DNOTIFIER BLOGS

Tag: AI agentic

  • AI Orchestration vs Multi-Agent Systems: What’s the Real Difference?

    You’re building an AI product with a lot of moving parts. Models calling APIs. Agents making decisions on their own. Data flowing in from five different directions. At some point you stop and ask: do I actually need orchestration here, or do I need a multi-agent system? People throw these terms around like they mean…

  • What Is Shared Memory in Multi-Agent Systems?

    Picture three AI agents working on the same task. One agent pulls data. One writes code. One tests it. If none of them can see what the others just did, they repeat work, step on each other, or sit waiting for updates that never arrive. That’s exactly the problem shared memory in multi-agent systems solves.…

  • What Is AI Agent Delegation? A Guide for Enterprise Architects

    You can easily build a single AI agent. However, a single agent quickly fails when facing complex, multi-step enterprise workflows. If your main agent tries to handle databases, customer support, and financial processing alone, it gets overwhelmed. The system becomes slow, expensive, and highly prone to hallucinations.To solve this operational bottleneck, implementing AI agent delegation…

  • The Architecture of Distributed AI Workloads

    Multi-agent systems scale by distributing specialized tasks across independent, autonomous nodes rather than relying on one massive language model. This modular division reduces the processing burden on individual prompts and keeps context windows clean. To understand how do multi-agent systems scale, developers must look at workload parallelization. Instead of running tasks sequentially, a distributed architecture…