← ashleyweinaug.com
Q1 2026 · Jan 1 – Mar 19

GitHub Activity

100 PRs across 17 repositories and 12 products

This quarter I focused on AI-native engineering — building evaluation frameworks, multi-model infrastructure, and intelligent content pipelines. Alongside new feature delivery across a dozen products, I drove production stability work that eliminated memory crashes, closed security gaps, and improved query performance.

0
PRs Authored
98 merged, 2 open
0
PRs Reviewed
cross-team
0
Issues Created
38 closed, 12 open
0
Repositories
12 products

Work Themes

AI Platform Engineering
Built RAG evaluation infrastructure, multi-turn conversation assessments, and admin tooling for an AI-powered knowledge platform.
Data Platform & Reporting
Overhauled data exports and reporting pipelines, fixing memory issues in large-scale CSV generation and improving survey data workflows.
AI Content Pipelines
Developed automated content generation systems using LLMs for SEO, marketing copy, and structured data extraction across multiple products.
Performance & Reliability
Eliminated OOM crashes, resolved N+1 query patterns, and hardened authentication on sensitive endpoints to improve system stability.
Product Development
Shipped new user-facing features including coaching chatbot personas, email marketing integrations, and multi-district user support.

Key Highlights

AI & Intelligent Systems

RAG evaluation pipeline — Built a full evaluation framework with test cases, automated runners, scheduled assessments, and admin UI, establishing measurable quality standards for AI responses
Multi-turn evaluator — Extended evaluation beyond single Q&A to assess conversational coherence across multi-step interactions, catching regressions that single-turn tests missed
Multi-provider LLM infrastructure — Decoupled the AI platform from a single LLM provider, enabling model flexibility, cost optimization, and resilience against provider outages

Production Quality

Memory crash fixes — Rewrote CSV export pipelines to stream to disk instead of buffering in memory, eliminating out-of-memory crashes that were taking down production servers
Query performance overhaul — Identified and resolved N+1 query patterns across report generation, reducing database load and preventing cascading memory failures
Endpoint security hardening — Added authentication requirements to sensitive reporting and data closure endpoints, preventing unauthorized access from bots and crawlers

Feature Delivery

Coaching chatbot persona — Created a specialized AI persona for coaching use cases, giving organizations a guided experience tailored to professional development conversations
Email marketing integration — Connected lead capture to an email marketing platform with share URL support, closing the loop between product engagement and nurture campaigns
Multi-district user model — Redesigned the data model to let users belong to multiple districts, a significant structural change that unblocked cross-district collaboration features