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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

#111

Post by dinvlad »

JohnMakin wrote: post #10

> 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…

> when the "right" format and "right" time are essentially, and maybe even necessarily, undefined, then aren't you still reaching for a "magic" solution?

Exactly the problem with all "knowing how to use AI correctly" advice out there rn. Shamans with drums, at the end of the day :-)

Re: The new skill in AI is not prompting, it's context engineering

#112

Post by simonw »

dinvlad wrote: post #110
storus wrote: post #48

Earlier quoted context omitted.

Those issues are considered artifacts of the current crop of LLMs in academic circles; there is already research allowing LLMs to use millions of different tools at the same time, and stable long contexts, likely reducing the amount of agents to one for most use cases outside interfacing different providers. Anyone basing their future agentic systems on current LLMs would likely face LangChain fate - built for GPT-3,…

> already research allowing LLMs to use millions of different tools Hmm first time hearing about this, could you share any examples please?

See this comment https://news.ycombinator.com/item?id=44428548

Re: The new skill in AI is not prompting, it's context engineering

#113

Post by emporas »

Prompting sits on the back seat, while context is the driving factor. 100% agree with this.

For programming I don't use any prompts. I give a problem solved already, as a context or example, and I ask it to implement something similar. One sentence or two, and that's it.

Other kind of tasks, like writing, I use prompts, but even then, context and examples are still the driving factor.

In my opinion, we are in an interesting point in history, in which now individuals will need their own personal database. Like companies the last 50 years, which had their own database records of customers, products, prices and so on, now an individual will operate using personal contextual information, saved over a long period of time in wikis or Sqlite rows.

Re: The new skill in AI is not prompting, it's context engineering

#114

Post by storus »

ZYbCRq22HbJ2y7 wrote: post #105
storus wrote: post #91

Earlier quoted context omitted.

My point is that newer models will have those baked in, so instead of supporting ~30 tools before falling apart they will reliably support 10,000 tools defined in their context. That alone would dramatically change the need for more than one agent in most cases as the architectural split into multiple agents is often driven by the inability to reliably run many tools within a single agent. Now you can hack around it…

There will likely be custom, large, and expensive models at an enterprise level in the near future (some large entities and governments already have them (niprgpt)). With that in mind, what would be the business sense in siloing a single "Agent" instead of using something like a service discovery service that all benefit from?

My guess is the main issue is latency and accuracy; a single agent without all the routing/evaluation sub-agents around it that introduce cumulative errors, lead to infinite loops and slow it down would likely be much faster, accurate and could be cached at the token level on a GPU, reducing token preprocessing time further. Now different companies would run different "monorepo" agents and those would need something like MCP to talk to each other at the business boundary, but internally all this won't be necessary.

Also the current LLMs have still too many issues because they are autoregressive and heavily biased towards the first few generated tokens. They also still don't have full bidirectional awareness of certain relationships due to how they are masked during the training. Discrete diffusion looks interesting but I am not sure how does that one deal with tools as I've never seen a model from that class using any tools.

Re: The new skill in AI is not prompting, it's context engineering

#115

Post by igravious »

JoeOfTexas wrote: post #96
simonw wrote: post #3

I wrote a bit about this the other day: https://simonwillison.net/2025/Jun/27/context-engineering/ Drew Breunig has been doing some fantastic writing on this subject - coincidentally at the same time as the "context engineering" buzzword appeared but actually unrelated to that meme. How Long Contexts Fail - https://www.dbreunig.com/2025/06/22/how-contexts-fail-and-ho... - talks about the various ways in which longer…

So who will develop the first Logic Core that automates the context engineer.

The first rule of automation: that which can be automated will be automated.

Observation: this isn't anything that can't be automated /

Re: The new skill in AI is not prompting, it's context engineering

#117

Post by inspectorwadget »

CamperBob2 wrote: post #58
_pdp_ wrote: post #27

It is wrong. The new/old skill is reverse engineering. If the majority of the code is generated by AI, you'll still need people with technical expertise to make sense of it.

Not really. Got some code you don't understand? Feed it to a model and ask it to add comments. Ultimately humans will never need to look at most AI-generated code, any more than we have to look at the machine language emitted by a C compiler. We're a long way from that state of affairs -- as anyone who struggled with code-generation bugs in the first few generations of compilers will agree -- but we'll get there.

>any more than we have to look at the machine language emitted by a C compiler.

Some developers do actually look at the output of C compilers, and some of them even spend a lot of time criticizing that output by a specific compiler (even writing long blog posts about it). The C language has an ISO specification, and if a compiler does not conform to that specification, it is considered a bug in that compiler.

You can even go to godbolt.org / compilerexplorer.org and see the output generated for different targets by different compilers for different languages. It is a popular tool, also for language development.

I do not know what prompt engineering will look like in the future, but without AGI, I remain skeptical about verification of different kinds of code not being required in at least a sizable proportion of cases. That does not exclude usefulness of course: for instance, if you have a case where verification is not needed; or verification in a specific case can be done efficiently and robustly by a relevant expert; or some smart method for verification in some cases, like a case where a few primitive tests are sufficient.

But I have no experience with LLMs or prompt engineering.

I do, however, sympathize with not wanting to deal with paying programmers. Most are likely nice, but for instance a few may be costly, or less than honest, or less than competent, etc. But while I think it is fine to explore LLMs and invest a lot into seeing what might come of them, I would not personally bet everything on them, neither in the short term nor the long term.

May I ask what your professional background and experience is?

Re: The new skill in AI is not prompting, it's context engineering

#118

Post by skydhash »

smeej wrote: post #18
ramesh31 wrote: post #8

Earlier quoted context omitted.

We shouldn't but it's analogous to how CPU usage used to work. In the 8 bit days you could do some magical stuff that was completely impossible before microcomputers existed. But you had to have all kinds of tricks and heuristics to work around the limited abilities. We're in the same place with LLMs now. Some day we will have the equivalent of what gigabytes or RAM are to a modern CPU now, but we're still stuck in t…

It also reminds me of when you could structure an internet search query and find exactly what you wanted. You just had to ask it in the machine's language. I hope the generalized future of this doesn't look like the generalized future of that, though. Now it's darn near impossible to find very specific things on the internet because the search engines will ignore any "operators" you try to use if they generate "too f…

An empty set of results is a good signal just like a "I don't know" or "You're wrong because " are good replies to a question/query. It's how a program crashing, while painful, is better than it corrupting data.

Re: The new skill in AI is not prompting, it's context engineering

#119

Post by d0gsg0w00f »

old_man_cato wrote: post #88
simonw wrote: post #3

I wrote a bit about this the other day: https://simonwillison.net/2025/Jun/27/context-engineering/ Drew Breunig has been doing some fantastic writing on this subject - coincidentally at the same time as the "context engineering" buzzword appeared but actually unrelated to that meme. How Long Contexts Fail - https://www.dbreunig.com/2025/06/22/how-contexts-fail-and-ho... - talks about the various ways in which longer…

[flagged]

This hits too close to home.

Re: The new skill in AI is not prompting, it's context engineering

#120

Post by d0gsg0w00f »

emporas wrote: post #113

Prompting sits on the back seat, while context is the driving factor. 100% agree with this. For programming I don't use any prompts. I give a problem solved already, as a context or example, and I ask it to implement something similar. One sentence or two, and that's it. Other kind of tasks, like writing, I use prompts, but even then, context and examples are still the driving factor. In my opinion, we are in an inte…

Yes, the other day I was telling a colleague that we all need our own personal context to feed into every model we interact with. You could carry it around on a thumb drive or something.
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