prompting for programming

#33

Post by ben_w »

mooreds wrote: post #24
nextworddev wrote: post #18

Earlier quoted context omitted.

The opposite might be true, and here’s why - 1) by using English as spec, the barrier of entry has gone lower, 2) LLMs can also write prompts and self introspect to debug.

> by using English as spec, the barrier of entry has gone lower, I'm not sure that is true. The level of back and forth and refinements needed indicate to me that the "English" used is not the normal language I use when talking to people. It's almost like a refined version of cucumber with syntax that is slightly more forgiving. Maybe I'm being a codger, but LLMs seem (at least for now) far better for summarizing and…

> It's almost like a refined version of cucumber with syntax that is slightly more forgiving.

I don't know if "cucumber" is autocorrupt or an actual non-vegetable thing; can you clarify?

Re: An example of LLM prompting for programming

#34

Post by mov_eax_ecx »

How to overengineer with an LLM, don't state clearly the requirements, shove your pet patterns first, it is more important to follow the slice redux awareness hook than to have working solution, never trust your developers to make decisions, worry more how it is built than building a solution.

My way to work with an LLM is to have a good, clear requirement and make the LLM write a possible file organization and query the contents of each file, just the code no comments and assemble a working prototype fast, then you can iterate over the requirements and evolve from there.

Re: An example of LLM prompting for programming

#35

Post by amelius »

What I want is a prompt that continuously copies whatever I'm doing, so I can ask to complete the task.

For example, say I'm converting all identifiers in a file from lowercase to CamelCase. Then after doing like 3 of them, I can ask the LLM to take over and do the remainder.

Re: An example of LLM prompting for programming

#36

Post by omnicognate »

ben_w wrote: post #33
mooreds wrote: post #24

Earlier quoted context omitted.

> by using English as spec, the barrier of entry has gone lower, I'm not sure that is true. The level of back and forth and refinements needed indicate to me that the "English" used is not the normal language I use when talking to people. It's almost like a refined version of cucumber with syntax that is slightly more forgiving. Maybe I'm being a codger, but LLMs seem (at least for now) far better for summarizing and…

> It's almost like a refined version of cucumber with syntax that is slightly more forgiving. I don't know if "cucumber" is autocorrupt or an actual non-vegetable thing; can you clarify?

https://cucumber.io/

That "did they actually mean that or was it autowrong?" feeling is going to get worse I fear.

Re: An example of LLM prompting for programming

#37

Post by mjr00 »

ben_w wrote: post #33
mooreds wrote: post #24

Earlier quoted context omitted.

> by using English as spec, the barrier of entry has gone lower, I'm not sure that is true. The level of back and forth and refinements needed indicate to me that the "English" used is not the normal language I use when talking to people. It's almost like a refined version of cucumber with syntax that is slightly more forgiving. Maybe I'm being a codger, but LLMs seem (at least for now) far better for summarizing and…

> It's almost like a refined version of cucumber with syntax that is slightly more forgiving. I don't know if "cucumber" is autocorrupt or an actual non-vegetable thing; can you clarify?

Not a typo.[0]

In the 00s/early 10s, software went through a fad phase where people earnestly thought that by implementing Gherkin frameworks like Cucumber, you'd be able to hand off writing tests to "business people" in "plain English." It went about as well as you'd expect.

[0] https://cucumber.io/docs/gherkin/

Re: An example of LLM prompting for programming

#38

Post by gwright »

ben_w wrote: post #33
mooreds wrote: post #24

Earlier quoted context omitted.

> by using English as spec, the barrier of entry has gone lower, I'm not sure that is true. The level of back and forth and refinements needed indicate to me that the "English" used is not the normal language I use when talking to people. It's almost like a refined version of cucumber with syntax that is slightly more forgiving. Maybe I'm being a codger, but LLMs seem (at least for now) far better for summarizing and…

> It's almost like a refined version of cucumber with syntax that is slightly more forgiving. I don't know if "cucumber" is autocorrupt or an actual non-vegetable thing; can you clarify?

https://cucumber.io/docs/guides/overview/

Re: An example of LLM prompting for programming

#39

Post by chrisco255 »

> He's using a generic application example in here: one thing to be wary of when interacting with ChatGPT and the like is that we should never put anything that may be confidential into the prompt, as that would be a security risk. Business rules, any code from a real project - all these must not enter the interaction with ChatGPT.

Remember, when storing your business code on Github servers hosted by Microsoft, it is important to not place real code from a project into OpenAI servers hosted by Microsoft. That would be a security risk.

Re: An example of LLM prompting for programming

#40

Post by nbzso »

Useful for form of learning and experimentation. Not applicable, in my view, at all due to lack of ownership of the generated code. There is no ability to copyright and protect the intellectual output from generative AI processes.

Even when your prompts are clearly the pseudocode which creates the scope of the generated response. Until this situation is legally cleared, I will be very cautious to include LLM's outside rapid prototyping and conceptual phase. Not to mention the madness of AutoGPT or more realistic approach of LangChain.

It is early in the game and the Hype train is riding more rapidly than crypto and web3 combined.

I see a lot of AI startups introducing the same capabilities through OpenAI API and prompts, without consideration of prompt injection risk. So we will see who will survive.

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