JetBrains Report 2025: AI Boosts Developer Productivity by 20%, TypeScript Surges, PHP Remains Stable

The “State of the Developer Ecosystem 2025” report by JetBrains, based on responses from 24,534 developers across 194 countries, indicates a pervasive integration of Artificial Intelligence (AI) tools in software development. An overwhelming 85% of respondents regularly use AI tools, with 62% relying on at least one AI assistant or AI-powered code tool daily. Notably, almost 90% of AI users report clear time savings, and 20% claim to save an entire workday per week, translating to a substantial 20% boost in individual productivity. Despite these gains, skepticism remains, with developers citing fluctuating code quality, lack of contextual knowledge, and concerns about skill atrophy. The report positions AI as a powerful abstraction and tool for enhancing efficiency, particularly with boilerplate code, rather than a replacement for developers, a trend observed historically with other significant technological shifts.

The report also details evolving language landscapes and a redefined understanding of productivity. TypeScript is identified as a rapidly rising and promising technology, valued for its strong typing capabilities derived from Java, combined with the lightweight nature of JavaScript. Java, conversely, is noted for its verbosity and extensive overhead, leading to its decline for new project starts. Meanwhile, JavaScript, PHP, and SQL have reached a mature phase, with little significant growth expected. PHP, in particular, demonstrates remarkable stability, with 89% of its developers using modern PHP 8.x, and 58% expressing no plans to switch languages; Laravel dominates its ecosystem with a 64% share. Beyond technical metrics, over half of developers now prioritize interpersonal factors like communication and clear goals as crucial for team productivity, though 66% feel current metrics don’t realistically represent their performance. Rust and Go are also highlighted as highly promising languages, alongside Python and Kotlin.

Further insights into AI implementation emphasize the critical role of fine-grained control and the separation of concerns principle. Effective AI integration, especially with large language models, requires extensive training and guardrails to prevent errors, hallucinations, and irrelevant tangents. This approach leverages AI for very specific, constrained tasks, enhancing developer efficiency without fully automating complex software processes, effectively making programming languages act as a 4GL facade. The developer job market presents regional disparities, with positive sentiment in Japan contrasting with challenges faced in Canada. Junior developers continue to encounter significant entry barriers, while senior developers grapple with coordination and context switching. Despite these challenges, the passion for coding remains strong across the ecosystem, with more than half of developers continuing to write code in their free time for relaxation.