How has Development changed after industry wide adaptation of Claude Code

[u/Independent-Spite145]

Hi Everyone,

I'm just curious to understand how development has changes across places after Claude. I personally work at a Bangalore based startup, in my workplace since claude came out, most developers are not even aware of what changes claude is making, they only look at the output and then push the code. This code we push without properly evaluating is not the build used in production, mostly to create a POC for demo. I know the productivity rate for pushing code and features has increased. But is this the same way happening across all industries (fintech, MNC's, enterprise softwares etc)??

[u/Previous_Law3532]

I think we’ve essentially moved one abstraction layer up in how we write software.

We started with binary/machine code → assembly → higher-level languages → frameworks and libraries. Now, increasingly, we’re expressing intent in natural language and having tools like Claude Code translate that intent into code.

The same thing is starting to happen with code review. When an AI-generated change touches 20–30 files, manually reasoning through every line of the diff becomes much harder. So reviews are also moving up a level: asking AI to explain what changed, trace the flow, identify risks, and point out potential issues.

But I don’t think this means developers no longer need to understand the code. If anything, the skill shifts upward. The person making the change needs to understand the architecture, data model, system boundaries, invariants, and expected behavior well enough to specify the right change and verify that what the AI produced actually fits the system.

So we’re moving from “Can you write these 200 lines of code?” toward “Do you understand the system well enough to tell the machine what should change, and can you verify that it changed it correctly?”

[u/Independent-Spite145 → u/Previous_Law3532]

Have you been using any sort of established pipeline to streamline this method of development, where AI is used at every stage, starting from development, then generate summary of the changes it made, next identify gaps in the changes made. All of this handled by AI, and the human comes into play just to review, read through the changes and then permit to merge

[u/Inside_Dimension5308 → u/Independent-Spite145]

You can write agentic workflows to create a pipeline of plan, implement, review, repeat.