GitHub Identifies a Sooty Pot and Does Not Offer a Fix
January 9, 2025
This is an official dinobaby post. No smart software involved in this blog post.
GitLab’s Sabrina Farmer is a sharp thinking person. Her “Three Software Development Challenges Slowing AI Progress” articulates an issue often ignored or just unknown. Specifically, according to her:
AI is becoming an increasingly critical component in software development. However, as is the case when implementing any new tool, there are potential growing pains that may make the transition to AI-powered software development more challenging.
Ms. Farmer is being kind and polite. I think she is suggesting that the nest with the AI eggs from the fund-raising golden goose has become untidy. Perhaps, I should use the word “unseemly”?
She points out three challenges which I interpret as the equivalent of one of those unsolved math problems like cracking the Riemann Hypothesis or the Poincaré Conjecture. These are:
- AI training. Yeah, marketers write about smart software. But a relatively small number of people fiddle with the knobs and dials on the training methods and the rat’s nests of computational layers that make life easy for an eighth grader writing an essay about Washington’s alleged crossing of the Delaware River whilst standing up in a boat rowed by hearty, cheerful lads. Big demand, lots of pretenders, and very few 10X coders and thinkers are available. AI Marketers? A surplus because math and physics are hard and art history and social science are somewhat less demanding on today’s thumb typers.
- Tools, lots of tools. Who has time to keep track of every “new” piece of smart software tooling? I gave up as the hyperbole got underway in early 2023. When my team needs to do something specific, they look / hunt for possibilities. Testing is required because smart software often gets things wrong. Some call this “innovation.” I call it evidence of the proliferation of flawed or cute software. One cannot machine titanium with lousy tools.
- Management measurements. Give me a break, Ms. Farmer. Managers are often evidence of the Peter Principle, an accountant, or a lawyer. How can one measure what one does not use, understand, or creates? Those chasing smart software are not making spindles for a wooden staircase. The task of creating smart software that has a shot at producing money is neither art nor science. It is a continuous process of seeing what works, fiddling, and fumbling. You want to measure this? Good luck, although blue chip consultants will gladly create a slide deck to show you the ropes and then churn out a spectacular invoice for professional services.
One question: Is GitLab part of the problem or part of the solution?
Stephen E Arnold, January 9, 2025
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