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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

#531

Post by fumblingness »

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.

"And at no point does it ever occur to you to demand proof that measures such as this will have the desired effect... or, indeed, that the desired effect is indeed worth achieving at all."

- you (https://news.ycombinator.com/item?id=44439447)

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

#532

Post by shakna »

groestl wrote: post #521
shakna wrote: post #315

Earlier quoted context omitted.

Engineering tends to mean "the application of scientific and mathematical principles to practical ends". I'm not sure there's much scientific or mathematical about guessing how a non-deterministic system will behave.

Funny how you use a scientific term to discredit applied statistics. I've built useful non-deterministic systems many times and they had nothing to do with AI. Also, particle physics would like to have a word with you.

Guessing, how a non-deterministic system would behave.

Statistics isn't guessing. But it is guessing when the confidence interval is unknowable and constantly shifting. We're not talking relativity, we're talking about throwing pancakes at a wall to tell if there's a person behind it.

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

#533

Post by shakna »

grugagag wrote: post #411
SonOfLilit wrote: post #359

Earlier quoted context omitted.

The moment you start building evaluation pipelines and running experiments to validate your ideas it stops being guessing

It’s validated and filtered but isn’t it still guessing at the core? Should we call it validated guessing?

If it's actually validated, according to rigorous principles, it's not a guess, but a system of predictions with a known confidence interval, that allows you to know if you can be sure of something.

Right now, you cannot get that far. And if you happen to... Tomorrow it will be different.

Predicting tides is possible. It requires enormous amounts of data and processing to be sure of it. Right now, we've got tides, but we don't have the data from the satellites. Because the owner is constantly shifting the prompt, for good reasons of their own. So we can't be confident - or we can only be so blindly.

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

#534

Post by bird0861 »

coldtea wrote: post #210
risyachka wrote: post #102

Earlier quoted context omitted.

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

What exactly month-long AI skills of 2023 AI are obsolete now? Surely not prompt engineering itself, for example.

Persona prompting. (Unless the persona is the point as in role-playing.)

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

#535

Post by briangriffinfan »

somewhereoutth wrote: post #150
mgdev wrote: post #77

If we zoom out far enough, and start to put more and more under the execution umbrella of AI, what we're actually describing here is... product development. You are constructing the set of context, policies, directed attention toward some intentional end, same as it ever was. The difference is you need fewer meat bags to do it, even as your projects get larger and larger. To me this is wholly encouraging. Some projec…

> for his own creations. for their own creations is grammatically valid, and would avoid accusations of sexism!

After mulling this issue over in my head for a significant amount of time, I've determined that I don't care and he sounds more natural.

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

#536

Post by tdaltonc »

StochasticLi wrote: post #434
niemandhier wrote: post #363

LLM agents remind me of the great Nolan movie „Memento“. The agents cannot change their internal state hence they change the encompassing system. They do this by injecting information into it in such a way that the reaction that is triggered in them compensates for their immutability. For this reason I call my agents „Sammy Jenkins“.

I think we can reasonably expect they will become non-stateless in the next few years.

If agents are stateful a few years form now it will be because they accrete a layer of context engineering.

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

#537

Post by jm4 »

hackable_sand wrote: post #527
jm4 wrote: post #415

Earlier quoted context omitted.

I went down that rabbit hole with Cursor and it's pretty good. Then I tried tools like Cline with Sonnet 4 and Claude Code. The Anthropic models have huge context and it shows. I'm no expert, but it feels like you reach a point where the model is good enough and then the gains are coming from the context size. When I'm doing something complex, I'm filling up the 200k context window and getting solutions that I just c…

Recently cancelled my Cursor subscription because it's pretty bad.

Personally, I think it's much better than Github Copilot. The autocomplete is phenomenal and ctrl+k to quickly generate code is convenient. Agentic coding is good until you try something like Cline or Claude Code and realize how limited it is. I don't use Cursor's agentic mode anymore. I may go back to Github Copilot for autocomplete and Cline/Claude for everything else.

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

#538

Post by mrcoders »

Looking at this thread, excited to see the community articulating what many of us have been experiencing. The shift from "prompt engineering" to "context engineering" really captures what's happening. The technical stuff (RAG, vector databases) is getting commoditized. But there's this foundational knowledge organization layer that's becoming critical.

Most companies have context scattered across wikis, Slack, Google Docs. You can build sophisticated retrieval systems, but if you're feeding them fragmented information, you're missing huge optimization opportunities.

There's research backing this - Microsoft/Salesforce found 39% accuracy drop in multi-turn conversations - so for the agent interaction's it's even more cirtical to give 'just enough' context (https://arxiv.org/pdf/2505.06120).

When (business) context is properly structured upfront, you minimize those patterns.

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

#539

Post by [deleted] »

shakna wrote: post #532
groestl wrote: post #521

Earlier quoted context omitted.

Funny how you use a scientific term to discredit applied statistics. I've built useful non-deterministic systems many times and they had nothing to do with AI. Also, particle physics would like to have a word with you.

Guessing, how a non-deterministic system would behave. Statistics isn't guessing. But it is guessing when the confidence interval is unknowable and constantly shifting. We're not talking relativity, we're talking about throwing pancakes at a wall to tell if there's a person behind it.

[deleted]

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

#540

Post by sva_ »

simonw wrote: post #379
phyalow wrote: post #353

Earlier quoted context omitted.

What? You can get consistent output on local models. I can train large nets deterministically too (CUBLAS flags). What your saying isn't true in practice. Hell I can also go on the anthropic API right now and get verbatim static results.

"Hell I can also go on the anthropic API right now and get verbatim static results." How? Setting temperature to 0 won't guarantee the exact same output for the exact same input, because - as the previous commenter said - floating point arithmetic is non-commutative, which becomes important when you are running parallel operations on GPUs.

Shouldn't it be the fact that they're non-associative? Because the reduction kernels will combine partial results (like the dot‑products in a GEMM or the sum across attention heads) in a way that the order of operations may change (non-associative), which can lead to the individual floats to be round off differently.
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