Multi-Agent Articles
Browse 597 articles about Multi-Agent.
How to Build a Semantic Memory System for AI Agents Without Hermes Agent
Hermes Agent proved memory matters, but you can build better recall inside Claude Code. Learn storage, injection, and semantic search using local vector DBs.
How to Use Fable 5 as Architect and GPT-5.6 Sol as Worker in Multi-Agent Systems
Fable 5 excels at planning complex systems while GPT-5.6 Sol executes at lower cost. Learn how to combine both models in a single agentic workflow.
How to Use Grok 4.5 as a Cheaper Sub-Agent in Multi-Model AI Workflows
Grok 4.5 matches GPT-5.5 on coding benchmarks at $2 per million input tokens. Learn how to route tasks to it from a smarter orchestrator model.
How to Use Progressive Disclosure in AI Agent Design to Scale Capabilities
Progressive disclosure lets agents load only the instructions they need per query. Learn how Pydantic AI 2.0 implements this pattern to prevent context bloat.
How to Decide When to Use a Single Agent vs a Multi-Agent Team
Four questions determine whether your task needs one agent or many: size, independence, separation of concerns, and checkability. Here's how to apply them.
What Is GPT-5.6 Ultra Mode? Multi-Agent Coordination for Demanding Tasks
GPT-5.6 Ultra spawns four or more coordinated agents to tackle complex tasks. Learn when to use it, what it costs, and how it compares to standard modes.
GPT-5.6 Sol vs Claude Fable 5: Which Model Wins for Multi-Agent Workflows?
GPT-5.6 Sol costs 3x less than Claude Fable 5 but falls short on creativity. Here's which model wins for different agentic use cases.
Hermes Agent vs Custom Claude Code Memory: Which Should You Build?
Hermes Agent is the fastest-growing open-source AI agent, but its memory has real limits. Here's when to use it versus building your own inside Claude Code.
What Is Pydantic AI 2.0? The Capability Primitive That Changes How You Build Agents
Pydantic AI 2.0 introduces a single composable unit called the capability that bundles tools, instructions, hooks, and guardrails. Here's how it works.
How to Use Fable 5 as Orchestrator and GPT-5.6 as Worker in Multi-Agent Workflows
Use Fable 5 for planning and review while GPT-5.6 Sol handles execution. This model routing pattern cuts costs by 10x without sacrificing quality.
GPT-5.6 Sol vs Claude Fable 5: Which Frontier Model Wins for Agentic Work?
GPT-5.6 Sol beats Fable 5 on cost and speed but falls short on creative quality. Here's when to use each model in your AI workflows.
How to Use the Advisor-Executor Pattern in Claude Code to Extend Your Fable 5 Limit
Use Fable 5 as an advisor and Opus or Sonnet as executor to get 93% of the work done at a fraction of the token cost—with a real example.
How to Build an AI Agent That Catches Its Own Hallucinations: The Checker Agent Pattern
Learn how to design multi-agent systems where independent checker agents verify every task output—catching hallucinations, shortcuts, and boss-model bugs.
How to Build a Complete Company from Scratch with One AI Agent Prompt
See how a single /goal prompt with Claude Fable 5 produced a business plan, brand, product, landing page, and launch videos in under 4 hours.
How to Use Claude Fable 5 as an Orchestrator Without Burning Your Token Budget
Use Claude Fable 5 for planning and review while delegating execution to Opus or Sonnet sub-agents—cutting costs by 10x with no quality loss.
How to Use Fable 5 as Architect and Grok 4.5 as Construction Crew in Multi-Agent Workflows
Use frontier models for planning and cheaper models for execution. This real example built a 50-district 3D city for $8 using this split-model pattern.
Multi-Agent AI Systems: How to Catch Hallucinations Without Reading Every Output
Learn how multi-agent swarms with checker agents catch hallucinations, worker shortcuts, and even boss-model bugs automatically—no human review needed.
Personal AI Agents vs Production AI Agents: When Markdown Stops Scaling
Understand the architectural difference between personal second-brain agents and production agents shipped to real users—and when to make the switch.
How to Build a Production AI Agent with Context Retrieval and Long-Term Memory
Learn how to architect production AI agents with database-backed context retrieval and semantic memory that scales to millions of users.
AI Industry Shift: Why the Model Race Is No Longer the Only Race That Matters
Meta is monetizing infrastructure, OpenAI is buying regulatory headroom, and the AI scoreboard has changed. Here's what it means for builders.