11–20 of 53 posts
Feels like you'd be a fan of - https://github.com/PrefectHQ/prefect - https://github.com/PrefectHQ/ControlFlow Motivated by more or less the same frustration you've laid out here.
Congrats on launching! From your explanation comparing to traditional workflow engines it would be a step up from something like Airflow, but I was wondering about a comparison to Temporal which does let you create dynamic DAGs as well as provides some additional guarantees around reliability of workers in case of crashes.
I tend to agree the graph approach is wrong. I have a meta question though - there seems to be a huge amount of activity in this space of LLM agent related developer tooling. Are people actually successfully and reliably delivering services which use LLMs? (Meaning services which are not just themselves exposing LLMs or chat style interfaces). It seems like 18 months ago people were running around terrified, but now…
Nice approach! I'm intrigued by the ability to start execution from a particular task. One thing I like about LangGraph is the declarative state merging. In the MapReduce example, how do you guarantee that the collector.append() operation is thread-safe?
Nice approach! I'm intrigued by the ability to start execution from a particular task. One thing I like about LangGraph is the declarative state merging. In the MapReduce example, how do you guarantee that the collector.append() operation is thread-safe?
Congrats on launching! From your explanation comparing to traditional workflow engines it would be a step up from something like Airflow, but I was wondering about a comparison to Temporal which does let you create dynamic DAGs as well as provides some additional guarantees around reliability of workers in case of crashes.
Thanks! Yep, retry and durability guarantee is on the roadmap for sure, I also wanted to start working on the serverless offering. What kind of workflows are you building with temporal?
The ReAct paradigm for agents makes me think of standard workflows because they're not that different conceptually: Read the state of the world, plan / "reason" based on user intent, perform actions that mutate, then go back and read the state of the world if problem hasn't been fully solved (ie start another workflow). Similar in concept from reading from dbs, computing logic, mutating / writing to new table, trigger follow on job from data engineering.
Earlier quoted context omitted.
Thanks! Yep, retry and durability guarantee is on the roadmap for sure, I also wanted to start working on the serverless offering. What kind of workflows are you building with temporal?
I'm working on building out an AI agent right now - looking through autogen, langgraph and other current frameworks along with just building my own logic on top of a workflow orchestrator. The ReAct paradigm for agents makes me think of standard workflows because they're not that different conceptually: Read the state of the world, plan / "reason" based on user intent, perform actions that mutate, then go back and re…
Earlier quoted context omitted.
Thanks! Yep, retry and durability guarantee is on the roadmap for sure, I also wanted to start working on the serverless offering. What kind of workflows are you building with temporal?
I'm working on building out an AI agent right now - looking through autogen, langgraph and other current frameworks along with just building my own logic on top of a workflow orchestrator. The ReAct paradigm for agents makes me think of standard workflows because they're not that different conceptually: Read the state of the world, plan / "reason" based on user intent, perform actions that mutate, then go back and re…
Earlier quoted context omitted.
I'm working on building out an AI agent right now - looking through autogen, langgraph and other current frameworks along with just building my own logic on top of a workflow orchestrator. The ReAct paradigm for agents makes me think of standard workflows because they're not that different conceptually: Read the state of the world, plan / "reason" based on user intent, perform actions that mutate, then go back and re…
Hey, I’m building agents on top of temporal as well. One of the main limitations is child workflows can not spawn other child workflows. Are you doing an activity for every prompt execution and passing those through other activities? Or something more framework-y?
I agree complex conditional LangGraph setups get pretty tedious after a certain point - though you claim to not use graphs here, but isn't that essentially what returning the "next task" does? The graph isn't explicitly defined but it still exists implicitly if you trace through all the tasks and next tasks. Would be interesting to see a complex agent implementation in both Flow and regular LangGraph to compare maint…