By skyforbes Prompt engineering falls apart under pressure. The real problem in enterprise AI isn’t intelligence, it’s determinism. So I built the Axiom Kernel: a governed synthetic OS that forces LLMs to behave like reliable compute engines instead of chatbots.
It runs identically on GPT, Claude, Gemini, Llama, Mistral, anything, thanks to a provider-neutral virtualization layer. Then I tried to break it.
Standard frameworks score ~4.5/10 on adversarial hardening. This system hit 8.2/10, near the ceiling for a text-only runtime. It stayed stable over huge context windows, resisted malicious inputs, and refused to drift.
Most people are building AI toys. I ended up building a problem solver.
Curious if anyone else here has pushed a single text-based framework past 1,000 pages, or if we're still mostly writing "Act as an expert…" prompts.