My understanding of AI implementation is limited, but I still want to put this idea out there. The central coordinator agent would have general capabilities and be responsible for identifying what kind of task it is facing. It could complete the task itself or delegate it to a domain specialist better suited to completing it. Each domain specialist would follow the same pattern: handle general tasks within its field, identify narrower tasks, and delegate those to subspecialists. Subspecialists could delegate to further specialists, allowing the hierarchy to extend to whatever depth is useful. Creating new specialists An agent could create a specialist beneath it when two conditions are met: No suitable specialist is already available. Handling the task directly has a higher expected net cost than creating, validating, and using a specialist, accounting for potential future reuse. The new specialist would be retained if it proved useful, so future tasks could benefit from the capability already developed. Conceptually, this resembles a person learning or strengthening a skill. Recognizing mistakes and escalating If an agent recognized that a task was outside its competence, incorrectly assigned, or dependent on another field, it would report that to its parent. The parent could then revise the task, redirect it, or escalate it further up the hierarchy. Connections across branches There could also be limited connections between agents in different branches. For example, a game-programming specialist might consult a physics-engine specialist when implementing object collisions or realistic movement, without routing every exchange through the central agent. Each agent would still have a primary place in the hierarchy, but these cross-branch connections could support tasks that span multiple fields. Do existing systems already work this way, and are there any obvious flaws or practical problems with this approach? submitted by /u/Stringsoftruth
Originally posted by u/Stringsoftruth on r/ArtificialInteligence