Does AI make developers more productive?

“we are seeing doubling in the code output for engineers”

Balaji KrishnamurthyChief Financial Officer · Executive, Uber

“Since the beginning of 2025, we've seen a 30% increase in output per engineer, with the majority of that growth coming from the adoption of agentic coding, which saw a big jump in Q4.”

MetaPublished by the organization itself (earnings call), no named author

“Our PR throughput inside of Airbnb is 65% higher than it was before we introduced agentic AI.”

Christopher SansonProduct Lead, AI Developer Experience · Leader, Airbnb

“For example, groceries took eight months, nine months, and airport pickups took about six weeks to develop.”

Brian CheskyCo-founder and Chief Executive Officer · Executive, Airbnb

“reduced the time from concept to delivery by as much as 60%”

AirbnbPublished by the organization itself (regulatory filing), no named author

“we've increased the number of features and improvements we shipped this year by nearly 80%.”

Brian CheskyCo-founder and Chief Executive Officer · Executive, Airbnb

“We're seeing even stronger gains with power users of AI coding tools, whose output has increased 80% year over year.”

MetaPublished by the organization itself (earnings call), no named author

“19,000 software developers have experienced efficiency gains of over 20% through real-time coding assistance”

Bank of AmericaPublished by the organization itself (post), no named author

“In May 2026, Anthropic averaged around 2,500 code changes merged per day; as of September, we merged over 30,000 per day.”

AnthropicPublished by the organization itself (post), no named author

“Total merged changes more than doubled year over year in August, from roughly 8,100 to 17,000.”

SpotifyPublished by the organization itself (post), no named author

“In the first 11 days of running the dependency workflow, the backlog of open issues fell by about 70%.”

Erin SonSenior Engineer · Practitioner, Shopify

“the number of issues with a pull request attached by someone in an engineering, product, or design function has grown sevenfold”

LinearPublished by the organization itself (post), no named author

“And all of this led to twice the number of lines of code per engineer year over year.”

Uday Kiran MedisettyDistinguished Engineer · Practitioner, Uber

“Organizations running this model report 3 to 5x productivity gains. Legacy backlogs that once ran to thousands of work days shrink to hundreds. Time to market compresses from quarters to weeks.”

BCG PlatinionPublished by the organization itself (post), no named author

“We have like 50 users and I don't want to scare people, but the PR throughput for these folks is like 3X higher again.”

Christopher SansonProduct Lead, AI Developer Experience · Leader, Airbnb

“more than 99% of our engineers use AI coding tools every week, 94% report that AI has made them more productive”

SpotifyPublished by the organization itself (post), no named author

“we're seeing a 76% increase in pull request frequency”

SpotifyPublished by the organization itself (post), no named author

“we complete about 189 tickets for this sprint, which is about four times as much or two to three times more than what we usually accomplish”

Xiucheng QuekSoftware engineer · Practitioner, Genentech

“we run around 50,000 builds a week, a number that is only increasing with AI adoption among our engineering teams accelerating commit rates and productivity”

Aditya AnchuriTech lead, Ruby Infra Platform team · Practitioner, Stripe

“This translates to an average throughput of 3.5 PRs per engineer per day, and surprisingly the throughput has increased as the team has grown to now seven engineers.”

OpenAIPublished by the organization itself (post), no named author

“engineers using it ship about 70% more merged pull requests”

OpenAIPublished by the organization itself (post), no named author

“roughly corroborates the 67% increase in merged pull requests”

AnthropicPublished by the organization itself (paper), no named author

“Today, … used by several tens of thousands of engineers every single week to review all of their code. So we also know, generally speaking, the number of pull requests that each of these people are writing. The median … user writes 50 pull requests a month, so call it about … per work day. The 90th percentile writes 500 pull requests per month. That is a drastic difference between the median and the P90. The P99 is in the thousands of pull requests.”

Daksh GuptaCo-founder · Executive, Greptile

“all of a sudden all the design docs and all the Slack messages and all the emails have gotten three or four times as long and … gotten two or three times as many emails and they say basically as much as they did before.”

Eyal BlumSoftware Engineer · Practitioner, Figma

“I aligned with three other teams for another week on that and then I just sent it to an agent to implement overnight and it came back, this is probably from two … not one, but it's basically six weeks of coding work … only one week. So that's where I get … 5X speed up if I include the review cycle at the end…”

Eyal BlumSoftware Engineer · Practitioner, Figma

“So for example, when … playwright … came out instead of having humans navigate the code now, the agent can explore the code. That was a big win unlock for productivity in a lot of our team.”

Eyal BlumSoftware Engineer · Practitioner, Figma

“And so it's not uncommon to spend a week writing a very detailed plan, making all the decisions, flushing it out, iterating, sending it out to teammates to review. And then only when it's read and you've … out all the decision, … to the agent, the agent will send it back to you when it's implemented … has been really successful also in accelerating and also really restoring some of the joy into the development process.”

