A Study of Microsoft's Early 2026 Rollout of Claude Code and GitHub Copilot CLI

by softwaredoug • 9 days ago

70 41 9 days ago

gojkoa3• 9 days ago

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• 9 days 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• 9 days ago

What kind of metric would you trust for measuring organization gains?

jayd16• 9 days 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.

didibus2• 9 days 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.

cj• 9 days ago

Engineering headcount.

dnackoul• 9 days 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• 9 days ago

Incredibly hard problem, but METR had a good method. They had people estimate how long a task would take (before knowing whether AI 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.

jimsperry• 9 days ago

Microsoft itself has a system for measuring this which outlines a few example metrics: https://queue.acm.org/detail.cfm?id=3819080

There was a nice talk about this by one of the author's at this year's BUILD conference: https://build.microsoft.com/en-US/sessions/BRK210

gojkoa3• 8 days ago

ultimately product success metrics such as market share and revenue, but those are lagging and might not be measurable over a 4 month period (the original study duration). beyond that, behaviour changes for users (is the product more useful?). those can be measured more frequently and can be compared to the previous period. if not that, than delivery output metrics such as cycle time for development (are we delivering faster?) paired with failure demand (% of tickets we thought were delivered but required rework/fixing). PRs are tied to effort/delivery process inputs, not outputs.

000ooo000• 9 days ago

Dependabot PR merges :rocket: :rocket:

frostlynx• 9 days 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.

Arainach• 9 days ago

24% PRs isn't 24% more productivity. Lines of code isn't productivity, and neither is CLs landed. What's the feature velocity of the team? How much time is being spent on rollbacks, outage responses, etc.?

Here's a quick hack to triple your PRs landed: Land a PR, then land ANOTHER PR undoing that one when you realize it was full of bugs, then land the PR again once you realize management doesn't care about quality, they just care about the number of PRs landed.

btown• 9 days ago

Given that Microsoft's overhead to actually landing features has, from what I've heard, long been more about dodging the cross-org and inter-org "guns" famously depicted in [0] and [1] than coding time... a 24% increase in merged PRs is massive!

[0] https://static.ma.nu/publications/images/2013.07.12_new_york...

[1] https://newsletter.pragmaticengineer.com/i/138252015/drawing...

pushplay• 9 days ago

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.

That's not necessarily bad. It could be a sign of effective prioritization. If you're good at working on the most important thing, and suddenly find yourself 24% more productive, what extra are you working on? The things that wouldn't have quite made the cut before.

onion2k2• 9 days ago

I've also seen an increase in merged PRs, but it coincided with developers opening smaller PRs. In other words, AI made devs break work down more so they opened more PRs for the same work. That's still good, because smaller increments are better, but there' no actual increase in coding productivity, and it means the context-switching burden from review work went up e.g developers slowed down in a different area.

unknownfuture• 9 days ago

Yeah welcome to the state of the art in measuring AI impact. I have contacts at a few different larger tech companies that are fully AI pilled (the one I work at included) and every single one has forgotten the last 50 years of lessons in measuring dev productivity and hyperfocused on PR throughput and token usage.

Fun fact: all the data I've seen suggests at most a 50% uplift in those metrics. And that's at the top percentiles. Its very clear that the already high performers see the greatest uplift but anyone in that meaty middle will only see incremental gains.

kg• 9 days ago

My personal experience was that I saw AI adopters opening and merging more PRs but I also spent more of my day reviewing PRs than I did in the past, in order to keep up with the flood of new stuff. Reconcile that with MSFT's repeated layoffs however you like.

threatripper• 9 days ago

To me the biggest gain I see is that you take the programmers out of the loop. Instead of formulating your ideas to start a project and then acquiring the resources to do a single iteration on it which may take months if not years, now many specialists "just do it" and do several such iterations in a single day. Afterwards they may still go the ordinary route via programmers but on a completely different level and a lot of fruitless work is frontloaded and 100x cheaper. This doesn't show up in any such statistic.

