Building an LLM Evaluation Pipeline That Outlasts Models
An evaluation pipeline designed as durable infrastructure caught 23 regressions and reduced model migration from 6 weeks to 9 days across 4 model transitions.
Adam Mosley
Product-oriented leader with 8+ years developing, launching, and scaling digital platforms across the full product lifecycle. I've modernized enterprise systems, automated data workflows, managed portfolios of 1,000+ annual programs, and supported $1M+ in revenue through data-informed strategy. Currently building AI-powered tools and writing about systems, philosophy, and the human experience of building things.
Core Competencies
Directed development, enhancement, and launch of 30+ digital offerings. Defined product scope, delivery models, pricing, and go-to-market strategy. Built modular learning content and micro-credential pathways from concept through market delivery.
Led enterprise platform implementations coordinating functional and technical requirements across IT, vendors, and engineering stakeholders. Integrated enrollment, communication, and credentialing workflows across 5+ systems. Designed automated badge and credential logic.
Recovered and rebuilt a 15,000-record SQL database, restoring historical integrity and improving lead conversion. Designed automated data workflows and centralized datasets supporting enrollment, revenue, marketing, and executive reporting. Built dashboards for forecasting and performance tracking.
Designed multi-agent orchestration systems and local LLM infrastructure. Built automation pipelines replacing hours of manual work with single CLI commands. Developed job application assistants, content publishing workflows, and SEC filing data pipelines processing 36,791 records.
Oversaw delivery of 1,000+ annual programs ensuring scalable operations and consistent quality. Built multi-system scheduling and payroll automation eliminating 9,000 manual interactions per cycle. Coordinated 15+ instructors and managed cross-functional execution across marketing, enrollment, and platform teams.
Performed financial analysis, revenue modeling, and multi-year forecasting supporting $1M+ in gross revenue. Designed comprehensive pricing proposals and employer-sponsored training frameworks. Analyzed enrollment funnels to identify conversion gaps and optimize marketing spend.
Experience
Directing product development and launch of 30+ workforce offerings. Leading enterprise platform implementations across 5+ systems. Performing financial analysis and revenue modeling supporting $1M+ in gross revenue. Managing facility relocation and hybrid learning environment buildout.
Launched consulting practice focused on small business operations and marketing systems. Established Jira-based project workflows, developed social media strategy, and built vendor outreach and communication systems for client engagements.
Oversaw delivery of 1,000+ annual non-credit programs. Recovered and rebuilt a 15,000-record learner database. Built Canvas-based product components and micro-credential pathways. Streamlined instructor onboarding, payroll, and scheduling workflows across 15+ instructors. Scaled operations from 4 staff to 20+.
Supported registration, logistics, and customer service for 1,000+ annual training sessions. Built a multi-system scheduling and payroll automation tool eliminating 9,000 manual data interactions per cycle. Improved communication workflows supporting 20,000+ annual student interactions.
Financial analysis, client reporting, regulatory documentation, and compliance.
Data validation, QA testing protocols, technical documentation, and test script development in engineering environments.
Selected Case Studies
An evaluation pipeline designed as durable infrastructure caught 23 regressions and reduced model migration from 6 weeks to 9 days across 4 model transitions.
A hybrid inference architecture routing between local and cloud models cut costs 67% while eliminating data sovereignty concerns for 45,000 daily healthcare queries.
Redesigning RAG as foundational data infrastructure reduced per-query costs 75% and improved answer accuracy from 67% to 91% across 2.3 million monthly queries.
Recent Essays
The average gap between AI capability deployment and regulatory response is 26 months. During that gap, organizations have a moral obligation to self-govern rather than exploit the vacuum.
Only 4 of 23 AI systems evaluated had undergone adversarial testing. Untested systems averaged 3.7 exploitable vulnerabilities including prompt injection and data extraction paths.
Cost-aware architecture patterns reduced monthly cloud data spend from $14,200 to $6,800 without degrading query performance. Five techniques every data engineer should apply.
Education
University of Missouri-St. Louis · Expected 2026
Coursework in psychology, philosophy of science, and statistics. Pursuing Clinical Psychology PhD specializing in existential psychology.
Excel Power User · SharePoint Collaboration Specialist · Power Automate Efficiency · Access Database Management
Research Interests
Technical Skills
From the Notebook
The Strangler Fig pattern replaces legacy systems incrementally, avoiding the big-bang rewrite that fails 62% of the time. Steady progress over dramatic overhaul.
Vector database selection is a standard data architecture decision. Evaluate query patterns, scale, operational overhead, integration, and 24-month total cost.
Context window limits force editorial decisions about what a model gets to know. The strategies for managing this constraint are epistemological choices, not just optimizations.
Automation debt compounds faster than technical debt because automated systems fail silently while manual processes fail visibly. When no one monitors, understands, or can safely modify an automated process, it becomes a liability disguised as efficiency.