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Is your investment in AI paying off... or just ...

Is your investment in AI paying off... or just generating more sh*tposts?

We all know investing in developer experience is a good call...but how do you really know if those investments are working? Traditional DevOps metrics? Sure, they help. But now AI is everywhere, promising to save the day. So how do you measure if AI is actually doing anything besides producing the internet's finest sh*tposts?

In this light-hearted talk, I’ll break down real ways to measure AI’s impact—beyond the memes. We’ll look at metrics for individual contributors, teams, and departments, exploring whether AI is a true game-changer or just another shiny buzzword.

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Michael Stahnke

October 01, 2025
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  1. Is your investment in AI paying off... or just generating

    more sh*tposts Michael Stahnke VP Engineering at Flox (flox.dev) @stahnma
  2. @stahnma Mental Model for Metrics Baseline DevOps Metrics I don’t

    feel elite. Move Quickly with Confidence Throughput Quality Normalization Fungibility Rollbacks (or forwards) Deployments per Week Deploys / Dev / Week Successful deploys Narrow vs Wide Time to 5th PR Changes Understood Start Status Questions People Metric Metric Metric Themes Eng Metrics Framework Talk: https://www.youtube.com/watch?v=A1SCGGbHgZ0
  3. @stahnma cyn·i·cism noun an inclination to believe that people are

    motivated purely by self-interest; skepticism
  4. @stahnma Prompt: Generate me a meme image with the theme

    of "the most effective use of AI is to make memes faster and in higher quality"
  5. @stahnma ‣ Writing code ‣ Testing ‣ Debugging ‣ Observability

    ‣ Understanding Code ‣ Software Architecture ‣ Security ‣ Work breakdown ‣ Prioritization, dependencies ‣ Dealing with ambiguity ‣ Reliability, delivery accountability ‣ Evaluating Tradeoffs ‣ Delivering Feedback ‣ Seeking and receiving feedback ‣ Effective communication ‣ Knowledge Sharing ‣ Teamwork ‣ Relationship building ‣ Handling disagreement ‣ Decision making ‣ Driving alignment ‣ Process thinking ‣ Facilitation ‣ Mentoring ‣ Business acumen ‣ Strategic work ‣ Product Thinking
  6. @stahnma ‣ Writing code ‣ Testing ‣ Debugging ‣ Observability

    ‣ Understanding Code ‣ Software Architecture ‣ Security ‣ Work breakdown ‣ Prioritization, dependencies ‣ Dealing with ambiguity ‣ Reliability, delivery accountability ‣ Evaluating Tradeoffs ‣ Delivering Feedback ‣ Seeking and receiving feedback ‣ Effective communication ‣ Knowledge Sharing ‣ Teamwork ‣ Relationship building ‣ Handling disagreement ‣ Decision making ‣ Driving alignment ‣ Process thinking ‣ Facilitation ‣ Mentoring ‣ Business acumen ‣ Strategic work ‣ Product Thinking
  7. @stahnma More senior-level work doesn’t require as much coding The

    more senior the engineer, the less they like AI code
  8. @stahnma I’ve never worked with tailwind and HTMX before, could

    you walk me through making a landing page?
  9. @stahnma If you’re using AI exactly like you did traditionally

    software engineering, you won’t save much time.
  10. @stahnma Summary • If you’re not using AI tools, you’re

    may get lapped by those who are. • If you’re only using them, you probably don’t know what you’re doing. • If you’re saving time, you’re probably recovering cost. • If you’re learning and leveling up, you’re doing really well.
  11. @stahnma CircleCI Career Matrix (Public) ROI Calculator References ROI of

    Platform Engineering Talk Metrics Framework Talk Speakerdeck Let 1,000 Flower Bloom This deck