So, the question is not "Does it make our programmers more productive?" but "Does it make our organization faster?".

royal__• 9 days ago

To be fair they do acknowledge this directly in the abstract. Kinda hard to have a good heuristic for this stuff, what would you propose?

byzantinegene• 9 days ago

more features doesn't mean anything if they don't translate into economic value, refactoring prs and dependency updates are easily automated now and it saves alot of productivity, but if you compare the costs and economic value gained it might not actually justify enterprise token spending.

anshumankmr• 9 days ago

281 billion tokens. Using the least expensive version of Claude Opus 4.6, which costs $5 for every million tokens, that one user alone could have cost Meta more than $1.4 million.

And that is based on the pricing that they sell a dollar for less than a dollar so the costs may be much much more.

simonreiff• 9 days ago

I really wish this study had chosen to focus on more useful endpoints like revenue, profitability, customer retention, conversion rate, etc....at a minimum, don't look at PRs merged without also looking at bugs in production code, number of incident reports, features shipped, debt log canceled, etc. Even if you only want to consider merged PRs, you should weigh the productivity of the reviewer and whether they are also 24% boosted or else it's just an accounting trick.

onion2k2• 9 days ago

The problem that I'm finding in my own work on figuring out the impact of AI is that there's just no reliable way to connect things directly to AI usage. Most of the tooling does things like "The user used AI on the same day that they opened this PR, therefore we'll assume the AI was used to write the code in the PR." In a mature AI-driven org that might be true, but in the rollout phase of an AI experiment it absolutely isn't.

Until there's a good way to fix that gap in the data any measure of AI impact is going to be horribly flawed.

sorokod2• 9 days ago

Completely disable the usage of AI for time period t. Compare the impact on whatever before t and during t.

saghm• 8 days ago

It's wild how we need to rediscover Goodhart's Law every time we have a new thing we think might increase productivity.

dzonga• 9 days ago

negative ROI - when you start using actual business metrics.

it's in everyone's best interest to keep those numbers covered.

xamut2• 9 days ago

The number of merged PRs increased. But what does that actually tell us?

There is no comparison of the complexity, or depth of those PRs with work previously done without agents. The authors themselves acknowledge that PR count rewards small, frequent PRs and that whether the additional output justifies its cost remains unanswered. We do not know whether end-to-end feature delivery became faster, whether the additional output justified the cost, or what happened to defects, maintainability, review effort, and rework.

The conclusion seems to be little more than: Microsoft engineers are using AI tools, Microsoft is spending more on AI usage, and AI vendors are earning more subscription and token revenue.

More PRs are not necessarily more value. Without quality, delivery-time, and ROI metrics, the claimed productivity gain is largely meaningless.

jvuygbbkuurx• 9 days ago

Especially in conditions where AI assisted PRs are tracked for performance.

I had some extra usage on claude yesterday and put several ultra workflows to look for code cleanup opportunities. It made -40 tasks and PRs just like that. This is 10% of all PRs/commits in the project history, but the before and after is arguably meaningless.

xamut2• 9 days ago

Exactly. Once AI-assisted PR count becomes a performance metric, the metric is no longer merely incomplete—it actively creates an incentive to generate more tasks and PRs

npunt• 9 days ago

Context: measuring productivity at all is hard. It was hard when computers were introduced into the workplace, when the internet was introduced, etc.

I worked with a journalist who covered tech in the 80s & 90s and she remembered that studies then didn't show improvements in productivity with the adoption of computers, despite people feeling as though they were more productive.

Reminds me of this Jeff Bezos quote:

"The thing I have noticed is when the anecdotes and the data disagree, the anecdotes are usually right. There's something wrong with the way you are measuring it."

A Study of Microsoft's Early 2026 Rollout of Claude Code and GitHub Copilot CLI

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