Best practices for reliable AI agents.
Best practices for reliable AI agents.
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September 8, 2025
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Agent frameworks are graduating from prototype to production. This shift from exploration to operation demands a new level of engineering discipline. The very creativity that makes language models powerful in open-ended tasks can quickly become a liability once reliability is required. Without clear, formal boundaries, agents hallucinate function calls, mishandle data structures, and fail in ways that are opaque and difficult to diagnose. The answer lies in precisely defining the interfaces through which they interact with the world.
The problem begins with a paradigm mismatch. A probabilistic, generative system is being connected to a deterministic, rule-based environment. The agent relies on inference, producing outputs that appear logical within its training but may be wrong within the specific context of an application. A small slip, a misremembered function name, a mistaken assumption about a default parameter, or a misread return value, registers as a minor semantic error to the agent. To the API beneath it, that same slip is a fatal exception. At this point of integration, weak or missing contracts create not a bridge but a fault line.
A common belief is that detailed natural language documentation will protect the system. It will not. Documentation is written for humans; contracts are written for machines. A more useful way to think about it is through aviation. Pilots are highly trained, yet they rely on pre-flight checklists. The checklist does not replace expertise; it ensures that expertise is applied within a framework that prevents oversights under pressure. An interface contract serves the same role for an agent. It is a set of machine-readable, enforceable rules that prevent slips in reasoning from escalating into cascading failures.
Strong contracts rest on three pillars: schemas, conditions, and failure modes.
Explicit Input and Output SchemasEvery input and output must be defined with precision. Inputs require exact data types, validation rules, and a designation of whether they are optional or required. Outputs need the same treatment, covering both successful returns and structured error states. Schemas form the first line of defense, stopping malformed requests and ambiguous responses before they spread further into the system. They turn vague instructions into binding agreements.
Formal Preconditions and PostconditionsSchemas describe the data; conditions describe the logic. Preconditions establish what must be true for an operation to make sense, such as whether a user is authenticated or whether a record exists. These checks protect the system from faulty assumptions. Postconditions verify that the intended change actually occurred. Together, they turn a function call into a verifiable transaction.
Defined Failure PathsResilience comes from design, not hope. A contract must make explicit what happens when a tool fails. This includes rules for retries, fallback strategies, or human escalation. Too often, this layer is neglected, and agents drift into undefined states that cause cost overruns and operational failures. Clear failure paths create protocols for graceful degradation rather than chaotic collapse.
The absence of contracts shows up in the frustration of developers working with agent frameworks. Debugging often devolves into tracing natural language reasoning logs, searching for intent rather than investigating actual actions. Contracts create a separation of concerns. The agent decides on the strategy: the what and the why. The contract governs the execution: the how. This separation makes accountability possible. When a failure occurs, it is immediately clear whether the fault lies in reasoning or in execution. That clarity is the foundation of debuggability and trust.
Some argue that this level of rigor slows teams down. This is a grave misconception. Teams that avoid contracts spend countless hours firefighting incidents caused by malformed calls and unexpected failures. Strong contracts provide the guardrails that allow agents to move quickly without spiraling into error. They are not bureaucracy. They are discipline applied in a way that protects both speed and reliability. In practice, contracts eliminate the bugs that erode trust and create the conditions for agents to succeed at production scale.
How structured traces cut debugging time from hours to minutes.
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