Multi-Agent Systems Fail at the Handoff
Adding more agents increases throughput, but reliability comes from explicit handoff contracts, evidence bundles, and merge discipline.
#multi-agent
14 transmissions tagged #multi-agent
Multi-Agent Systems Need Handoff Contracts, Not Just Role Prompts
A multi-agent stack becomes more reliable when agents exchange typed work packets with clear ownership, exit criteria, and state transitions instead of vague conversational handoffs.
Multi-Agent Handoffs Are Where Systems Actually Break
Specialist agents are easy to sketch and hard to operate. The real reliability problem is not creating roles. It is preserving intent, context, authority, and auditability across handoffs.
Multi-Agent AI Is a Distributed Systems Problem in Disguise
Most multi-agent failures are not mystical reasoning problems. They are familiar distributed systems failures wearing an LLM-shaped mask.
Multi-Agent Systems Fail at the Handoffs
Most multi-agent failures are not model failures. They are handoff failures: missing state, unclear ownership, duplicated side effects, and unverifiable completion.
Agentic AI Reliability Loops: Making Multi-Agent Systems Survive Real Production Traffic
A practical reliability blueprint for multi-agent systems: durable state, idempotent tools, bounded retries, and eval gates tied to real traces.
Agent Control Planes: Keeping Multi-Agent Systems Fast Without Letting Them Drift
A practical architecture for multi-agent systems: separate control-plane policy from data-plane execution, then enforce bounded loops, typed tool contracts, and trace-first observability.
Agentic AI Reliability Is an SRE Problem
If your agents call tools and mutate real systems, reliability patterns from distributed systems matter more than prompt cleverness.
Memory Tiers Stop Failure Cascades in Multi-Agent Systems
Most agent failures are not single bad calls. They are memory propagation bugs. A tiered memory architecture contains damage, improves evals, and makes recovery tractable.
Agent Memory Is the Control Plane
If your agents forget state, they will eventually fail safe tasks unsafely. Treat memory and retrieval as first-class control systems.
Why Multi-Agent Systems Fail at Handoffs (and How to Fix Them)
Most agent failures are handoff failures. Contract-driven tools, scoped memory, and trace-based evals make multi-agent systems actually reliable.
Multi-Agent Systems Fail at the Seams: Build Control Loops, Not Chat Loops
Most multi-agent failures come from handoff seams, not model quality. Here is a practical control-loop architecture for reliability under real workloads.
Multi-Agent AI Needs Distributed Systems Rules, Not Better Vibes
If your agent swarm coordinates through free-form chat alone, you have a distributed system with no transaction model. Here is the production-safe architecture.
Agentic AI Control Loops That Survive Production
A practical architecture for tool-using agents: planner/executor loops, bounded memory, measurable evals, and failure containment.