# Taming LLMs in Production: Control Patterns for Coding Agents

Learn how control stacks, budgets, validation, and safe fallbacks reduce loops, hallucinations, and inconsistencies in production LLM systems.

**By Team Innovaccer**

February 5, 2026

**Contributed by** Ritik Jain

Production LLMs can look impressive in demos, but in the real world they often fail in repeatable ways: infinite loops, runaway edits (“crazy cursor”), tool-chain fragility, hallucinations, and inconsistent clinical summaries. This whitepaper argues that reliability doesn’t come from “smarter prompts,” but from engineering a **control stack** around the model. It lays out practical patterns, **budgets, disciplined state/context management, schema validation, reflection/critics, routing, and safe fallbacks**, to make LLM systems controllable and auditable. Along with playbooks and checklists, it shows measurable gains like reduced loop rates and higher consistency for clinical workflows.