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

philschmid.de

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

#91

Post by storus »

Foreignborn wrote: post #74
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,…

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 today by turning tools on/off depending on the agent's state but at some point in the future you might afford not to bother and just dump all your tools to a long stable context, maybe cache it for performance, and that will be it.

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

#92

Post by mentalgear »

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…

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.

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

#94

Post by rvz »

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.

> Not really. Got some code you don't understand? Feed it to a model and ask it to add comments.

Absolutely not.

An experienced individual in their field can tell if the AI made a mistake in the comments / code rather than the typical untrained eye.

So no, actually read the code and understand what it does.

> 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.

So for safety critical systems, one should not look or check if code has been AI generated?

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

#95

Post by dolebirchwood »

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.

The skill amounts to determining "what information is required for System A to achieve Outcome X." We already have a term for this: Critical thinking.

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

#96

Post by JoeOfTexas »

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.

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

#97

Post by simonw »

storus wrote: post #85
simonw wrote: post #51

Earlier quoted context omitted.

Can you link to the research on millions of different terms and stable long contexts? I haven't come across that yet.

You can look at AnyTool, 2024 (16,000 tools) and start looking at newer research from there. https://arxiv.org/abs/2402.04253 For long contexts start with activation beacons and RoPE scaling.

I would classify AnyTool as a context engineering trick. It's using GPT-4 function calls (what we would call tool calls today) to find the best tools for the current job based on a 3-level hierarchy search.

Drew calls that one "Tool Loadout" https://www.dbreunig.com/2025/06/26/how-to-fix-your-context....

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

#100

Post by mentalgear »

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…

Basically, finding the right buttons to push within the constraints of the environment. Not so much different from what (SW) engineering is, only non-deterministic in the outcomes.
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