LLMs are probabilistic by nature – probability buys flexibility, never 100% accuracy. So can a Tln + LLM agent pipeline promise same input, same output? The honest answer is a split: the decision core is provably deterministic, the LLM edge is only reproducible. Determinism comes from architecture, not from taming the model.
LLMs are excellent at writing code, but bad at making business decisions. Cloudflare’s Code Mode idea – let the model write the script, and let an expert system run it – is a natural fit for EITL. A claims-processing example in the Tln language.
Managing AI agents in the enterprise means solving for security, knowledge access, and orchestration at the same time. A look at OpenTalon – an EITL-first framework that combines LLMs with expert rules for corporate AI architecture.