Cord: Coordinating Trees of AI Agents

This is my question also but a bit different.

Is there any reason to explicitly have this binary decision.

Instead of single primitive where the parent dynamically defines the childs context. Naturally resulting in either spawn or fork or anything in between.

My small agent harness[0] does this as well.

The tasks tool is designed to validate a DAG as input, whose non-blocked tasks become cheap parallel subagent spawns using Erlang/OTP.

It works quite well. The only problem I’ve faced is getting it to break down tasks using the tool consistently. I guess it might be a matter of experimenting further with the system prompt.

[1]: https://github.com/matteing/opal

I have yet to read this article (in full), but I love trees! As an amateur AST transformation nerd. Kinda related but I’ve been trying to figure out how to generalize the lessons learned from this experiment in autogenerating massive bilingual dictionary and phrasebook datasets: https://youtu.be/nofJLw51xSk

Into a general purpose markup language + runtime for multi step LLM invocations. Although efforts so far have gotten nowhere. I have some notes on my GitHub profile readme if anyone curious: https://github.com/colbyn

Here’s a working example: https://github.com/colbyn/AgenticWorkflow

(I really dislike the ‘agentic’ term since in my mind it’s just compilers and a runtime all the way down.)

But that’s more serial procedural work, what I want is full blown recursion, in some generalized way (and without liquid templating hacks that I keep restoring to), deeply needed nested LLM invocations akin to how my dataset generation pipeline works.

PS

Also I really dislike prompt text in source code. I prefer to factor in out into standalone prompt files. Using the XML format in my case.

This is the comment I was looking for. In the last month or so this is how Claude Code represents tasks, as a DAG of objectives, built from plan mode.

I agree, Claude does spawn subagents but subagents don't spawn sub-subagents.