The new skill in AI is not prompting, it's context engineering
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Re: The new skill in AI is not prompting, it's context engineering
#292> Building powerful and reliable AI Agents is becoming less about finding a magic prompt or model updates. Ok, I can buy this > It is about the engineering of context and providing the right information and tools, in the right format, at the right time. when the "right" format and "right" time are essentially, and maybe even necessarily, undefined, then aren't you still reaching for a "magic" solution? If the definit…
It's magical thinking all the way down. Whether they call it now "prompt" or "context" engineering because it's the same tinkering to find something that "sticks" in non-deterministic space.
In other words; context.
But that was like old man programming.
As the laws of physics changed between 1970 and 2009.
Re: The new skill in AI is not prompting, it's context engineering
#293> Building powerful and reliable AI Agents is becoming less about finding a magic prompt or model updates. Ok, I can buy this > It is about the engineering of context and providing the right information and tools, in the right format, at the right time. when the "right" format and "right" time are essentially, and maybe even necessarily, undefined, then aren't you still reaching for a "magic" solution? If the definit…
There are many sciences involving non-determinism that still have laws and patterns, e.g. biology and maybe psychology. It's not all or nothing.
Also, LLMs are deterministic, just not predictable. The non-determinism is injected by providers.
Anyway is there an essential difference between prompt engineering and context engineering? They seem like two names for the same thing.
Re: The new skill in AI is not prompting, it's context engineering
#294Earlier quoted context omitted.
It's magical thinking all the way down. Whether they call it now "prompt" or "context" engineering because it's the same tinkering to find something that "sticks" in non-deterministic space.
>Whether they call it now "prompt" or "context" engineering because it's the same tinkering to find something that "sticks" in non-deterministic space. I dont quite follow. Prompts and contexts are different things. Sure, you can get thing into contexts with prompts but that doesn't mean they are entirely the same. You could have a long running conversation with a lot in the context. A given prompt may work poorly, w…
Re: The new skill in AI is not prompting, it's context engineering
#295Re: The new skill in AI is not prompting, it's context engineering
#296I feel like this is incredibly obvious to anyone who's ever used an LLM or has any concept of how they work. It was equally obvious before this that the "skill" of prompt-engineering was a bunch of hacks that would quickly cease to matter. Basically they have the raw intelligence, you now have to give them the ability to get input and the ability to take actions as output and there's a lot of plumbing to make that ha…
It reads like articles put out by consultants at the height of SOA. Someone thought for a few minutes about something and figured it was worth an article.
Re: The new skill in AI is not prompting, it's context engineering
#297> Building powerful and reliable AI Agents is becoming less about finding a magic prompt or model updates. Ok, I can buy this > It is about the engineering of context and providing the right information and tools, in the right format, at the right time. when the "right" format and "right" time are essentially, and maybe even necessarily, undefined, then aren't you still reaching for a "magic" solution? If the definit…
It's magical thinking all the way down. Whether they call it now "prompt" or "context" engineering because it's the same tinkering to find something that "sticks" in non-deterministic space.
I mean this not as an insult to software dev but to work generally. It’s all play in the end.
Re: The new skill in AI is not prompting, it's context engineering
#298The new skill is programming, same as the old skill. To the extent these things are comprehensible, you understand them by writing programs: programs that train them, programs that run inferenve, programs that analyze their behavior. You get the most out of LLMs by knowing how they work in detail. I had one view of what these things were and how they work, and a bunch of outcomes attached to that. And then I spent a…
Saying the best way to understand LLMs is by building one is like saying the best way to understand compilers is by writing one. Technically true, but most people aren't interested in going that deep.
If you want to be an F1 driver it's probably useful to understand almost every part of a car. If you're a delivery driver, it probably isn't, even if you use one 40+ hours a week.