I found it understandable and clear. Pocket flow looks cool, although that magic with - >> operators seems a bit obtuse... Also, I think "simply" is a trap - an agent might be modeled by a graph, but that graph can be arbitrarily complex.
LLM Agents Are Simply Graph – Tutorial for Dummies
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Re: LLM Agents Are Simply Graph – Tutorial for Dummies
#52My experience is Mistral Small, QwQ and QwenCoder can build much better diagrams in Mermaid compared to those attempt by Mr haung
Re: LLM Agents Are Simply Graph – Tutorial for Dummies
#53Earlier quoted context omitted.
I think "low-level" is relative to what's being discussed. Low-level for LLMs would have to do with how transformer layers are implemented (self-attention layer, layer norms, etc.) whereas low-level for agents would be the graph structure. Although I personally don't think the graph implementation for agents is necessarily as established or widely standardized, it's helpful to know about why such an implementation wa…
I'm not quite sure I agree, but I do get your point. Why I don't quite agree is that the agents are communicating and thus the "in the weeds" part is getting into how that communication is being processed. Which is what makes or breaks agents. How they interpret one another and respond. There needs to be some mech interp for me to really think of something as low-level. I'll put emphasis on the in the weeds part. Nua…
What I meant was, the phrase "inner workings of the processing" doesn't really mean anything at all. i.e. it doesn't convey any useful information about what you're trying to say.
> How they interpret one another and respond.
That sounds like it just falls back to "how LLMs work". It's the wrong level of abstraction in this case, because it's one level down from the topic being discussed here.
Re: LLM Agents Are Simply Graph – Tutorial for Dummies
#54It is hard to put a pin on this one because there are so many thing wrong with this definition. There are agent frameworks that are not rebranded workflow tools too. I don't think this article helps explain anything except putting the intended audience in the same box of mind we were stuck since the invention of programming - i.e. it does not help. Forget about boxes and deterministic control and start thinking of er…
Could you give some examples of the agent frameworks you're referring to? I'd love to see some examples that go beyond the graph pattern! Thank you
The agentic ai capabilities of chatbotkit.com has nothing to do with workflows.
The graph rendering is simply for illustrative purposes and most to cater for people who think in terms of graphs but the underlaying mechanics are not nodes and edges and a flow that goes from one to the next.
Re: LLM Agents Are Simply Graph – Tutorial for Dummies
#55It is hard to put a pin on this one because there are so many thing wrong with this definition. There are agent frameworks that are not rebranded workflow tools too. I don't think this article helps explain anything except putting the intended audience in the same box of mind we were stuck since the invention of programming - i.e. it does not help. Forget about boxes and deterministic control and start thinking of er…
Why forget about boxes and deterministic control and start thinking of error tolerance and recovery?
I know, that LLMs are statistical models, but can you not use patterns to enforce a deterministic outcome? (Single responsibility for each agent, retrying llm calls, rephrasing prompts, etc?)
Re: LLM Agents Are Simply Graph – Tutorial for Dummies
#56Strangely the original HN post on the framework got no comments but this one is getting viral! Good luck.
Re: LLM Agents Are Simply Graph – Tutorial for Dummies
#57It is hard to put a pin on this one because there are so many thing wrong with this definition. There are agent frameworks that are not rebranded workflow tools too. I don't think this article helps explain anything except putting the intended audience in the same box of mind we were stuck since the invention of programming - i.e. it does not help. Forget about boxes and deterministic control and start thinking of er…
> There are agent frameworks that are not rebranded workflow tools too.
To me "workflow" is just what agent means: the rules under which an automated action occurs. Without some central concept "agent" just a magic wand that does stuff that may or may not be what you want it to do. If we can't use state machines at all I'm just going to go out and say LLMs are a dead end. State machines are the bread and butter of reliable software.
> Forget about boxes and deterministic control and start thinking of error tolerance and recovery.
