The Most Important AI Agent Design Choice: Don’t Let the Model Be the Final Authority
AI agents are getting very good at doing things . They can search databases, call APIs, modify tickets, draft code, update records, trigger workflows, and interact with production systems. And that changes the engineering problem. When an LLM only generates text, a bad answer is usually just that: a bad answer. When an LLM can take an action, a bad answer can become a bad state change . So the most important question in agent architecture is no longer: Can the model figure out what to do? It is: Who decides whether the model should actually be allowed to do it? Those are two very different responsibilities. And I think one of the most useful principles for production AI agents is surprisingly simple: Use the model to reason. Don’t automatically give it authority to execute. The architecture that works beautifully in demos A lot of agent demos reduce to something like this: User → LLM → Tool → Action The model receives a request. It reasons about what should happen. It selects a tool. It generates the parameters. The tool executes. That is an incredibly productive abstraction. It is also a risky one when the tool can affect something real. The same probabilistic system is effectively doing two jobs: deciding what it believes should happen; authorizing that thing to happen. You can try to fix this with prompting: Always ask for confirmation before making important changes. But that is still an instruction. It is not a security boundary. The difference becomes clearer when you compare the two architectures. %%{init: {'theme':'base','themeVariables': { 'primaryTextColor':'#111827', 'secondaryTextColor':'#111827', 'tertiaryTextColor':'#111827', 'textColor':'#111827', 'edgeLabelBackground':'#FFFFFF', 'lineColor':'#4B5563' }}}%% flowchart LR subgraph BAD["❌ Demo-Style Agent"] direction LR A["User"] --> B["🧠 LLM"] B --> C["🔧 Tool"] C --> D["💥 Real-World Action"] end subgraph GOOD["✅ Production-Oriented Agent"] direction LR E["User"] --> F["🔎 Evidence"] F --> G["🧠 LLM"] G --