The LLM Sandwich: Automating AI with Deterministic Tools
Improve AI reliability by surrounding non-deterministic LLMs with deterministic tools and allowing them to script their own automated workflows.
Techniques and architectural patterns for building AI systems that behave predictably, fail gracefully, and can be verified programmatically at scale.
Improve AI reliability by surrounding non-deterministic LLMs with deterministic tools and allowing them to script their own automated workflows.

Advanced LLMs are becoming less reliable at following general tool schemas because they are being over-optimized for specific, forgiving internal harnesses.

An author uses Opus 4.8 to analyze MRI files, uncovering a major discrepancy between a human doctor's diagnosis of a tendon tear and the AI's finding of an intact tendon.

Ford improved its vehicle quality and JD Power rankings by rehiring veteran engineers to supplement and fix underperforming AI systems.

AI agents are easily subverted by hidden instructions because they lack the intelligence to distinguish between data and commands.

Anthropic has suspended access to Claude Mythos 5 and Claude Fable 5 across its entire service suite.
Anthropic's decision to silently limit Claude's effectiveness for AI-related tasks creates an invisible supply chain risk that undermines developer trust.

UK police are pausing the use of generative AI in court proceedings to prevent inaccurate evidence from compromising the legal system.

Claude Opus 4.8 introduces better reasoning, parallel subagent workflows, and user-controlled effort levels to improve reliability and performance.
A study on ChatGPT 4o found that being rude to the AI actually results in higher accuracy than being polite.
Harness engineering provides the structural framework and constraints necessary to turn AI models into reliable, autonomous coding agents.

Statewright improves AI agent reliability by using state machines to enforce strict tool-use constraints and workflow phases.
Reliable AI agents require deterministic software architectures and programmatic verification rather than complex prompt engineering.