I built Plandex[1] to try to enable a more sustainable approach to vibe coding. It writes all of the model's changes to a cumulative version-controlled sandbox by default, which in my experience helps a lot to address many of the points raised in the article. While there are still categories of tasks I'd rather do myself than vibe code, the default-sandbox approach makes it feel a lot less risky to give something a shot.
On another note, a related but somewhat different technique that I think is still under-appreciated is "vibe debugging", i.e. repeatedly executing commands (builds, tests, typechecks, dependency installs, etc.) until they run successfully. This helps a lot with what imo are some of the most tedious tasks in software development—stuff like getting your webpack server to startup correctly, getting a big C project to compile for the first time, fixing random dependency installation errors, getting your CloudFormation template to deploy without errors, and so on. It's not so much that these tasks are 'difficult' really. They just require a lot of trial-and-error and have a slow feedback loop, which makes them naturally a good fit for AI.
I put a lot of focus on execution control in Plandex in order to make it helpful for these kinds of problems. It's built to be transactional—you can apply the changes from the sandbox, run pending commands, and then roll back all changes if the commands fail. You can do this repeatedly, even letting it continue automatically for some number of tries until the commands succeed (or you hit the tries limit). While there are some limitations to the terminal modality in terms of UX, I think this is an area where a CLI-based agent can really shine.
1 - https://github.com/plandex-ai/plandex