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Tagged: multi-agent
Self-Healing Multi-Agent Team in LangGraph: Architect, Tester, Debugger
Build a LangGraph state machine in Python where an Architect, Developer, pytest sandbox, Debugger and Reviewer collaborate and loop until the tests pass.
31 min readParallel Coding Agents With Git Worktrees, Conductor and Antigravity 2.0
Parallel coding agents with git worktrees, Conductor and Antigravity 2.0: a coordinator, one worktree per agent, and a dozen SRE features in about five hours.
14 min readHow Subagents and Multi-Agent Systems Split Work and Cost Tokens
Subagents vs multi-agent systems: the orchestrator-worker design, four topologies, what each costs in tokens, and the cases where a single agent does better.
12 min readOpenAI's Managed Agents API: Hosted Sandboxes vs Self-Hosted Execution
How OpenAI's managed agent harness works in public beta: hosted Linux workspaces, self-hosted exec servers, context compaction, tool search and subagents.
8 min readMulti-Agent K-Drama Recommender: BERTopic, RAG and Reciprocal Rank Fusion
A taste-aware K-drama recommender: BERTopic trope tags, ChromaDB RAG, an interview agent, query expansion and Reciprocal Rank Fusion ahead of an LLM re-rank.
10 min readMulti-Agent Orchestration on Bedrock and LangGraph: Four Patterns
Supervisor-worker, pipeline, fan-out and debate patterns with LangGraph on AWS Bedrock, plus handoffs, budget guards, tracing and production failure modes.
22 min readTracing a LangGraph Blog Pipeline with Langfuse: Spans, Scores, Warnings
Instrument a multi-agent LangGraph pipeline with Langfuse: one trace per article, nested spans, warnings, scores, and a debugging routine for weak drafts.
8 min readLayer by Layer: Designing a Real RAG Retrieval Pipeline for AI Agents
Plan a RAG pipeline with SourceDocument and DocumentChunk contracts, chunking, embeddings and ChromaDB, all behind a RetrievalService that keeps the agent stable.
10 min readMaking Two Local LLM Agents Debate: Grounding, Fake Consensus, Schema Bugs
Two local LLM agents on Ollama made to debate by evidence, not persona: NLI grounding, a fake consensus bug, attack vs assertion checks and required fields.
7 min read
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