https://sperixlabs.org/tags/llm-agents/Recent content in Llm-Agents on SPERIXLABSHugo -- gohugo.ioen-usSPERIXLABSMon, 21 Sep 2026 12:00:00 +0000https://sperixlabs.org/post/2026/09/the-function-that-beat-the-model-what-we-measured-when-we-removed-the-llms/Mon, 21 Sep 2026 12:00:00 +0000https://sperixlabs.org/post/2026/09/the-function-that-beat-the-model-what-we-measured-when-we-removed-the-llms/For months, a 1-billion-parameter model validated sensitive-data detections in our proxy pipeline. Last week we ran it against a 40-line Python function. The model kept 85% of the deliberately invalid test data — fake credit cards with broken checksums — and quietly dropped real IBANs, real social security numbers, and a person’s actual email address. The function caught every fake, kept every real one, and answered in ten microseconds. We didn’t set out to pick a fight with local LLMs. We set out to answer one question — can each layer of our pipeline do the same job, or better, without a local model? — and we refused to flip any switch until a benchmark said yes. What follow are the four experiments, the numbers, and the pattern hiding underneath them. The pattern matters more than the numbers.