Software engineer. Love Mobile!Keywords: Android, Appengine, Python, Golang, Java, NodeJS, etc. Learning Machine Learning. Experience with google cloud and AWS.
> Git itself wasn't designed for that load, and bolting AI onto platforms not built for agents is the biggest mistake of this era. We're doing a generational rebuild of the underlying infrastructure to handle agent-rate work as the default. Git itself is being reengineered for machine scale. The monolith is giving way to modern, API-first, composable services
Two big red flags here.
First git itself is distributed and built for scale.
I guesss they mean “gitlab” instead of “git”. But such a huge mistake would never go unnoticed.
Are they going to rebuilt git??
Secondly: a big rebuilt of monolith to services. Firstly there is nothing wrong with a Modulith. Secondly “rebuilt” will cause a lot of busy work without immediate value for customers.
And first of all: this announcement is done due to the stock price not AI
The productivity increase with AI is inflated because they want their stock price up.
Sell Gitlab stock while you can.
The leadership team has no clue what they are doing.
Sadly non engineering leaders buy into this dogma. AI is very usefull but in my experience doesn’t 10x if you don’t YOLO it.
There are two kid of specs, formal spec, and "Product requirements / technical designs"
Technical design docs are higher level than code, they are impricise but highlight an architectural direction. Blanks need to be filled in. AI Shines here.
Formal specs == code
Some language shine in being very close to a formal spec. Yes functional languages.
But lets first discuss which kind of spec we talk about.
We make the creator of the PR responsible for the code. Meaning they must understand it.
Also, we only allow engineers to commit (agent generated) code. Designers just come up with suggestions, engineers take it and ensure it fits our architecture.
We do have a huge codebase. We are teaching Claude Code with CLAUDE.md's and now also <feature>.spec.md (often a summary of the implementation plan).
I dont like the "impure" label. But the guts of it is right. Most software solves a business problem. Even the "pure" ones could choose to deliver value sooner with tech debt.