The study unfortunately looks only at individual productivity, not any org gains, and the big claim in the PDF is that adopters "merge roughly 24% more pull requests" over a four month period. not exactly headline-making material. There's no data in the paper whether those 24% extra pull requests actually added anything more valuable or not.
HeavyStorm•1h ago
Highly doubt. Pace for merging requests have not improved and teams at MSFT are terrible at reviewing said PRs. Longer PRs and more frequent requests were clearly creating more friction.
simonw•1h ago
What kind of metric would you trust for measuring organization gains?
jayd16•1h ago
It'll probably take a really good product built by a profitable company evangelizing an AI workflow with reproducible examples dating back a few years.
didibus•1h ago
I think number of features released to customers (not behind a feature flag or still being rolled out, but fully rolled out). And number of bug fixes (only those reported by customers).
Also just in general, customer satisfaction, acquisition, conversion, retention, etc.
Number of completed org-level roadmap items, org-level goals achievement rate, and so on.
I also think a good one would be seeing an increase in meeting estimation, like if project was estimated to take X days with Y devs, does the use of AI increased how often you met or beat those estimates in actual time/dev effort?
And you'd want to compare that against prior years, where no AI was used, within the same org, or try going 1 quarter without AI and another with and compare quarter to quarter.
wilkystyle•29m ago
I also think something along these lines is the correct answer. It can be hard to pin down an exact metric because once you start optimizing for a metric it tends to not be a good measure of the original thing anymore. But in general I think it comes down to some measure of feature velocity combined with a counter metric on support/maintenance burden.
"Number of PRs merged" seems like "number of lines of code" wearing a trenchcoat, and I thought we all agreed back in the 90s that number of lines of code was a terrible measure of software productivity...
cj•48m ago
Engineering headcount.
dnackoul•21m ago
We use a tool called Weave (I believe YC 25?) that analyzes PRs for "expert units of work" and shows lift from AI tools. My understanding is they have their own proprietary model that assesses the difficulty of each PR. I find the organization level view and pivots useful and aligned with intuitive expectations.
jdlshore•10m ago
Incredibly hard problem, but METR had a good method. They had people estimate how long a task would take (before knowing what tool would be used), and then randomly assigned each task to “with AI” or “without AI.” When the data was in, they compared actual/estimate ratios of the two populations.
(Presumably, they used a t-test that only compared people against themselves.)
Interestingly, for that study (released in 2025), participants self-rated themselves as 20% more productive, but were measured as being 19% less productive.
000ooo000•1h ago
Dependabot PR merges :rocket: :rocket:
frostlynx•11m ago
24% of increased productivity (yes, this is assuming of course that the “proxy” of merged PRs reflects productivity) is actually a pretty big deal. Given the salary of developers, this translates to tens of thousands of dollars per year, per developer.
My guess is they used # of PRs as a measure as it’s easy to obtain, while other measures are hard, may be due to other factors, etc.
FWIW I saw a similar number for myself, around 30% more PRs in the last 6 months, compared to the 6 months before that (I picked up agentic coding around at the start of the year). And a similar increase for closed issues.
In my case this clearly doesn’t translate to as much value for the organization, or rather, it’s hard to say, as many of those PRs were things I wouldn’t even have done without AI support. This means they were low priority. However, many were of the cleanup/refactor type, so they might result in speedups later.
gojkoa•3h ago
HeavyStorm•1h ago
simonw•1h ago
jayd16•1h ago
didibus•1h ago
Also just in general, customer satisfaction, acquisition, conversion, retention, etc.
Number of completed org-level roadmap items, org-level goals achievement rate, and so on.
I also think a good one would be seeing an increase in meeting estimation, like if project was estimated to take X days with Y devs, does the use of AI increased how often you met or beat those estimates in actual time/dev effort?
And you'd want to compare that against prior years, where no AI was used, within the same org, or try going 1 quarter without AI and another with and compare quarter to quarter.
wilkystyle•29m ago
"Number of PRs merged" seems like "number of lines of code" wearing a trenchcoat, and I thought we all agreed back in the 90s that number of lines of code was a terrible measure of software productivity...
cj•48m ago
dnackoul•21m ago
jdlshore•10m ago
(Presumably, they used a t-test that only compared people against themselves.)
Interestingly, for that study (released in 2025), participants self-rated themselves as 20% more productive, but were measured as being 19% less productive.
000ooo000•1h ago
frostlynx•11m ago
My guess is they used # of PRs as a measure as it’s easy to obtain, while other measures are hard, may be due to other factors, etc.
FWIW I saw a similar number for myself, around 30% more PRs in the last 6 months, compared to the 6 months before that (I picked up agentic coding around at the start of the year). And a similar increase for closed issues.
In my case this clearly doesn’t translate to as much value for the organization, or rather, it’s hard to say, as many of those PRs were things I wouldn’t even have done without AI support. This means they were low priority. However, many were of the cleanup/refactor type, so they might result in speedups later.