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I'm not sure I like Claude Code using the phrase "hand-written" for something IT did. I had to change that to "agent-written" in a README.MD file it created.
We are moving from a world where you buy a specialized tool to a world where you generate a specialized tool, but then realize you aren't equipped to operate it.
If AI commoditizes the creation of code, the real value shifts to the lifecycle of that code.
I just can't get you out of my head
Claude Code, your codin' is all I think about
I just can't get you out of my head
Claude Code, its more than I dare to think about
Every night
Every day
Just to be there in your arms
Won't you stay
Won't you lay
Stay forever and ever, and ever, and ever
How many of us begrudgingly live with legacy software?
How many jobs are impacted by inefficient workarounds or manual processes because of legacy software?
How much productivity could be unlocked if we can update or completely transform this software (or the process itself)?
The adage "if it ain't broke, don't fix it" may not hold up that well in the new age of AI coding agents. They change the math by lowering the cost of exploring options.
https://hbr.org/2026/02/ai-doesnt-reduce-work-it-intensifies-it
I can 100% attest to this. The distinction between day and night, or weekday and weekend, has significantly blurred for me. Just today, I mentioned to a coworker that Claude Code makes me feel like I'm in my 20s again, except now I have much more experience. Combined, it's a superpower.

One of the promises of AI is that it can reduce workloads so employees can focus more on higher-value and more engaging tasks. But according to new research, AI tools don’t reduce work, they consistently intensify it: In the study, employees worked at a faster pace, took on a broader scope of tasks, and extended work into more hours of the day, often without being asked to do so. That may sound like a win, but it’s not quite so simple. These changes can be unsustainable, leading to workload creep, cognitive fatigue, burnout, and weakened decision-making. The productivity surge enjoyed at the beginning can give way to lower quality work, turnover, and other problems. To correct for this, companies need to adopt an “AI practice,” or a set of norms and standards around AI use that can include intentional pauses, sequencing work, and adding more human grounding.