Eyal BlumSoftware Engineer · Practitioner, Figma

“You could figure out which ones took less tool calls, … which one made less errors, which one produced the correct outcome, and deterministically know what's going on. The point is you can start building data-driven systems without ever writing a single line of code. … in order to build a programming language, it wouldn't have taken eight people. It wouldn't have taken less than two years. It would have taken hundreds and thousands and tens of thousands of man hours, and then you would still have a broken system. And today, we can just spend billions of tokens and make it work, and we can make it stable.”

Vaibhav GuptaCo-founder and Chief Executive · Executive, Boundary (BoundaryML)

“We built an architecture.md file. Instead of using … MD, just pick something that every model can just understand. This file has to be incredibly small, and it can only have things that will not change for months or for years. In our case, it's the layers of the compiler. … So now we have standards so anyone can use whatever they want.”

Vaibhav GuptaCo-founder and Chief Executive · Executive, Boundary (BoundaryML)

“When we started building BAML, I didn't think it would be possible to build some of the software we did. And just yesterday, one of … engineers built a partial C compiler, purely in BAML. … Our processes have to evolve if we're going to ship at agent speed.”

Vaibhav GuptaCo-founder and Chief Executive · Executive, Boundary (BoundaryML)

“We do no code reviews. We require every engineer to work on things in parallel, and we have no standardization how people do AI.”

Vaibhav GuptaCo-founder and Chief Executive · Executive, Boundary (BoundaryML)

“The job changed, and most of us didn't even notice, we're harness engineers now. Our work is the system that helps produce and verify the code. The constraints, the gates, the skills, the verification.”

Andrew OrobatorSenior Software Engineer · Practitioner, Reddit

“On the Square side, we took a list of features sellers had been waiting on for months and our engineers shipped them in days. Builderbot handled the scaffolding and the repetitive work, and our engineers made the decisions that shaped the product.”

Brad AxenHead of AI Capabilities · Leader, Block

“it grew like 7X over, the last, I think it was, two months, three months, something like that. And then you see our engineering headcount growth. It’s, gone up by, 10% or something.”

Walden YanCo-founder and Chief Product Officer · Executive, Cognition

“90% of these teams used Kiro, among other internal tools that we have, and what they found was it wasn't about the tools, it was about the way that they worked. The teams that achieved step function improvements intentionally changed the way that they worked, and the other simply kind of sprinkled Kiro and some of the other tools that we have on top of their existing way of working.”

Clare LiguoriSenior Principal Engineer, AWS · Practitioner, Amazon

“And sometime last year, we knew, or I say we, but the bedrock team knew that they were going to need to build a new inference data plane. But they had estimated it at 30 people over 18 months. This is a big, big service, and it was … take time to build the new one, migrate customers over, migrate models over, and they decided to take a step back. They took six people and they built it in 76 days with …”

Clare LiguoriSenior Principal Engineer, AWS · Practitioner, Amazon

“Previously, writing code manually was the bottleneck. I find that with an Amazon, we've found the speed of decision making becomes a new bottleneck. … When it used to take nine to 12 months to build a new product, it didn't matter so much in the overall wash of things if it took two months to make the decision to build the product and then two months to approve the launch. But now, those are the bottlenecks. … Often, I find that frontier engineering teams spend more time making decisions than they do writing code.”

Clare LiguoriSenior Principal Engineer, AWS · Practitioner, Amazon

“And completely anecdotally based on my own experience, I've really only felt maybe 10 to 20% more productive with all of these phases that have come before. But now inside of Amazon, we've been running pilots with different teams across the company, and we've been seeing a median of 4.5x productivity improvement and sometimes more than 10x.”

Clare LiguoriSenior Principal Engineer, AWS · Practitioner, Amazon

“So another experiment that I want to talk about is an experimental sprint that was done in the Prime Video Organization. They took a 10-day sprint and they … experiment where they put, again, six engineers in a room and they let them go wild with Kiro. They brought down the project delivery time estimate from what was going to be 90 weeks down to 24, based on all of the progress they had made in this 10-day sprint.”

Clare LiguoriSenior Principal Engineer, AWS · Practitioner, Amazon

“The second one is slowing down to speed up. In almost every team that was interviewed, they reported that their productivity actually went down, as they intentionally adopted a new way of working. That's counterintuitive, right? You have to do intentional engineering work before you're gonna see that hockey stick curve in productivity improvement.”

Clare LiguoriSenior Principal Engineer, AWS · Practitioner, Amazon

“They watched 50 teams that were totally … distribution of early career folks, mid-career senior engineers, and that worked on existing systems. … And they watched them for the better part of last year, and they found something super interesting. They found that there was a big difference in the productivity gains that they saw between half of the teams and the other half. And in this case, they used a productivity metric of deployment velocity to production. … And they saw that for half of the teams, they achieved less than 3X increase.”

