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Study Finds AI Tools Slow Down Experienced Software Developers in Familiar Codebases

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A new study challenges the common assumption that artificial intelligence always speeds up software development. Conducted by AI research nonprofit METR, the study focused on seasoned developers working with Cursor, a popular AI coding assistant, within open-source projects they knew well. Contrary to their expectations, these experienced developers took 19% longer to complete tasks when using AI compared to working without it.

Before the study, developers predicted AI would speed up their work by about 20-24%, but the actual results showed the opposite. The study’s lead authors, Joel Becker and Nate Rush, expressed surprise at the findings, with Rush originally anticipating a potential twofold productivity increase.

These findings complicate the popular narrative that AI tools dramatically boost the productivity of highly skilled engineers—a claim that has helped fuel heavy investment in AI-powered software development products. While AI is often touted as a way to replace entry-level coding jobs, the METR study reveals that its benefits may not extend to all developers or coding scenarios.

Previous research has shown significant AI-driven productivity gains, with some studies citing up to 56% faster coding speeds or 26% more tasks completed in a given time. However, METR’s work highlights that these improvements might be more relevant to junior developers or those unfamiliar with complex codebases. Experienced developers, intimately aware of the nuances of mature open-source projects, tended to slow down because they spent extra time reviewing and fixing AI suggestions.

Becker noted that while AI-generated code was often on the right track, it frequently required careful correction to meet precise needs. The study authors emphasized that the slowdown was specific to the context of experienced developers working in familiar environments and might not occur in other development settings.

Despite the slower task completion times, most participants, including the study authors, continue to use Cursor, finding that AI makes coding less effortful and more enjoyable—comparable to editing an essay rather than starting from scratch. Becker explained, “Developers have goals other than completing the task as soon as possible. So they’re going with this less effortful route.”

Apple Opens Apple Intelligence to Developers, Keeps AI Rollout Cautious at WWDC

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At its annual Worldwide Developers Conference (WWDC), Apple unveiled a series of incremental artificial intelligence updates, emphasizing practical features while keeping broader ambitions restrained compared to its tech rivals. The company announced that developers will now gain access to Apple Intelligence’s foundational on-device AI model, though cloud-based advanced capabilities remain out of reach.

Apple’s software chief Craig Federighi confirmed that third-party developers can integrate Apple’s on-device large language model (LLM), which operates at around 3 billion parameters. While this allows for enhanced privacy and offline functionality, it also limits the model’s capacity for more complex AI tasks that cloud-based systems can handle. Apple plans to supplement these with integrations from partners like OpenAI, allowing developers to use both Apple’s and OpenAI’s code completion tools directly within Apple’s developer platform, Xcode.

The updates reflect a shift from the sweeping promises made a year ago. Last year, Apple hinted at being a visionary in AI with talk of “AI agents.” This year, the company focused on concrete applications such as live translation during phone calls, call screening, and visual intelligence that helps users find products similar to those viewed online.

Federighi also announced a major design refresh across Apple’s operating systems, introducing a “Liquid Glass” aesthetic with semi-transparent icons and menus inspired by visionOS. Future OS versions will adopt year-based naming, replacing sequential version numbers.

While the AI additions may appear modest, Apple’s back-end infrastructure improvements suggest a longer-term strategy. The company prioritizes privacy-focused, on-device AI processing while allowing users to opt in when data is shared with third parties like OpenAI.

Despite these moves, analysts expressed mixed views. Some highlighted Apple’s cautious but practical approach, while others warned that Apple risks falling behind as competitors like OpenAI and Microsoft rapidly advance in AI development. Apple’s shares dipped 1.2% following the announcements.

In the broader context, OpenAI reported reaching a $10 billion annualized revenue run rate, underscoring the fast-paced evolution of the AI sector that Apple is cautiously navigating.

RevenueCat Raises $50 Million Series C to Expand Subscription Platform Amid AI and Gaming Boom

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RevenueCat, a subscription management platform serving mobile and app-based businesses, has raised $50 million in Series C funding, the company announced Thursday. The round was led by Bain Capital Ventures, with continued backing from Index Ventures, Y Combinator, Volo Ventures, and others.

The San Francisco-based startup enables app developers to manage pricing, subscriptions, and virtual goods across platforms like iOS, Android, and web — a function that’s becoming increasingly vital amid a surge in AI-driven apps and mobile gaming.

Key Highlights

  • Major Clients: Includes OpenAI, which worked with RevenueCat to deploy ChatGPT on mobile after its 2022 launch.

  • AI App Growth: 20% of RevenueCat’s top 20 apps are AI-based, CEO Jacob Eiting told Reuters, as generative AI apps tend to charge premium fees and convert users more effectively.

  • Expansion Plans: The company plans to use the new capital to:

    • Grow its workforce

    • Pursue strategic acquisitions

    • Advance into mobile gaming with features like virtual currency tools

“We eventually hope to be as important in the game market as we are in the app market,” Eiting said.

Strategic Context

RevenueCat is riding a wave of increased app creation thanks to tools like no-code platforms and AI-based development kits, which have fueled demand for streamlined monetization infrastructure. Its technology abstracts complex payment logic and backend infrastructure, allowing developers to focus on product development.

The platform is also expanding capabilities tailored to game developers, a sector known for in-app purchase complexity and a high-spending user base. The company’s new virtual currency feature aims to help developers better manage in-game economies and monetization models.

With this new funding, RevenueCat is positioning itself as the go-to backend for subscription infrastructure, not just for mobile apps, but increasingly for AI and gaming ecosystems — two of the fastest-growing digital markets.