DNOTIFIER BLOGS

Category: Product & Platform

  • What Is Realtime Agent Orchestration?

    Picture this. You’ve got five AI agents working on a customer request. One pulls data, one checks inventory, one drafts a response, one flags risk, one sends the reply. Now picture them all working off information that’s thirty seconds old. That’s the problem realtime agent orchestration exists to fix. As teams move from single-agent tools…

  • Centralized vs Distributed AI Orchestration

    Your AI agents work fine in testing. Then you add a fifth agent, a sixth data source, and suddenly nothing talks to anything on time. This is the moment every engineering team hits the centralized vs distributed AI orchestration question head-on. Picking the wrong model here doesn’t just slow you down. It forces a painful…

  • What Is Agent Delegation?

    Agent Delegation is the process where a primary AI agent assigns specific subtasks to specialized sub-agents. Instead of solving an entire workflow alone, the primary agent evaluates the goal. It then routes smaller tasks to worker agents based on their specific capabilities. Definition: Agent Delegation is an architectural pattern where a central orchestrator assigns tasks…

  • Coordinating 100+ AI Agents in the Field: Practical Patterns for Robotic Swarms

    Introduction We shipped our first 10-robot demo and thought the hard part was solved. Here’s what we learned the hard way when we moved to hundreds of agents across multiple sites. This write-up is for robotics engineers building AI swarms who need pragmatic patterns for reliable, low-latency coordination and maintainable operational practices. The Trigger Everything…

  • What Broke After 10M WebSocket Events — Rebuilding Realtime Orchestration Without Reinventing the Stack

    Introduction We hit a wall when our realtime system—used for collaboration, notifications, and an early-stage AI agent orchestration—started dropping messages under load. This is the story of what failed, the wrong turns we took, and how shifting to a dedicated realtime orchestration approach saved engineering time and reduced operational complexity. The Trigger Users started seeing…

  • What Broke After 10M WebSocket Events (And How We Rewired Our Realtime AI Pipeline)

    Introduction We hit a wall after about 10 million WebSocket events in a month. Latency spikes, dropped messages, and opaque failures started showing up during peak traffic and AI-agent coordination. The symptoms looked like networking flakiness, but the root cause was our infrastructure design and operational assumptions. Here’s what we learned the hard way and…

  • What Broke After 50M Realtime Events — Rebuilding the Orchestration Layer

    Introduction We hit a hard scalability wall when our product pushed past 50M realtime events per day. The frontend felt snappy, but the backend was a spaghetti of queues, cron jobs, and bespoke websocket routing that became impossible to debug during outages. This is the story of the mistakes we made, the signals that mattered,…

  • We Replaced Our DIY WebSocket Orchestrator — Here’s What Finally Scaled

    Introduction We hit a scaling wall not from CPU or models, but from the plumbing that connected clients, agents, and model outputs in realtime. Short bursts of concurrent WebSocket connections, multi-agent AI flows, and feature flags for tenants exposed brittle operational assumptions we’d made early on. Here’s what we learned the hard way, and the…

  • What Broke After 10M WebSocket Events — How We Rebuilt a Realtime AI Orchestration Layer

    Introduction We hit a hard scaling wall after shipping a realtime feature tied to our AI agents. Latency spiked, message loss crept in, and ops time ballooned. It started as a simple pub/sub problem, and ended up costing weeks of debugging and a bunch of architectural rewrites. Here is what we learned the hard way,…