PARCER as an Operational Contract to Reduce Variance, Cost, and Risk in LLM Systems
Systems based on Large Language Models (LLMs) have become formidable tools for automating research and software production. However, their governance remains a challenge when technical requirements demand absolute consistency, auditability, and predictable control over cost and latency. Recent literature highlights two phenomena that aggravate this scenario: the stochastic variance inherent in the model's judgment (often treated as "systemic noise") and the substantial degradation of context utilization in long inputs, with critical losses when decisive information is diluted in the middle of the prompt. This article proposes PARCER as an engineering response to these limitations. The fra...
| Authors | Elzo Brito dos Santos Filho |
|---|---|
| Primary category | cs.SE |
| Published | 1 March 2026 |
| Last updated at source | 1 March 2026 |
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