Paul Welty, PhD AI, WORK, AND STAYING HUMAN

· artificial-intelligence

Bookmark: From proof of concept to production: Embracing systems thinking

Transform your AI strategy with a systems-thinking approach, ensuring seamless transition from proof of concept to impactful production deployment.

Here’s a notable quote from the article: “AI at scale is a significant organizational change that must be managed and starts with ongoing investments in AI literacy and workforce readiness.” This underscores the transformative impact of AI on business operations.
From Proof Of Concept To Production: Embracing Systems Thinking

The article, “Flexible Work Can’t Replace The Office—But Here’s How To Make It Work,” discusses the challenges enterprises face in fully implementing generative AI (GenAI) beyond the proof-of-concept phase. Despite its transformative potential, many projects stall due to poor data quality, inadequate risk controls, rising costs, and unclear business value. To advance AI from conception to production, a systems-thinking approach is critical, viewing AI as a fundamental shift akin to enterprise resource planning systems. This involves strategy, secure AI applications, a robust data supply chain, well-defined AI operations, and a product-thinking mindset. Key considerations include establishing ethical and compliant AI strategies, securing data control, ensuring ongoing compliance, and integrating AI into core business functions. Successful AI deployment demands significant resource investment, focused on data quality, security, and infrastructure. Viewing AI as an evolving business element rather than a standalone technology is essential for sustained success. Through systemic thinking and continuous adaptation, organizations can leverage AI’s full potential as a cornerstone of their operational framework.

Why customer tools are organized wrong

This article reveals a fundamental flaw in how customer support tools are designed—organizing by interaction type instead of by customer—and explains why this fragmentation wastes time and obscures the full picture you need to help users effectively.

Infrastructure shapes thought

The tools you build determine what kinds of thinking become possible. On infrastructure, friction, and building deliberately for thought rather than just throughput.

Server-side dashboard architecture: Why moving data fetching off the browser changes everything

How choosing server-side rendering solved security, CORS, and credential management problems I didn't know I had.

The work of being available now

A book on AI, judgment, and staying human at work.

The practice of work in progress

Practical essays on how work actually gets done.

Dev reflection - February 20, 2026

I want to talk about the difference between execution and verification. Because something happened this week that made the distinction painfully clear, and I think it matters far beyond software.

Dev reflection - February 18, 2026

There's a moment in any system—a team, a company, a workflow—where the thing you've been optimizing for stops being the constraint. And you don't notice right away. You keep pushing on the old bott...

Dev reflection - February 17, 2026

I want to talk about staging areas. Not the technical kind—the human kind. The places where work goes to sit. The inbox you check before forwarding. The draft folder. The approval queue. The meetin...

Bookmark: I’m not convinced ethical generative AI currently exists

Explore the ethical challenges of generative AI, from data acquisition to environmental impact, and why true ethical solutions remain elusive.

Embracing AI in education: Balancing integrity with future workforce demands

Explore how educators can balance academic integrity with the need for AI literacy, preparing students for a future-driven workforce.

Bookmark: The next wave of automation: Will AI disrupt more high-skill jobs?

Explore how AI is reshaping high-skill jobs, driving the need for new skills and offering opportunities in a rapidly evolving job market.