Building Agents is Easy; Achieving Reliability is a Continuous Process.

With everyone talking about building and using AI Agents, it's easy to get lost in the hype. But building reliable agents - ones that consistently solve real problems - is hard.

When thinking about agents, it's not just about building them; it's about testing, running, and continuously managing them over time.

The Problem Statement

With so many frameworks available - and in multiple languages - it has never been easier to build an agent. Agno, CrewAI, LangChain, Mastra, and others have made agent development incredibly accessible.

Building agents isn't the blocker anymore - deploying and maintaining them reliably, aligned with business needs and customer goals, is where the real challenge lies. This process cannot happen in silos; while developers set up and integrate these agents, non-technical users who understand the business context play a key role in refining prompts, iterating behavior, and ensuring agents deliver consistent value.

Observability, Logging, and (hopefully) Reliability

To build reliability, you need visibility - into the agent's reasoning, tool usage, and outcomes. Observability and Logging become essential. Without them, you're operating in the dark, reacting to failures instead of preventing them.

Because agents aren't workflows (explained here and by Harrison Chase as well), you simply cannot track through a deterministic path; they reason, act, and observe, which requires digging into their thinking process to understand why they made the decisions they did. When you opt into building a reliable agent, you are opting for autonomy at the expense of predictability.

Reliability, in this context, isn't about perfection. Rather, it's about predictability - knowing how and why your agent chose tool A over tool B and being able to align its behavior consistently over time.

The path to reliability

The future of agents lies in making both building and deploying them simpler and more reliable. While no-code and natural language interfaces will make agent creation more accessible, true progress will come from treating reliability through deployment pipelines as a first-class concern.

True progress requires:

• Versioning and rollback built into the deployment process
• Integrated monitoring and observability
• Continuous improvement and feedback loops
• Accessible no-code or natural language interfaces that make collaboration between developers and business facing users easier to achieve

Achieving reliability isn't a single feature; it's a continuous process. It comes from tight feedback loops, real-world testing, observability, and proactive management - not just clever prompts or bigger models.