Oshan Ranasinghe

Work / AI / ML / Multi-Agent Task Solver

Multi-Agent System · LLM Agents

Multi-Agent Task Solver

A multi-agent system where specialised LLM agents collaborate on complex tasks — planner, executor, critic, and memory agents communicate through a structured message bus.

Section

AI / ML

Stack

Multi-Agent Systems · LLM Agents · Tool Use · Python

Category

Multi-Agent System · LLM Agents

Status

Core agent loop working, critic integration in progress

01 — Challenge

The core engineering challenge

Single-agent LLM systems hit a ceiling on complex multi-step tasks — decomposing work across specialised agents with explicit handoff contracts unlocks more reliable multi-step reasoning.

03 — Decisions

Engineering decisions and what they cost

01Each agent has a single defined role — no agent both plans and executes to prevent conflation.
02Inter-agent messages are typed and validated so the communication contract is explicit.
03The critic agent operates on outputs, not inputs — it cannot interfere with execution mid-task.

04 — Stack

Multi-Agent SystemsLLM AgentsTool UsePythonLangGraph