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Czech software development company JetBrains may be an anomaly in the world of rapidly scaling AI investment. A private company founded over two decades ago with a profitable software subscription revenue model and consistent growth, the firm is one of a minority afforded the leeway to be a little more high-minded about its product growth.
The top-down ethos behind the company’s growth is one of ethical and open-source software development, which has helped shape a brand that is beloved by developers around the world. And while the company has not become a household name like its competitors Microsoft and GitHub, it nevertheless wields an outsize influence in the workflows of millions of developers globally.
Founded in 2000, in Prague, by three Russian software developers Sergey Dmitriev, Valentin Kipyatkov and Eugene Belyaev, the company has since had some leadership turnover, the latest in February 2024 when Kirill Skrygan became CEO.
Skrygan spent the 14 years prior at JetBrains, during which time he founded Rider and GameDev IDE, created Code With Me to help with collaboration during the pandemic, as well as led the company’s IDE business. On brand with its developer-first philosophy, it seems fitting to have someone like Skrygan at the helm—a software developer at heart.
The company’s tools are used by 15 million developers globally, as well as 88 Fortune 100 businesses, says Skrygan. And while many companies involved in building AI have perhaps prioritised moving fast over model quality, there is far more caution within enterprise environments, and its impact on enterprise tasks is still limited on the whole, notes Skrygan.
“We talk to a lot of CTOs, tech leads and CIOs, and they are cautious,” he says. “They may say that they can generate three times more code with AI, but that they end up spending ten times longer to review pull requests, and the customer satisfaction is lower.
“Our philosophy is not just to build AI for the sake of building AI; we are not hype chasers. We have always been a private company, so we really depend on bringing true value to our developers,” says Skrygan.

Remaining under private ownership “really matters” to Skrygan because it has created a company focused on sustainable growth year after year rather than “hype and fake numbers to gain more funding in the next round”. Sustainable growth ensures that the critical balance between the speed and quality of generating AI tools has never been compromised.
“We’re not Luddites,” he adds. “But AI should be controllable and transparent, and we have the leverage to make it happen, because we have 25 years of expertise and technological assets, of all the programming languages, frameworks, and a very strong brand.”
The company launched its AI coding agent Junie in January. Based on the same premise of quality over speed, the company claims that while fast agents will reduce the time taken to complete a given task, a smart agent like Junie will “tangibly enhance the end-to-end development experience, minimising errors, bugs, and context switching, and helping you achieve high-quality code”.
ROI on enterprise AI – how to get there?
As AI hype gives way to questions about return on investment (ROI) on AI investments, Skrygan claims that Junie’s pricing model is the most transparent in the business. He encourages enterprise IT leaders to consider the whole software development arc, from idea to product, when evaluating ROI. “It’s about prototyping, and about communication,” he says. “Yes, it’s about coding too. But then you have to deploy and maintain, check for security vulnerabilities, for example. So you have to measure the efficiency of the whole arc, not just coding.”
For example, CTOs tell Skrygan that despite AI enabling the coding part of the arc to take less time, it can mean that significantly more time is then spent on other parts. But how does an IT leader evaluate this?
“It depends on a business,” says Skrygan. Speaking frankly, he admits that AI has not made any massive improvements on big enterprise projects, whereas “if you want to prototype something very fast, it’s a game changer.” Something that would take five developers and half a year to just battle test a hypothesis can now take just one or two developers a fraction of the time.
Skrygan’s advice to CTOs is to stay updated with AI tools and focus on the entire software development arc to avoid technical debt and, in this way, become much more efficient in every stage of the software development pipeline. Approaching the software development pipeline as a life cycle can create more visibility on what is working well in terms of tools, frameworks and agents. Then each part of the development stack can be tailored to its own specific needs.
Secondly, tech leaders need a broad vision of the tasks at hand. AI disruption is happening at an organisational level, not just an individual level. “It’s not just about one person being a little bit more productive, but about the whole organisation, which will create software in a completely different manner,” Skrygan explains.
AI preserving the dignity of the engineer
Skrygan is firmly in the cohort of those anticipating that AI will augment roles rather than replace them. “I honestly do not believe that AI will cut out computer science jobs. Knowing computer science, knowing algorithms, is actually a fundamental bottleneck for macroeconomics right now,” he says, adding that AI could actually be the solution to filling widening skills gaps.
Eventually, every organisation’s cloud environment will include proactive agents, rather than the reactive agents currently deployed. What Skrygan describes as all the “boring boilerplate tasks” will eventually be assigned to proactive agents, albeit with a human in the loop to assess and guide. He imagines that the efficiencies created would increase ROI by 300-400%.
“I strongly believe – and this is our mission – that this doesn’t make employees into factory tools within an organisation, but instead it preserves the dignity of being an engineer,” says Skrygan. “Offloading boring boilerplate code to proactive agents means engineers can focus on… higher-level things.”
Alongside augmented engineering, there will be the evolution of a new workforce segment of creators, according to Skrygan. When pressed to define this skillset, he describes them as “people who are capable of solving much higher-level abstraction tasks, much closer to product design, product assessment, and not necessarily about coding.”
“With no code solutions, creators can produce software, and this will be really valuable,” says Skrygan. He sees this new type of creator seamlessly interacting with computer science without even being aware that they are doing so.
In more philosophical terms, Skrygan says the JetBrains leadership team are all “human believers”. While AI technology will become increasingly powerful, it should always reside within “human hands”.
This article was originally published on Verdict.