Blog

The Patterns Hiding in Your AI Workflow

2026-04-09

LLMs are where web design was in the late 1990s — creative chaos before the patterns solidified. This article maps the workflow patterns already emerging from daily practice: from prompt layering and context shaping to multi-pass pipelines and the shifting boundary between tool and collaborator.

Performance Tests That Produce Numbers, Not Answers

2026-01-24

Performance tests often run successfully while answering no clear question. This article explores why performance testing fails when intent is missing, and how a lightweight, experimental mindset can turn metrics into meaningful answers.

Running LLMs Locally: Overconditioning, Right-Sizing, and Multi-Pass Pipelines

2026-01-18

A practical look at running LLMs as system components rather than assistants. Based on processing thousands of ASR transcripts, this article covers prompt overconditioning, model right-sizing, local execution tradeoffs, and why multi-pass pipelines with validation outperform single, all-in-one prompts.