Featured work
QueryTuner
● live productA SQL performance analysis tool that catches slow queries before they hit production. Combines heuristic analysis with an LLM insights layer, and generates shareable reports across five SQL dialects.
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60+ posts on autoshiftops.com — here are the five most recent.
🧠 CPU-Only LLM Inference Explained: Quantization, GGUF, and llama.cpp
🤖 Best Practices for Developing AI Agents
↔️New Relic to ServiceNow Incident Automation(Lab Guide)
🚀 Building an AI Incident Copilot: How I Automated the First 15 Minutes of Every Production Incident
🚀 Building an AI-Powered Stock Trading Bot in Python
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Open source projects
Smaller tools built to solve real operational problems — incident response, alert fatigue, and database migration risk.
incopilot
A practical incident-triage CLI agent that automates the first 15 minutes of a production incident — the part that's usually pure improvisation.
github.com/AutoShiftOps/incopilot →alertdecider
An alert decision layer that normalizes noisy signals, applies an opinionated rule engine, and emits decisions with reasons — not just more alerts.
github.com/AutoShiftOps/alertdecider →SP Migration Companion
Analyzes stored procedures for safe database migration — validated as an AWS hackathon entry and built as a potential QueryTuner feature.
github.com/AutoShiftOps/sql-sp-companion →Where I publish
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