Let’s imagine we are implementing deterministic behavior for agent systems using control techniques (harnessing). Suddenly, we observe that the agent's actions and responses begin to become clumsy, an
designednotmagic.hashnode.dev4 min read
Design-driven AI. Real tools. No tricks.
Really enjoyed this perspective. The idea that uncertainty should be treated as an explicit part of the system rather than simply another error to patch really stood out to me. It’s tempting to keep adding guardrails whenever an agent behaves unexpectedly, but that can eventually make the system overly rigid. I especially liked the comparison with exception handling in distributed systems it makes the concept much easier to understand. Defining where deterministic control ends and where the agent is allowed to reason and adapt seems like an important architectural decision. Looking forward to seeing how the next parts explore reliability and maintainability in practice.
Joselo Martinez
Thank you so much! Coming from a team that develops a production-grade SaaS like BotSailor, this means a lot to me. Managing omnichannel state (WhatsApp, Telegram, etc.) must make balancing the line between deterministic and probabilistic behavior incredibly complex. If a sales bot "hallucinates" a workflow, the impact on the business is immediate. I’m really looking forward to reading your series on "Agent AI in Production" to see how you handle state persistence. Cheers!