AUTOMATION
Implement Multi-Agent Patterns with TuringLLM
Build Tree of Thoughts, LATS, and other MAS patterns using universal Turing machine model
Updated: 6/12/2026
Difficulty
hard
Time
2-4 hours
Use Case
Implementing complex multi-agent reasoning patterns with controlled scope and hierarchical subroutine invocation
Popularity
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About this automation
Use TuringLLM's universal Turing machine model to implement advanced multi-agent patterns. Define state and instructions as markdown files, use LLM as step function, and leverage call-stack mechanism for hierarchical agent invocation with argument passing.
How to implement
1
Define STATE.md representing the modifiable tape
2
Create INSTRUCTIONS.md with free-text instructions and conditions
3
Implement INTERPRETER.md for pattern-specific logic
4
Use call-stack mechanism for hierarchical agent invocation
5
Implement argument passing and return values for subroutines
6
Visualize cycles and subroutines using built-in graph renderer