I don't have as many years of professional experience as you do, but IMO code pissing is one of the areas LLMs and "agentic tools" shine the least.

In both personal projects and $dayjob tasks, the highest time-saving AI tasks were:

- "review this feature branch" (containing hand-written commits)

- "trace how this repo and repo located at ~/foobar use {stuff} and how they interact with each other, make a Mermaid diagram"

- "reverse engineer the attached 50MiB+ unstripped ELF program, trace all calls to filesystem functions; make a table with filepath, caller function, overview of what caller does" (the table is then copy-pasted to Confluence)

- basic YAML CRUD

Also while Anthropic has more market share in B2B, their model seems optimized for frontend, design, and literary work rather than rigorous work; I find it to be the opposite with their main competitor.

Claude writes code rife with safety issues/vulns all the time, or at least more than other models.