Beyond Vibe Coding: Engineering Resilient AI Agents with FSMs, Privacy, and Cost Controls

Short summary

Argues that vibe-coding with LLMs hits a production ceiling due to non-determinism, statelessness, and security risks. Proposes wrapping LLMs in Finite State Machines for predictable control flow, local privacy layers for PII protection, and cost controls for economic viability. Includes a Python flight-booking agent example demonstrating FSM-driven state transitions with LLM intent extraction.

• •FSMs provide deterministic control flow, error handling, and debuggability around LLM calls
• •Local privacy layers redact PII before sending data to public LLM APIs
• •Cost controls cap token usage to keep agent interactions economically viable

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