First you'd have to define what an error even is. Then you're just writing deterministic software again (a workflow), just with less confidence. Nice for stuff with low risk and confidence to begin with (eg semantic analysis etc whose error tends to wash out in aggregate), but not for stuff acting on my behalf.
LLMs are cool bits of software, but I can't say I see much use for "agents" whose behavior is not well-defined and whose non-determinism is formally bounded.
Re: LLM Agents Are Simply Graph – Tutorial for Dummies
#58Earlier quoted context omitted.
Hey, sorry for the confusion. This tutorial is focusing on the low-level internals of how agents are implemented—much like how intelligent large language models still boil down to matrix multiplications at their core.
> This tutorial is focusing on the low-level internals of how agents are implemented We have very different definitions of what "low-level" means. Exact opposites in fact. "Low-level" means in the inner workings. Like a low-level language is assembly (some consider C low-level but this is debatable), whereas Python would be high-level. I don't think this tutorial is "near the metal" of LLMs nor do I think it should b…
> We have very different definitions of what "low-level" means.
Does it really matter if you can understand them? waiting for strongly-opinionated engineers to finish their pedantic spiels (...even when they're wrong or there is no obvious standard of correctness) when everyone already understands each other is one of the most miserable part of being in this industry.
I—and I emphatically don't include the above poster in this view as it takes continual & repeated behavior to accrue such judgement—see this as a small tantrum, essentially, for people who never learned to regulate their emotions in professional spaces. I don't understand why this sort of bickering is considered acceptable behavior in the workplace or adjacent spaces. It's rude, arrogant, trivially avoidable with slight change in tone and rhetoric, and it makes you look like an asshole if you're not 100% right and approach it in good humor.
Re: LLM Agents Are Simply Graph – Tutorial for Dummies
#59I follow Mr. Huang, read/watch his content and also plan to use PocketFlow in some cases. A preamble, because I don't agree with this assessment. I think agents as nodes in a DAG workflow is _an_ implementation of an agentic system, but is not the systems I most often interact with (e.g. Cursor, Claude + MCP). Agentic systems can be simply the LLM + prompting + tools[1]. LLMs are more than capable (especially chain-o…
> Agentic systems can be simply the LLM + prompting + tools[1]. LLMs are more than capable (especially chain-of thought models) to breakdown problems into steps, analyze necessary tools to use and then executing the steps in sequence. All of this is done with the model in the driver seat.
Sort of, kind of. It's still a directed graph. Dynamically generated graph, but still a graph. Your prompted LLM is the decision/dispatch block. When the model decides to call a tool, that's going from the decision node to another node. The tool usually isn't another LLM call, but nothing stops it from being one.
The "traditional workflow" exists because even with best prompting, LLMs don't always stick to the expected plan. It's gotten better than it used to, so people are more willing to put the model in the driving seat. A fixed "ahead of time" workflow is still important for businesses powering products with LLMs, as they put up a facade of simplicity in front of the LLM agentic graph, and strongly prefer for it to have bounded runtime and costs.
(The other thing is that, in general, it's trickier to reason about code flow generated at runtime.)
Re: LLM Agents Are Simply Graph – Tutorial for Dummies
#60Earlier quoted context omitted.
Despite the memes, this reductivism is not exactly insightful. Like why stop there? Matrix multiplication is just a bunch of dot product. Which in turn is just cos and magnitude. What insights were generated from this?
The reductionism is insightful when it comes to providing an implementation with those specific details in mind. In the case of LLMs knowing it does boil down to matrix multiplication is insightful and useful because now you know what kind of hardware is best suited to executing a model. What is actually not insightful or useful is believing LLMs are AGI or conscious.
Belief is generally not insightful or useful by definition.
Then again, I don't think anyone who can follow this article believed that LLMs were conscious to begin with, so I'm not sure what your point is. You're preaching on behalf of a demographic that won't read this article to begin with, and presumably the people who are can see how useless, distracting, and unproductive this reductionism is.