Kodik’s AI Editor Is Already Winning Recognition in the Startup Market

Promyshlennost Rossii spoke with Kodik founder Yury Golovko about the platform’s capabilities, its impact on software-development workflows, and the potential risks for professionals who choose to use it.

Second Programmer on the Screen

– You describe Kodik as a “second programmer.” What does that mean for the average person?

– Imagine programmers always have a teammate sitting right beside them – someone who can instantly read through an entire project, remembers how everything works, and can suggest the best way to build a new feature. Now imagine that teammate living directly inside the code editor. It can suggest code, create new files, help fix bugs, and even write documentation. For a company, that means work gets done noticeably faster, and developers spend far less time stuck on routine tasks.

– So computers are writing software on their own now?

– Not exactly. It is closer to working with a very smart assistant. The human still defines the task, makes the decisions, and remains responsible for the final result. The AI helps create a first draft, points out potential mistakes, and suggests multiple ways to solve a problem. A good programmer does not become redundant because of that – they become faster and more effective.

How AI Shortens Development Cycles

– Can development timelines really be reduced, or is that just good marketing?

– Yes, and we are already seeing it in real-world projects. Routine tasks that used to take a team weeks can now often be completed in just a few days. AI helps not only with writing code itself, but also with configuring environments, creating tests, and updating documentation. As a result, companies can release updates more frequently and validate new ideas in practice much faster.

– Is that connected to the way AI systems themselves are trained?

– Absolutely. In the past, every project required a lengthy training process: collecting large volumes of data, teaching the system from scratch, and waiting months for results. Today, many models arrive pre-trained on vast amounts of information. We adapt them to a specific project or company, and they begin delivering value fairly quickly. For businesses, that means a much shorter path from an idea to a working prototype.

What Programmers Should Learn in the New Reality

– If smart assistants can do so much of the work, what should young developers focus on learning now?

– The priority is no longer memorizing commands and syntax. It is understanding how systems work as a whole and what business problems they are meant to solve. The more valuable skills are critical thinking, solution design, asking the right questions, and validating what AI proposes. A new competency is emerging: not simply writing code, but effectively managing an intelligent assistant while remaining accountable for the final outcome.

– Is there a risk that the next generation will stop understanding what is happening under the hood?

– That risk exists if people start treating AI like a magic wand. But the market is already showing that the most valued professionals are those who can use new tools while still understanding the fundamentals. It is similar to a calculator: it speeds up calculations, but if you do not understand the math behind them, you will not notice when the answer makes no sense.

The Future of the Job Market: Who Gets Replaced and Who Gets Amplified

– Still, the big question remains: is AI taking jobs away from programmers?

– What it primarily takes away is repetitive, routine work. Tasks that once required several people manually handling standard workflows can now be completed by a smaller team equipped with intelligent tools. At the same time, demand is growing for people who can design solutions, understand business needs, and take responsibility for the quality and security of complex systems.

– What happens to newcomers who are just entering the profession?

– It will become harder to build a career simply by producing large volumes of routine code – that is exactly the kind of work AI excels at. On the bright side, we are likely to see more internship and training programs that teach young professionals how to work alongside these tools from the very beginning. Those who adapt quickly to the new approaches will remain in demand. What definitely will not work is staying at the level of an autocomplete operator.

How This Affects Industry and Everyday Life

– How does all of this connect to ordinary people and industries such as energy or manufacturing?

– In complex industries, the cost of mistakes is extremely high. It can mean risks to human safety, costly equipment downtime, or serious environmental damage. In those environments, AI is not about replacing engineers. It is about reducing the number of errors, identifying problems faster, and testing ideas before they are deployed in the real world. In the end, both companies and consumers benefit: systems become more reliable, accidents become less frequent, and decisions can be made faster.

– If you look five years ahead, how would you describe Kodik’s goal in simple terms?

– We want working with AI to become as natural for programmers as working with a traditional code editor is today. We want companies to stop viewing it as an experiment and start using it every day – to accelerate development, reduce risks, and free people from routine work so they can focus on more interesting and meaningful challenges.

Meanwhile, reports have emerged that investment firm UKM Group plans to acquire a 20% stake in Russian IT startup ArkhiTekh AI, the company behind Kodik, in a deal valued at $15 million. For ArkhiTekh AI, bringing in an investor would mark the next stage of scaling the business and expanding the Kodik ecosystem.