Why delivery economics once forced heavy QA

AI is bringing massive changes to our industry, but it's not just about how fast you can write code or use agentic flows. In this episode, I explore how AI is fundamentally shifting the economic bottleneck of software development, and how you can use your systems-thinking engineering mindset to adapt and thrive in this new era.

🎧 Episode Notes: The Engineering Bottleneck Shift

For years, the software development pipeline was designed around one core assumption: engineering is the most expensive and restrictive bottleneck. Because of this, organizations optimized heavily for upstream risk mitigation to ensure we only built what was absolutely necessary. But AI is changing that math, making the act of coding significantly cheaper and faster. Here is what happens when that bottleneck breaks:

• The Historical Cost of Bugs: I look back at the Windows 95 era, where physical software delivery meant post-release bugs were incredibly expensive, demanding massive upfront QA.
• The Continuous Delivery Precedent: Discover how the internet made software updates cheap, which fundamentally changed the ROI of risk mitigation and enabled fast, iterative soft releases.
• The Upstream Shift: Understand why, as engineering throughput increases by 50% to 100% due to AI, the new organizational bottlenecks will rapidly shift upstream to product, design, and decision-making.
• Optimizing for Speed Over Risk: Learn why companies will likely begin to lessen their focus on risk mitigation (outside of catastrophic data breaches) to prioritize higher volume throughput and decision speed.
• The New Iterative Workflows: Explore the potential for consolidated roles where engineers, PMs, and designers use AI to make rapid, on-the-fly product decisions together without traditional hand-offs.
• Your Core Engineering Value: Remember that punching cards or manually managing memory didn't define engineers in the past, and manually typing code doesn't define you now. Your true value is your ability to approach problems with a systems-thinking mindset.

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