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Comment by DebtDeflation | Hacker News Reader

There are two competing definitions of agents being used in industry.

https://www.anthropic.com/engineering/building-effective-age...

"- Workflows are systems where LLMs and tools are orchestrated through predefined code paths.

- Agents, on the other hand, are systems where LLMs dynamically direct their own processes and tool usage, maintaining control over how they accomplish tasks."

What Anthropic calls a "workflow" in the above definition is what most of the big enterprise software companies (Salesforce, ServiceNow, Workday, SAP, etc.) are building and calling AI Agents.

What Anthropic calls an "agent" in the above definition is what AI Researchers mean by the term. It's also something that mainly exists in their labs. Real world examples are fairly primitive right now, mainly stuff like Deep Research. That will change over time, but right now the hype far exceeds the reality.

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I think Anthropic's definition of workflows is inaccurate for modern definitions of the term. Temporal for instance (disclaimer, my employer) allows completely dynamic logic in agentic workflows to let the LLM choose what to do next. It can even be very dynamic (e.g. eval some code) though you may want it to operate on a limited set of "tools" you make available.

The problem with all of these AI specific workflow engines is they are not durable, so they are process local, suffer crashes, cannot resume, don't have good visibility or distribution, etc. They often only allow limited orchestration instead of code freedom, only one language, etc

"Workflow can be very dynamic" is a great summary!

What about workflows are not agents?

To me, a workflow is a predetermined set of steps that are followed based on fixed logic. Agents should have some agency to determine which steps in the workflow to perform next, without them being predetermined by fixed logic.

>The problem with all of these AI specific workflow engines is they are not durable, so they are process local, suffer crashes, cannot resume, don't have good visibility or distribution, etc. They often only allow limited orchestration instead of code freedom, only one language, etc

So what's the solution?

My biased answer, because I work at Temporal[0], is to use an existing workflow solution that solves all of these problems instead of reaching for a solution that doesn't help with any of these but happens to be AI specific. Most agentic AI workflows are really just microservice orchestrations, the only "AI" involved is prompting an HTTP API that uses AI on its end. So use a good solution for "agentic X" whether that X is AI or any other orchestration needs.

0 - https://temporal.io/solutions/ai

It’s only a true agent if it chooses what to eat for breakfast everyday.

PocketFlow calls itself "agentic" due to its "agentic coding" paradigm (AI agents like Cursor building apps), but this is about development, not runtime behavior. At runtime, it’s a workflow system. This stretches Anthropic’s definition, where "agentic" implies dynamic LLM control during execution. I think this si where the misunderstanding stems from.

This was a LLM generated reponse which was pretty stupid involving Agentic coding. But it's still correct that PocketFlow does not align with Anthropic's definition of what an "Agent" is.

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