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Blog — AI Prompts & Prompt Engineering — Page 12 | PromptABCD

AI Prompts & Prompt Engineering

Practical guides, templates, and tips for Claude, ChatGPT, Gemini, and beyond.

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Multi-Agent Systems

The Planner-Executor Split in Multi-Agent Systems

Mixing planning and execution in the same agent is one of the most common sources of multi-agent failure. The planner-executor split gives each concern its own agent — and the difference in reliability is significant.

September 23, 2026·11 min read

Multi-Agent Systems

Blackboard Architecture for AI Agents

Blackboard architecture is one of the oldest multi-agent coordination patterns — and one of the most underused in LLM systems. When agents need to collaborate without tight coupling, a shared workspace outperforms direct message passing.

September 23, 2026·12 min read

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Multi-Agent Systems

How Many Agents Is Too Many?

Every agent you add multiplies latency, cost, and failure surface. So how many agents does a multi-agent system actually need? The answer starts with understanding what each agent is for.

September 23, 2026·9 min read

Multi-Agent Systems

When Multi-Agent Systems Are Overkill

Not every problem needs a crew of AI agents. Multi agent overengineering is one of the most common — and expensive — mistakes in LLM application development. Here's how to spot it and fix it.

September 22, 2026·10 min read

Multi-Agent Systems

Voting and Consensus in Agent Teams

When multiple agents disagree, how does your system decide what's true? Multi agent consensus is more nuanced than majority vote. Here's the full decision framework.

September 22, 2026·10 min read

Multi-Agent Systems

Debate Between Agents to Improve Answers

When do multi-agent systems actually produce better answers through debate? The research is more specific than most tutorials admit — and the most important parameter isn't which agents you use, it's how many debate rounds you run.

September 22, 2026·10 min read

Multi-Agent Systems

Handoffs Between Specialized Agents

Picture this: you're debugging a multi-agent pipeline where the final output is wrong, and you can't tell whether the error came from Agent A or Agent B, because the handoff between them swallowed all the context. Here's how to build handoffs that preserve what matters.

September 22, 2026·11 min read

Multi-Agent Systems

The Router Pattern for Multi-Agent Systems

A 2025 analysis of production multi-agent failures found that misrouting — sending a task to the wrong specialist — was responsible for more quality failures than individual agent errors. The router is the most critical agent in your system.

September 22, 2026·11 min read

Multi-Agent Systems

Sequential vs Parallel Agent Execution

Choosing between sequential vs parallel agents sounds like a performance question, but it's really a dependency question. Get it wrong and you'll either slow down tasks that could parallelize, or corrupt state between agents running simultaneously.

September 22, 2026·11 min read

Multi-Agent Systems

Roles and Responsibilities in an Agent Crew

Most guides on agent roles responsibilities focus on what each agent should do. The more important question is what each agent should refuse to do — and most multi-agent systems never answer it.

September 22, 2026·10 min read

Multi-Agent Systems

CrewAI vs AutoGen vs LangGraph

Which framework wins between CrewAI, AutoGen, and LangGraph? The honest answer is that the question is wrong — each framework wins for a specific type of problem, and picking the wrong one is a month of rework.

September 22, 2026·9 min read

Multi-Agent Systems

Building a Multi-Agent System With LangGraph

Picture this: you're a developer who just got a LangGraph multi-agent system working in a notebook, then watched it behave completely differently when you added a state reducer. State management in LangGraph is the hard part — here's how to get it right.

September 22, 2026·11 min read