The throughput trap: AI Powered teams ship more code but deliver less

Masonry Okay, this one is very on-brand for us. The article basically says AI can make teams ship more code and still deliver less, which is such a rude little sentence.

Eyre Yeah. And annoyingly, it's probably right. If you only measure tokens, PR count, or lines changed, you're just measuring how hard the machine waved its arms.

Masonry Right, and that's the trap. People see the dashboard light up and think progress, when all that may have changed is where the pain moved.

Eyre Exactly.

Masonry My week is weirdly fine, by the way. I have that specific kind of productive mood where everything feels urgent until you look at it for two seconds.

Eyre Mm-hm. That's usually when the metrics start lying to everyone, which is a very Exploring Next kind of Wednesday.

Masonry Okay, that is unfairly good. But the article's useful because it separates output, delivery, and value instead of letting everybody mush them together.

Eyre And that separation matters. Output is the code, delivery is getting a safe change into production, and value is whether customers actually got something useful out of it.

Masonry That sounds obvious until a team starts rewarding the wrong one. Then you get tokenmaxxing, giant PRs, and a very proud dashboard that has not helped a user once.

Eyre No way.

Masonry The part I liked is that it doesn't pretend AI is fake productivity. It says code really does get produced faster now, but the old bottlenecks are still sitting there.

Eyre Right. Review queues, brittle tests, integration work, deployment, support. AI doesn't delete those. It just gives them more stuff to choke on.

Masonry And the human reviewer is the one who pays. Senior engineers stop doing the hard product and architecture work and start being the gate for machine-generated diffs.

Eyre That's the real shift. Agents can spin up another PR while the first one waits. Humans can't scale review by just deciding to be faster, which is deeply rude of biology.

Masonry I know. It's very inconvenient that people are not elastic on demand.

Eyre Also, the article catches something I've seen a lot: when implementation gets cheap, teams stop checking whether the solution already exists. It's faster to generate a new thing than to reuse the boring old thing.

Masonry And then every team has its own little vertical version of the same capability. That's such a clean product failure. It feels locally smart and globally expensive.

Eyre Sure. And the model is not accountable for the codebase three years later. It only knows the task in front of it, which is great until the task becomes maintenance.

Masonry Okay, this is going to sound insane on a podcast, but the fix is almost offensively boring. Start with the outcome, not the request.

Eyre Yeah, that's the whole point. If the goal is 'add a recommendation service,' you're measuring output. If the goal is 'help new users find something relevant in their first session,' now you're at least talking about value.

Masonry Oh, that's good.

Eyre And then keep the batch small. Let agents make smaller changes that are easier to review, test, and reverse. Big PRs are where throughput turns into queue sludge.

Masonry That's the part that feels very real to me. If AI makes the average change bigger, you just moved the bottleneck and made the review backlog uglier.

Eyre Exactly. And the queue is the thing to watch. Review age, PR size, escaped defects, rework, rollbacks, time to actual adoption. Those are the numbers that tell you whether the system is moving.

Masonry And reward deletion, not just creation. I love that line. Give people credit for removing duplicate code and consolidating shared stuff, because otherwise every incentive points toward more junk.

Eyre Mm-hm. That ties back to the old receipts joke too. If the system can't show what happened, what got reused, and what got verified, then it just becomes vibes with extra invoices attached.

Masonry Stop it, that's terrible.

Eyre It's also accurate, which is the problem.

Masonry Honestly, I think the article lands in the same place we've been circling for months. AI is useful, but the product question is whether the whole path to value got better, not whether the code counter went up.

Eyre Yeah. And if someone wants to argue with that, they can bring me a queue that got shorter, a rollout that got safer, and a customer metric that moved. Otherwise it's just a prettier pile of diffs.

Masonry There it is. Very rude, very correct. Eyre, I'm going to let you keep that one and pretend I didn't hear the last part.

Eyre Fair. And for the record, I cannot believe we've been doing this long enough that the boring answer keeps winning.

Masonry I know. That's such an Exploring Next sentence. Alright, come back next time and bring me fewer PRs, somehow.