jtbetz22

The $500M is part of a larger $3B gift that will also start a CMU campus in Miami, FL. The total gift is the largest individual donation to a US university in history.

I suspect they are fielding complaints that autonomous vehicles increase road traffic, so they want to show that they are encouraging the use of public transit. Uber and Lyft have long been blamed for an increase in overall traffic.

I periodically go through the big box of cables and pull out anything that I don't expect to ever need again.

I put those in another box, seal it completely, and write a message on the outside along the lines of "presumed useless - Sep 2016".

If I come across that box in, say, September 2026, I feel entirely comfortable tossing the whole thing.

> So even when you have a nicely structured commit history, you end up realizing that some things need to be changed and start appending a bunch of "fix" and "actual fix" commits at the end.

I have found that this no longer needs to be an issue with agentic coding tools.

Once I am happy with the end state of a branch, I tell Claude to rebuild the change from scratch as a set of atomic incremental commits. It adds about 2 minutes to the dev process, but creates a pr that is infinitely easier to review.

The overall thrust of the article is great, though. The tooling around prs needs a ton of attention.

This is really cool.

In general I think there has been (a) too little utilization of the hooks provided by agents for deterministic checks and follow-ups to agentic coding, and (b) too little investment in creating re-usable org-wide monitoring controls and reporting on convention enforcement.

Oculi looks like a strong advance on both fronts.

I find it is now 1000x more effective to draft documents in collaboration with Claude, working with a markdown file as the output format.

However, git doesn't work in my team as a document collaboration mechanism - the commenting and discussion on a file has so much more friction that Google Docs or Notion.

What I've ended up on is a workflow where I iterate on the doc until I am satisfied, then export it to notion (via MCP) and publish that for feedback. Once there is consensus on the notion doc, that becomes the artifact of record.

It's a suboptimal solution, though - claude makes a number of poor design choices when exporting .md -> notion.

Interesting. I don't know if people are trusting AI-generated code too much, but AI is generating way more code than humans can review, and the 'looks fine' bar is what the AI gets held to.

I strongly agree with you that the solution likely involves pushing the correction mechanism much closer to the point of code generation. You want to put the AI back on track as soon as it starts to stray, you can't let it build a lot on top of a mistake.

My own attempt at resolving this involves running a set of deterministic checks on agent-generated code at the end of every agent turn, along with a lightweight AI-powered review on every commit, and deep AI review on PRs before merge. I am pretty happy with the results so far.

At my company, we ask everyone in the hiring process about how they have used any kind of agentic coding tools.

We're not concerned about hiring for the 'skill' of using these things, but more as a culture check - we are a very AI-forward company, and we are looking for people who are excited to incorporate AI into their workflow. The best evidence for such excitement is when they have already adopted these tools.

Among the team, the expectation is that most code is being produced with AI, but there is no micromanager checking how much everyone is using the AI coding tools.