The Shift to Multi-Agent Architecture
In 2026, the AI agent landscape has fundamentally changed. Single-agent systems are being replaced by coordinated multi-agent teams.
Three Key Lessons
1. Tool use is table stakes, not a feature
If your agent can't call APIs, browse the web, and execute code, it's not competitive. The bar has moved.
2. Cost has collapsed
Running a capable agent 24/7 now costs less than a junior developer's coffee budget. This changes the economics of automation entirely.
3. Architecture matters more than model size
The companies winning right now aren't the ones with the biggest models. They're the ones with the best agent architectures.
What's Working
- Customer support agents that actually resolve issues
- Code review agents that catch bugs humans miss
- Research agents that synthesize across 50 sources in minutes
- Content agents that maintain brand voice across platforms
The Stack
- Specialized agents (each with a focused tool set)
- An orchestrator (routes tasks, manages state)
- A feedback loop (human corrections improve the system)
- Observability (traces, metrics, logs)
What agent architectures are you building?
