Context engineering

77 pointsposted 18 hours ago
by chrisloy

29 Comments

elteto

14 hours ago

Are there any open source examples of good context engineering or agent systems?

calebkaiser

11 hours ago

Any of the "design patterns" listed in the article will have a ton of popular open source implementations. For structured generation, I think outlines is a particularly cool library, especially if you want to poke around at how constrained decoding works under the hood: https://github.com/dottxt-ai/outlines

voidhorse

14 hours ago

There is nothing precise about crafting prompts and context—it's just that, a craft. Even if you do the right thing and check some fuzzy boundary conditions using autoscorers, the model can still change out from beneath you at any point and totally alter the behavior of your system. There is no formal language here. After all, mathematics exists because natural language is notoriously imprecise.

The article has some good practical tips and it's not on the author but man I really wish we'd stop abusing the term "engineering" in a desperate attempt to stroke our own egos and or convince people to give us money. It's pathetic. Coming up with good inputs to LLMs is more art than science and it's a craft. Call a spade a spade.

calebkaiser

10 hours ago

I think it's fair to question the use of the term "engineering" throughout a lot of the software industry. But to be fair to the author, his focus in the piece is on design patterns that require what we'd commonly call software engineering to implement.

For example, his first listed design pattern is RAG. To implement such a system from scratch, you'd need to construct a data layer (commonly a vector database), retrieval logic, etc.

In fact I think the author largely agrees with you re: crafting prompts. He has a whole section admonishing "prompt engineering" as magical incantations, which he differentiates from his focus here (software which needs to be built around an LLM).

I understand the general uneasiness around using "engineering" when discussing a stochastic model, but I think it's worth pointing out that there is a lot of engineering work required to build the software systems around these models. Writing software to parse context-free grammars into masks to be applied at inference, for example, is as much "engineering" as any other common software engineering project.

amonks

10 hours ago

long shot, apropos of nothing, just recognized your name:

If you are the cincinnatian poet Caleb Kaiser, we went to college together and I’d love to catch up. Email in profile.

If you aren’t, disregard this. Sorry to derail the thread.

qrios

14 hours ago

I agree with you one hundred percent.

But: Interestingly, the behavior of LLMs in different contexts is also the subject of scientific research.

chrisweekly

13 hours ago

"Context crafting", ok, sure. I think a lot of expert researchers (like simonw) would agree.

satisfice

14 hours ago

My thoughts exactly. The author is saying we should think strategically about the use of context. Sure. Yes. But for that to qualify as engineering we need solid theory about how context works.

We don’t have that, yet. For instance experiments show that not all parts of the context window are equally well attended. Imagine trying to engineer a bridge when no one really knows how strong steel is.

skeeter2020

13 hours ago

or how wide the river is year round

alecco

10 hours ago

This looks AI generated slop.

Balgair

2 hours ago

I know this is a bit of a non sequitur but, on my feed just below your comment, some asked for the RSS for this blog. The juxtaposition of the two comments here is just soooo HN

aeve890

13 hours ago

Are we still calling this things engineering?

simonw

10 hours ago

Yes, and we've also decided that they deserve the title "engineering" more than software engineering does.

Most engineering disciplines have to deal with tolerances and uncertainty - the real world is non-deterministic.

Software engineering is easy in comparison because computers always do exactly what you tell them to do.

The ways LLMs fail (and the techniques you have to use to account for that) have more in common than physical engineering disciplines than software engineering does!

quequon

2 hours ago

Classic shilling behavior of the insufferably embarrassing: redefining words to the benefit of those who pay your bills to the confusion of everyone else.

The definition of engineering, according to people outside the pocket of the llm industry:

> The application of scientific and mathematical principles to practical ends such as the design, manufacture, and operation of efficient and economical structures, machines, processes, and systems.

How do these techniques apply scientific and mathematical principals?

I would argue to do either of those requires reproducibility, and yet somehow you are arguing the less reproducible something is that the more like "physical engineering" it becomes.

cadamsdotcom

10 hours ago

Yep. Consider woodworking - the wood you use might warp over time, or maybe part of it ends up in the sun or the thing you’ll make gets partly exposed to water.

Can you make a thing that’ll serve its purpose and look good for years under those constraints? A professional carpenter can.

We have it easy in software.

mpalmer

10 hours ago

Physical engineers might scoff good-naturedly at an attempt by project managers to refer to work scheduling as "logistics engineering".

But they really shouldn't because obviously scheduling and logistics is difficult, involving a lot of uncertainty and tolerances.

scuff3d

10 hours ago

Lol. This has to be a troll. No way someone seriously wrote this and meant it.

dingnuts

8 hours ago

The tools mechanical and civil engineers use are predictable. You're confusing the things these engineers design, which have tolerances and things like that, with the tools themselves.

If an engineer built an internal combustion engine that misfired 60% of the time, it simply wouldn't work.

If an engineer measured things with a ruler that only measured correctly 40% of the time, that would be the apt analogy.

The tool isn't what makes engineering a practice, it's the rigor and the ability to measure and then use the measurements to predict outcomes to make things useful.

Can you predict the outcome from an LLM with an "engineered" prompt?

No, and you aren't qualified to even comment on it since your only claim to fame is a fucking web app

voidhorse

10 hours ago

I completely agree that much of software engineering is not engineering, and building systems around LLMs is no better in this sense.

When the central component of your system is a black box that you cannot reason about, have no theory around, and have essentially no control over (a model update can completely change your system behavior) engineering is basically impossible from the start.

Practices like using autoscorers to try and constrain behaviors helps, but this doesn't make the enterprise any more engineering because of the black box problem. Traditional engineering disciplines are able to call themselves engineering only because they are built on sophisticated physical theories that give them a precise understanding of the behaviors of materials under specified conditions. No such precision is possible with LLMs, as far as I have seen.

The determinism of traditional computing isn't really relevant here and targets the wrong logical level. We engineer systems, not programs.

timr

10 hours ago

lol. who is “we”? I honestly can’t tell if you’re being serious.

I’m going to start a second career in lottery “engineering”, since that’s a stochastic process too.

aeve890

9 hours ago

>The ways LLMs fail (and the techniques you have to use to account for that) have more in common than physical engineering disciplines than software engineering does!

Ah yes, the God given free parameters in the Standard Model, including obviously the random seed of a transformer. What if just put 0 in the inference temperature? The randomness in llms is a technical choice to generate variations in the selection of the next token. Physical engineering? Come on.

skeeter2020

13 hours ago

"professionally trained & legally responsible for the results" is definitely not the same thing as what we used to just call "good at googling".

aeve890

12 hours ago

I'd say this shit is even worse that "good at googling". Literal incantation for stochastic machines is like just two notches above checking the horoscope.

j45

10 hours ago

Engineering how to engineer things might be engineering in some ways.

sgt101

13 hours ago

Why would I believe that any of this works? This is just some blokes idea of what people should do.

There is no evidence offered. No attempt to measure the benefits.

calebkaiser

11 hours ago

Most of the inference techniques (what the author calls context engineering design patterns) listed here originally came from the research community, and there are tons of benchmarks measuring their effectiveness, as well as a great deal of research behind what is happening mechanistically with each.

As the author points out, many of the patterns are fundamentally about in-context learning, and this in particular has been subject to a ton of research from the mechanistic interpretability crew. If you're curious, I think this line of research is fascinating: https://transformer-circuits.pub/2022/in-context-learning-an...

dwaltrip

8 hours ago

Imagine the gall of someone who just goes on the internet and writes something.