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Totally agree. With the speed at which code can be written and deployed today due to AI, the emphasis should shift onto the review. Does the code actually run properly, are all of our assumptions correct, and are there any unintended side effects?

I've found the review and debugging process to be much more time consuming than writing/producing code, and just "praying it works" never ends well.

The problem with this is that so many diffs created by AI are gigantic. Thousands and thousands of lines of code, per PR. Of course this is fine if AI is creating, reviewing AND merging, but it's an exercise in futiliy for human reviewers, as there is no way for them to catch up.

Companies that allow this will quickly lose control over code quality. The company should have PR size guidelines, and/or developers need to feel confident that they can say "please split into smaller PRs"

MCP is something people think of as a "panacea" to all AI issues. I think people are beginning to realize it is just one, albeit important, part of a successful AI architecture.

First of all, people have been saying this for a long time. It’s nothing new, at least half a year, maybe closer to a year.

Secondly, it’s not even that important, it’s the tool calling itself that’s important. MCP servers are just a convenient way to interact with remote services when a command line utility for the same would be inconvenient.