The hidden cost of context switching in AI workflows
Multi-step AI workflows lose information at every boundary. The handoff between steps is where accuracy degrades, latency compounds, and cost accumulates. Most teams do not measure it.
AI WorkflowsAutomationProduction AIAI ArchitectureMulti-Agent Systems
The token budget problem: why your production agents run out of room
Context windows are finite. Production workloads are not. Here is what actually breaks when an agent exhausts its budget, and three patterns that prevent it.
AI EngineeringProduction AIToken OptimizationContext WindowsMulti-Agent Systems
Why long-running AI agents fail silently
Long-running AI agents degrade silently: no errors, only drifting outputs. Here is how context pressure builds and how to catch it early.
AI EngineeringProduction AIMulti-Agent SystemsObservability
Most multi-agent systems are sequential pipelines wearing a costume
Most 'multi-agent' systems are sequential pipelines with role-play prompts. Three diagnostic questions to tell the difference.
Multi-Agent SystemsAgentic ArchitectureProduction AI
Beyond Chatbots: Multi-Agent Architecture Patterns for Production
Single-model AI hits a ceiling fast. Four multi-agent architecture patterns we use to coordinate specialized agents in production.
Agentic ArchitectureMulti-Agent Systems