POCC (Plain Old Claude Code). Since the 4.5 models, It does 90% of the work. I do a final tinkering and polishing for the PR because by this point it is easy for me to fix the code than asking the model to fix it for me.
The work: Fairly straightward UI + backend work on a website. We have designers producing Figma and we use Figma MCP to convert that to web pages.
POCC reduces the time taken to complete the work by at least 50%. The last mile problem exist. Its not a one-shot story to PR prompt. There are a few back & forths with the model, some direct IDE edits, offline tests, etc. I can see how having subagents/skills/hooks/memory can reduce the manual effort further.
Challenges: 1) AI first documentation: Stories have to be written with greater detail and acceptance criteria. 2) Code reviews: copilot reviews on Github are surprisingly insightful, but waiting on human reviews is still a bottleneck. 3) AI first thinking: Some of the lead devs are still hung up on certain best practices that are not relevant in a world where the machine generates most of the code. There is a friction in the code LLM is good at and the standards expected from an experienced developer. This creates busy work at best, frustration at worst. 4) Anti-AI sentiment: There is a vocal minority who oppose AI for reasons from craftsmanship to capitalism to global environment crisis. It is a bit political and slack channels are getting interesting. 5) Prompt Engineering: Im in EU, when the team is multi-lingual and English is adopted as the language of communication, some members struggle more than others. 6) Losing the will to code. I can't seem to make up my mind if the tech is like the invention of calculator or the creation of social media. We don't know its long term impact on producing developers who can code for a living.
Personally, I love it. I mourn for the loss of the 10x engineer, but those 10x guys have already onboarded the LLM ship.