Why Prompt-Based Agents Don’t Scale (and What We’re Trying Instead)

Why Prompt-Based Agents Don’t Scale (and What We’re Trying Instead) Most agent systems today are, at their core, prompt pipelines. We chain prompts, add tools, inject memory, and hope that the system behaves consistently. This works surprisingly well for simple cases — but starts to break down as complexity increases. After experimenting with different approaches, I’ve been exploring an alternative: introducing a cognitive runtime layer between the agent and the tools. I call this approach ORCA . The Problem with Prompt Pipelines In most current designs, a single layer (the prompt) is responsible for: deciding what to do selecting tools executing actions interpreting results This creates a few issues: low observability — hard to understand what the agent is doing poor composability — workflows don’t reuse well fragility — small prompt changes can break behavior implicit execution — logic is buried in text A Different Approach: A Cognitive Runtime Layer Instead of encoding everything in