[hwchase17]

Hi HN, Harrison (CEO/co-founder of LangChain) here, wanted to chime in briefly

I appreciate Fabian and the Octomind team sharing their experience in a level-headed and precise way. I don't think this is trying to be click-baity at all which I appreciate. I want to share a bit about how we are thinking about things because I think it aligns with some of the points here (although this may be worth a longer post)

> But frameworks are typically designed for enforcing structure based on well-established patterns of usage - something LLM-powered applications don’t yet have.

I think this is the key point. I agree with their sentiment that frameworks are useful when there are clear patterns. I also agree that it is super early on and super fast moving field.

The initial version of LangChain was pretty high level and absolutely abstracted away too much. We're moving more and more to low level abstractions, while also trying to figure out what some of these high level patterns are.

For moving to lower level abstractions - we're investing a lot in LangGraph (and hearing very good feedback). It's a very low-level, controllable framework for building agentic applications. All nodes/edges are just Python functions, you can use with/without LangChain. It's intended to replace the LangChain AgentExecutor (which as they noted was opaque)

I think there are a few patterns that are emerging, and we're trying to invest heavily there. Generating structured output and tool calling are two of those, and we're trying to standardize our interfaces there

Again, this is probably a longer discussion but I just wanted to share some of the directions we're taking to address some of the valid criticisms here. Happy to answer any questions!

[jfjeschke]

Thanks Harrison. LangGraph (eg graph theory + Networkx) is the correct implementation of multi-agent frameworks, though it is looking further into, and anticipating a future, then where most GPT/agent deployments are at.

And while structured output and tool calling are good, from client feedback, I'm seeing more of a need for different types of composable agents other then the default ReAct, which has distinct limitations and performs poorly in many scenarios. Reflection/Reflextion are really good, REWOO or Plan/Execute as well.

Different agents for different situations...

[hwchase17]

> Different agents for different situations...

totally agree. we've opted for keeping langgraph very low level and not adding these higher level abstractions. we do have examples for them in the notebooks, but havent moved them into the core library. maybe at some point (if things stabilize) we will. I would argue the react architecture is the only stable one at the moment. planning and reflection are GREAT techniques to bring into your custom agent, but i dont think theres a great generic implementation of them yet

[cynicalpeace]

LangChain had a time and place. That was Spring of 2023, when everyone was figuring out how to string together llm calls with function calls.

We've figured that out, and the answer (like usual) is just K.I.S.S., not LangChain.

It seems even the LangChain folks are abandoning it. Good on you, you will most likely succeed if you do.

[fswd]

using LangGraph for a month, every single "graph" was the same single solution. The idea is cool, but it isn't solving the right problem.... (and the problem statement shouldn't be generating buzz on twitter. sorry to be harsh).

You could borrow some ideas from DSPy (which borrows from pytorch) their Module: def forward: and chain LM objects this way. LangGraph sounds cool, but is a very fancy and limited version of basic conditional statements like switch/if, already built into languages.

[hwchase17]

ooc, what was the "same single solution"

[causal]

I appreciate that you're taking feedback seriously, and it sounds like you're making some good changes.

But frankly, all my goodwill was burnt up in the days I spent trying to make LangChain work, and the number of posts I've seen like this one make it clear I'm not the only one. The changes you've made might be awesome, but it also means NEW abstractions to learn, and "fool me once..." comes to mind.

But if you're sure it's in a much better place now, then for marketing purposes you might be better off relaunching as LangChain2, intentionally distancing the project from earlier versions.

[hwchase17]

sorry to hear that, totally understand feeling burnt

ooc - do you think theres anything we could do to change that? that is one of the biggest things we are wrestling with. (aside from completely distancing from langchain project)

[ctxc]

They were early to the scene, made the decisions that made sense at each point in time. Initially I (like many other engineers with no AI exposure) didn't know enough to want to play around with the knobs too much. Now I do.

So the playing field has and is changing, langChain are adapting.

Isn't that a bit too extreme? Goodwill burnt up? When the field changes, there will be new abstractions - of course I'll have to understand them to decide for myself if they're optimal or not.

React has an abstraction. Svelte has something different. AlpineJS, another. Vanilla JS has none. Does that mean only one is right and the remaining are wrong?

I'd just understand them and pick what seems right for my usecase.

[jes5199]

[deleted]

[causal]

I also have my criticisms of LangChain, but this feels mean-spirited towards devs that I think are honestly trying and didn't charge anything to use.