Clare LiguoriSenior Principal Engineer, AWS · Practitioner, Amazon

“Back in 2024, we were seeing that engineers would get their first review within three hours. Now, in 2026, that has grown to nine hours, in addition to all of the volume changes. So in short, code review is now the bottleneck that we are running into.”

Will BondStaff Engineer, AI Foundations team, Development Platform organization · Practitioner, Uber

“requests and tokens tell us like usage, like merge requests and pipelines tell us about platform activity, but they do not tell us what value … providing. … the more meaningful long-term question really is like what is the future velocity and outcomes that we can measure with less friction, getting changes out safely.”

Rajesh BhatiaSenior Director of Engineering, Cloudflare · Leader, Cloudflare

“The impact on developer velocity internally is clear: we’ve never seen a quarter-to-quarter increase in merge requests to this degree. As AI tooling adoption has grown the 4-week rolling average has climbed from ~5,600/week to over 8,700.”

CloudflarePublished by the organization itself (post), no named author

“it's not about how many tokens you use, it's about the throughput of your product and the quality of your product designs and how much you're shipping.”

Brian CheskyCo-founder and Chief Executive Officer · Executive, Airbnb

“at a minimum, it has allowed us to moderate the pace with which we are adding headcount there.”

Balaji KrishnamurthyChief Financial Officer · Executive, Uber

“Our bankers automate the research and presentation materials. Our developers code more efficiently, and all our teammates improve productivity, consistency, and client service”

Brian MoynihanChair and Chief Executive Officer · Executive, Bank of America

“Some of the technology is letting our people do more and be more productive.”

Goldman SachsPublished by the organization itself (earnings call), no named author

“It started with productivity and a more narrow component of the firm called engineering, but based on leveraging the firm's relationships with a number of different large language model providers”

Goldman SachsPublished by the organization itself (earnings call), no named author

“This is supported by AI-enabled productivity gains and continued cost discipline across the business.”

KlarnaPublished by the organization itself (regulatory filing), no named author

“What I started seeing in some of the more advanced kind of teams is that … rituals of, Hey, we're doing a planning and we're doing a retro in a team that they weren't about like, Hey, we had issues with the code, but we're seeing we had issues with the system. So on the retro part is like, Hey, the agent went over and over hit this problem. Can we fix the system? That's something you'll learn in the retro.”

Patrick DeboisProduct DevRel Lead · Practitioner, Tessl

“A year ago, agents triggered less than 3% of the deployments on Vercel. Now, they trigger around 29%, and we expect half of all deployments to come from agents soon.”

VercelPublished by the organization itself (post), no named author

“Our engineers are orchestrating fully autonomous digital task forces, firing off agents and accomplishing incredible things.”

Google (Alphabet)Published by the organization itself (post), no named author

“Pull requests arrive faster than human-driven review can stay meaningful.”

Bence A. TóthAuthor on the Zendesk Engineering blog (role not stated on the pages read) · Practitioner, Zendesk

“more than 12,000 engineers bankwide now have access to AI coding assistants, supporting efficiency and faster feature deployment.”

NatWest GroupPublished by the organization itself (post), no named author

“AI and Automation have helped IBM unlock extreme productivity gains across the company since January 2023, and we are on track to reach USD 4.5B in savings by the end of 2025.”

IBMPublished by the organization itself (post), no named author

“uReview today analyzes over 90% of the weekly ~65,000 diffs (equivalent of pull requests) landed at Uber.”

Sonal MahajanStaff Engineer, Programming Systems team · Practitioner, Uber

“We're talking about roughly a 10x increase in load on some systems. At most companies, that kind of growth might happen over two or three years. At OpenAI, we see it in about six months.”

Venkat VenkataramaniVP of Engineering, Applied Infra · Leader, OpenAI

“He's orchestrating 16 agents and he's going a whole lot faster.”

Will GaybrickPresident, Technology and Business (also styled President of Product and Business) · Executive, Stripe

“seller productivity has increased by 20%”

Will GaybrickPresident, Technology and Business (also styled President of Product and Business) · Executive, Stripe

“So one of the reasons we built … artifacts that we shipped a couple of weeks ago was partially for that, which is you would send somebody a PR, and then they'd be like, I don't know, man, this is like 2000 lines of code. It looks like code to me. And what we started doing instead is sharing much more like, here's a … artifact. Here's the explanation. Here's the intention of the change. Here's the trade-offs that were made.”

Mike KriegerHead of Anthropic Labs · Leader, Anthropic

“It's now more than half. So more than 50% of deployments to Vercel are being made by coding agents, which is insane.”

Guillermo RauchFounder and Chief Executive Officer · Executive, Vercel