AI Won’t Fix a Bad Process: The Posture Your Code Needs
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AI is faster, but not if the process is broken. Emily Bache’s Trombone Paradox tells us that adding a powerful AI tool to a faulty software workflow can amplify the very bottlenecks you hoped to bypass. The message isn’t anti-AI — it’s a plea for engineering posture: align people, process, and tooling before you chase speed.
When AI meets a bad process
As the video framing suggests, AI-assisted coding can feel like strapping a turbocharger onto a car that won’t shift gears. The risk isn’t just that AI writes sloppy code; it’s that downstream bottlenecks in testing, integration, and risk management become the new choke points. A recent industry read from IBM argues that while AI accelerates code generation, bottlenecks in the software development lifecycle often lie far from the keyboard, in coordination, understanding, and delivery of change. The lesson: speed up the wrong part of the system and you only go faster to the same problems.
Sources & further reading
IBM — Discusses that improvements in coding speed do not automatically fix larger bottlenecks in the software delivery lifecycle, supporting the article’s central claim about ‘posture’ over speed.
TechXplore — Provides a broader view of how AI is reshaping software development beyond code-writing, aligning with the piece’s argument about process and delivery.
Gary Marcus on AI hype — Frames the conversation about hype and safety in AI, offering a cautionary counterpoint to speed-focused AI narratives.
Definitions
Agentic AI
AI that can autonomously perform tasks and take actions to pursue goals, rather than just suggesting outputs.
Trombone Paradox
Emily Bache’s metaphor that adding AI to a poor process can worsen downstream bottlenecks, like a heavy trombone amplifying the problem.
Process posture
The disciplined alignment of people, practices, and tooling to ensure AI augments rather than undermines software delivery.
Test-Driven Development (TDD)
A software development approach where tests drive design and implementation, creating a reliable feedback cycle; AI-generated tests should be integrated within this discipline to avoid brittle results.
