JetBrains wants to solve the disconnect between developers having access to AI coding tools and knowing how to use them effectively.
Generative models are now commonplace, but integrating autonomous agents into established workflows is a far messier reality. JetBrains, partnering with Nebius, is attempting to close this gap with a new educational push designed to embed AI expertise directly into the developer’s daily routine.
Technical leadership faces a governance hurdle rather than an access problem. JetBrains, drawing on its 25 years of tooling experience, argues that AI needs to stop being a novelty and become standard practice.
To support this transition, the vendor released ‘AI-Assisted Programming’, a 10-part series spanning roughly 20 hours of self-paced material. The syllabus avoids simple code generation and instead focuses on where AI fits into the broader machinery of development: refactoring, debugging, DevOps, and automation.
It isn’t just for junior engineers building their first stack. JetBrains’ AI content aims to help senior developers future-proof their coding workflows and gives managers the context needed to introduce these technologies safely.
Two primary courses anchor the programme, illustrating the difference between using AI as a distinct coding tool and deploying it as a collaborator.
‘Coding With Junie’ deals with immediate execution. Participants install the Junie agent to build projects from scratch, offering a sandbox to watch the system generate and run code step-by-step.
“Effective prompting” is a core component here. Developers learn to structure requests for better output and apply the agent to labour-heavy tasks like debugging and test automation. The goal is simple: keep the human in control while stripping away repetitive manual effort.
One tangible exercise involves constructing a web application that analyses food images via Nebius vision models. This highlights how context improves accuracy; a critical lesson for enterprises feeding internal data into LLMs.
Moving beyond using AI coding tools for execution, with the ‘AI Agents as Your Team’ course JetBrains tackles the architectural and managerial headaches of agentic workflows. Distinguishing a standard LLM call from an autonomous agent is vital for risk management. This module lifts the bonnet on LLM-powered agents, detailing how they process decisions internally.
Productivity playbooks are included, but the syllabus balances these with a necessary focus on risk. It forces teams to confront challenges inherent to generative models, such as bias, hallucination, and poor observability. Identifying these pitfalls early allows team leads to navigate the complexities of integrating agents into modern stacks.
Partnering with Nebius allows JetBrains to ground complex infrastructure concepts in reality. With 25 hands-on tasks and a capstone project, the programme ensures learners aren’t just absorbing theory but applying it to realistic scenarios.
For the enterprise, this resource acts as a template for internal upskilling. Success rarely comes from buying the tools alone; it requires training staff to understand the mechanisms, limitations, and proper governance of the agents they employ.
Leaders should assess their development team’s current proficiency with agentic workflows. Encouraging participation in structured programmes like this one from JetBrains can help standardise AI usage, ensuring developers use these AI coding tools with architectural awareness rather than just blind reliance.
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