I spent last weekend building a local log parser that uses small language models to debug production errors. It took me exactly 48 hours from idea to first successful deployment. The tool is called LogWhisper. It runs entirely on my laptop. No data leaves my machine. No API keys required. You might wonder why I built this when Datadog and Sentry exist. The answer is simple. Cost and privacy. My startup processes about 50GB of logs daily. Our current observability bill hit $1,200 last month. That number scared me. It was growing 15% month over month. I needed a way to find the needle in the haystack without paying for the whole haystack. Most AI tools for devs focus on code generation. Few focus on runtime analysis. Even fewer do it locally. The Problem With Cloud Observability Cloud observability platforms are great. They offer beautiful dashboards. They send alerts to Slack. But they have two major flaws for early-stage teams. First, they are expensive. You pay for ingestion. You pay for retention.…