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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

#101

Post by labrador »

simonw wrote: post #57
labrador wrote: post #35

I’m curious how this applies to systems like ChatGPT, which now have two kinds of memory: user-configurable memory (a list of facts or preferences) and an opaque chat history memory. If context is the core unit of interaction, it seems important to give users more control or at least visibility into both. I know context engineering is critical for agents, but I wonder if it's also useful for shaping personality and i…

I really dislike the new ChatGPT memory feature (the one that pulls details out of a summarized version of all of your previous chats, as opposed to older memory feature that records short notes to itself) for exactly this reason: it makes it even harder for me to control the context when I'm using ChatGPT. If I'm debugging something with ChatGPT and I hit an error loop, my fix is to start a new conversation. Now I c…

On the other hand, for my use case (I'm retired and enjoy chatting with it), having it remember items from past chats makes it feel much more personable. I actually prefer Claude, but it doesn't have memory, so I unsubscribed and subscribed to ChatGPT. That it remembers obscure but relevant details about our past chats feels almost magical.

It's good that you can turn it off. I can see how it might cause problems when trying to do technical work.

Edit: Note, the introduction of memory was a contributing factor to "the sychophant" that OpenAI had to rollback. When it could praise you while seeming to know you was encouraging addictive use.

Edit2: Here's the previous Hacker News discussion on Simon's "I really don’t like ChatGPT’s new memory dossier"

https://news.ycombinator.com/item?id=44052246

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

#102

Post by risyachka »

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…

“A month-long skill” after which it won’t be a thing anymore, like so many other.

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

#103

Post by simonw »

zacharyvoase wrote: post #99

I love how we have such a poor model of how LLMs work (or more aptly don't work) that we are developing an entire alchemical practice around them. Definitely seems healthy for the industry and the species.

The stuff that's showing up under the "context engineering" banner feels a whole lot less alchemical to me than the older prompt engineering tricks.

Alchemical is "you are the world's top expert on marketing, and if you get it right I'll tip you $100, and if you get it wrong a kitten will die".

The techniques in https://www.dbreunig.com/2025/06/26/how-to-fix-your-context.... seem a whole lot more rational to me than that.

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

#104

Post by geeewhy »

ive beeen experimenting with this for a while, (im sure in a way, most of us did). Would be good to numerate some examples. When it comes to coding, here's a few:

- compile scripts that can grep / compile list of your relevant files as files of interest

- make temp symlinks in relevant repos to each other for documentation generation, pass each documentation collected from respective repos to to enable cross-repo ops to be performed atomically

- build scripts to copy schemas, db ddls, dtos, example records, api specs, contracts (still works better than MCP in most cases)

I found these steps not only help better output but also reduces cost greatly avoiding some "reasoning" hops. I'm sure practice can extend beyond coding.

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

#105

Post by ZYbCRq22HbJ2y7 »

storus wrote: post #91
Foreignborn wrote: post #74

Earlier quoted context omitted.

yes, but those aren’t released and even then you’ll always need glue code. you just need to knowingly resource what glue code is needed, and build it in a way it can scale with whatever new limits that upgraded models give you. i can’t imagine a world where people aren’t building products that try to overcome the limitations of SOTA models

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?

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

#106

Post by simonw »

risyachka wrote: post #102
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…

“A month-long skill” after which it won’t be a thing anymore, like so many other.

Most of the LLM prompting skills I figured out ~three years ago are still useful to me today. Even the ones that I've dropped are useful because I know that things that used to be helpful aren't helpful any more, which helps me build an intuition for how the models have improved over time.

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

#108

Post by ModernMech »

root_axis wrote: post #59
baxtr wrote: post #2

> Conclusion Building powerful and reliable AI Agents is becoming less about finding a magic prompt or model updates. It is about the engineering of context and providing the right information and tools, in the right format, at the right time. It’s a cross-functional challenge that involves understanding your business use case, defining your outputs, and structuring all the necessary information so that an LLM can “a…

I am not a fan of this banal trend of superficially comparing aspects of machine learning to humans. It doesn't provide any insight and is hardly ever accurate.

I agree, however I do appreciate comparisons to other human-made systems. For example, "providing the right information and tools, in the right format, at the right time" sounds a lot like a bureaucracy, particularly because "right" is decided for you, it's left undefined, and may change at any time with no warning or recourse.

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

#109

Post by grafmax »

simonw wrote: post #61
grafmax wrote: post #31

There is no need to develop this ‘skill’. This can all be automated as a preprocessing step before the main request runs. Then you can have agents with infinite context, etc.

You need this skill if you're the engineer that's designing and implementing that preprocessing step.

In the short term horizon I think you are right. But over a longer horizon, we should expect model providers to internalize these mechanisms, similar to how chain of thought has been effectively “internalized” - which in turn has reduced the effectiveness that prompt engineering used to provide as models have gotten better.

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

#110

Post by dinvlad »

storus wrote: post #48
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…

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?

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