Managing AI coding agents at scale has emerged as a critical challenge for enterprises, even as deploying the agents themselves has become straightforward. JetBrains Central, unveiled recently by the Prague-based developer tools company, targets this gap with a governance and execution platform designed to track return on investment, manage expenses, and orchestrate agent workflows.
The ease of agent deployment masks a deeper problem: visibility into whether these systems deliver measurable business value. Oleg Koverznev, vice president and head of Agentic Platform at JetBrains, warned that the industry faces a familiar pattern. Everyone knows AI is a game changer, he said. But it's very hard to prove that implementing these systems is making a difference in what the return is for the business.
This dynamic mirrors what occurred during cloud migration waves, when initial investment surges gave way to pressure for demonstrable returns, spurring the growth of cost management and observability tools. JetBrains is positioning itself ahead of that curve in the agentic AI space.
Data from JetBrains' AI Pulse survey of 11,000 developers in January 2026 underscores the rapid adoption trajectory. The findings showed that 90% of developers already incorporate AI into their work, and 66% of organizations intend to deploy coding agents within the next year. However, only 13% report using AI across the entire software development lifecycle. Code generation is cheap and no longer a bottleneck, Koverznev noted in the launch announcement. The real challenge is aligning outcomes with intent, along with managing the growing operational and economic complexity of agent-driven work.
The coordination challenge emerging at scale
Beyond ROI measurement, Koverznev highlighted a less-discussed operational risk: loss of visibility when agent deployments proliferate beyond isolated pilot projects. We envision that in the future there will be teams of humans and agent co-workers, he explained. The coordination across agents and humans is a big aspect — and this problem is emerging.
Currently, most organizations run agents in disconnected silos. Gartner forecasts that 40% of enterprise applications will incorporate AI agents by the end of 2026, compared with fewer than 5% today. At that scale, tracking running systems, associated costs, and alignment with intended outcomes becomes a substantial operational burden.
JetBrains Central addresses this through a semantic layer that synthesizes context from source repositories, system architecture, runtime performance, and delivery infrastructure. This approach grants agents system-level awareness rather than relying solely on prompt-based instructions. To get predictable results, we need to give agents the necessary context and the ability to understand the code, Koverznev stated.
The platform integrates Air Team, a collaborative workspace for assigning tasks to agents and monitoring multi-step workflows. Integration points include Slack, Atlassian products, and Linear. The underlying premise holds that agent workflows operating outside existing team systems create redundant coordination layers atop established processes.
Open architecture in a market trending toward vendor lock-in
While most AI platform vendors construct closed, proprietary ecosystems, JetBrains is pursuing the opposite direction. We don't want to own the stack, Koverznev said. We want to provide the system so that customers choose which tools, which agents — and we give them the ability to control it.
The platform supports connections to any integrated development environment or command-line interface, allows customers to supply their own API credentials for OpenAI and competing providers, and enables integration of external agents—including Claude, Codex, and Gemini CLI—through the Agent Communication Protocol without requiring custom development. An on-premises deployment option is in development.
We're standing on the shoulders of giants, Koverznev said. LLMs provide great intelligence — we don't compete with that. We bring it all together into a controllable system.
The strength of a no-lock-in strategy depends on the integrations supporting it, and this sector continues accelerating. JetBrains is applying its own platform internally to validate the approach. We're increasingly leaning into agents and AI-driven workflows, which is creating a need for better visibility into costs and governance, said Hadi Hariri, SVP of Operations. That's why we've started piloting JetBrains Central internally.
Pricing: Fixed governance, variable execution
The pricing model comprises two components: a fixed per-seat subscription covering governance for JetBrains and third-party users, plus consumption-based charges for agent execution. Koverznev illustrated the range of spending possibilities: One developer can spend $100 a month, he said. Another can orchestrate thousands of agents and spend $100,000. It's really possible. The platform's function includes making such expenditures transparent and linking them to business outcomes such as delivery speed and operational costs.
The Early Access Program commences in Q2 2026 with a select group of design partners evaluating JetBrains Central in production agentic workflows. The open-platform strategy carries timing pressure: JetBrains must reach general availability before the market consolidates around a competing governance solution.
Source: The New Stack