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Miracles In Progress 12 Step Recovery Forums -> Alcoholics Anonymous -> Alcoholics Anonymous -> Where Large Action Models actually fit in real production systems
Post Info TOPIC: Where Large Action Models actually fit in real production systems
JockGR


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Where Large Action Models actually fit in real production systems
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Ive been trying to understand where Large Action Models actually fit in real software systems, not just in theory. Most of what Ive seen so far is either demos or very controlled environments, but I recently read this breakdown that explains how theyre supposed to coordinate actions across tools instead of just generating text: https://www.trinetix.com/insights/what-are-large-action-models-and-how-do-they-work . It reminded me of a small internal tool I worked on where we had an AI layer deciding which API endpoint to call next, but it was still very rigid and rule-driven. Im wondering if anyone here has actually seen something like this running in a real production environment where the model has some real autonomy, or is it still mostly just structured automation with a smarter interface?



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Alianse88


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Ive worked on something close in an enterprise workflow system, but it definitely wasnt fully autonomous. What we did was more like guided execution, where the model could propose a sequence of actions, but each step had to pass validation rules and sometimes even manual approval depending on the risk level. The interesting part is that even that limited version already improved speed for routine tasks like data entry and ticket routing. But we quickly learned that letting the model freely decide actions creates too much unpredictability. So the real value wasnt full autonomyit was reducing the number of decisions humans had to make while still keeping control over execution. I think most real systems today are somewhere in that middle ground.

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lejab94302


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Im not involved in development directly, but I work in a role where we interact with a lot of automated internal tools. From my side, the most noticeable change isnt that systems are thinking more, but that workflows are becoming less visible. Earlier, you could clearly see each step in a process. Now, some tools just return a final result, and its not always obvious what happened in between. Thats convenient, but it also makes troubleshooting harder when something goes wrong. So even if the technology is improving, I think transparency is still a big challenge, especially for teams that rely on these systems daily.

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Miracles In Progress 12 Step Recovery Forums -> Alcoholics Anonymous -> Alcoholics Anonymous -> Where Large Action Models actually fit in real production systems