#21 - 🚀 AI Coding Tools: Seniors Ship 2.5x More AI Code

New tools & research on how devs use AI coding tools

Author

Ian L.
September 02, 2025

Hey readers! 👋 This week we're diving into some fascinating research on how senior vs. junior developers use AI coding tools, plus exciting new releases from xAI, Cline, and Cognition. It seems the AI coding landscape is evolving rapidly with specialized models designed for agentic workflows. Let's explore what's new!

This Week's Highlights 🔍

AI Adoption Research

Senior developers are all in on vibe coding, but junior staff lack the experience to spot critical flaws — A Fastly study reveals senior developers use AI coding tools 2.5 times more than juniors, with greater confidence in spotting and fixing AI-generated flaws. – ITPro

This finding is particularly interesting because it contradicts the assumption that younger developers would be quicker to adopt AI tools. The experience to recognize when code "looks right" but contains errors makes seniors more confident using AI even for critical code.

Fastly: Senior Devs Ship 2.5x More AI Code Than Juniors — Nearly one-third of senior developers say over half their production code is AI-generated, compared to just 13% of juniors, with seniors approaching AI tools more scientifically. – Darryl K. Taft

The survey also found that 28% of developers spend so much time fixing AI-generated code that it negates most time savings. As one developer put it, "You can't outsource taste to an AI. You need to have good professional sensibilities to know what good looks like."

Microsoft says AI is finally having a 'meaningful impact' on developer productivity — Microsoft researchers report 75% of developers regularly use AI tools, with 90% feeling more productive and 80% saying they "would be sad if they could no longer use it." – ITPro

The study using the SPACE framework found AI is changing team interactions by reducing interruptions for basic questions and fostering deeper strategic discussions about architecture and project planning.

New AI Coding Tools

Grok Code Fast 1: xAI's Latest Model Lands in Cline (Free for a Week) — xAI has launched Grok Code Fast 1, a model built specifically for agentic coding workflows with significantly faster response times. – Cline Blog

The model delivers responses so quickly that it changes how developers work—giving smaller, focused tasks and iterating rapidly instead of crafting massive prompts. With cache hit rates above 90% in typical workflows, subsequent requests feel nearly instantaneous.

Cline v3.26.6: Three Ways to Code for Free — Cline introduces three free AI-powered coding options: ultra-fast cloud-based coding with Grok Code Fast, fully offline local coding, and 2,000 free daily requests via Qwen Code. – Cline Blog

The local coding option is particularly impressive, allowing developers to use AI coding assistance with no internet dependency or API costs—even "on a boat in the middle of the ocean."

Introducing Grok Code Fast 1, a speedy and economical reasoning model — Grok Code Fast 1 is now available for free on GitHub Copilot, Cursor, Cline, Kilo Code, Roo Code, opencode, and Windsurf. – xai

This wide availability across multiple platforms shows how quickly new AI models are being integrated into the developer ecosystem, creating a more competitive landscape for AI coding assistants.

Devin Updates

Cognition | Devin December '24 Product Update (Part 2) — Devin is now generally available with subscriptions starting at $500/month, offering unlimited seats, API access, Slack integration, and IDE extensions. – The Cognition Team

Recent improvements include a 10% increase in speed and cost efficiency, fixes for crashes and stuck states, and enhanced customization options such as session filtering and Slack notifications.

Cognition | Devin February '25 Product Update — Devin is now approximately twice as fast as in October 2024, with new features including batch code edits, proactive feedback on suboptimal prompts, and GitLab support in beta. – Devin

The batch edits feature allows parallel editing of multiple files, significantly improving speed for repetitive refactors. Browser improvements include handling auto-opening tabs and multiple tabs for better workflow.

AI Coding Challenges & Perspectives

Why AI Alone Fails at Large-Scale Code Modernization — AI tools lack deterministic understanding of codebases, build systems, and dependencies, which is critical for safe and scalable modernization. – Olga Kundzich

The author advocates for combining AI with deterministic automation frameworks like OpenRewrite, which use precise, compiler-accurate parsing and rule-based recipes to ensure reliable, repeatable code transformations.

They're lying to you about Vibe Coding — Sara Dietschy explores "vibe coding" by building a Pinterest clone using AI tools, finding significant challenges with databases and authentication. – Sara Dietschy

Despite the hype, she concludes vibe coding platforms aren't yet complete end-to-end solutions for production-ready apps, especially for complex backend needs. "These self-proclaimed vibe coding platforms are not the answer to building a product from end to end. They take you to a certain point, then you have to dive in the deep end."

Will AI Ever Fully Replace Human Coders? — AI coding tools have significantly advanced but still struggle with large codebases, complex logic, and long-term planning required for software development. – IEEE Spectrum

The study emphasizes that AI tools currently lack the ability to collaborate with humans at the nuanced level required for complex coding tasks. As one expert noted, "If it takes longer to explain to the system all the things you want to do and all the details of what you want to do, then all you have is just programming by another name."

Developer Experience & Productivity

Jellyfish Tracks Which AI Dev Tools Actually Pay Off — Jellyfish has launched new features for its AI Impact platform to provide engineering leaders with data-driven insights into the effectiveness and ROI of various AI development tools. – Darryl K. Taft

This vendor-neutral approach helps companies move beyond guesswork to understand which AI tools truly boost productivity and delivery outcomes in software development, addressing the challenge that 90% of engineering teams use AI coding tools but many lack data to optimize their investments.

Harness AI Tackles Software Development's Real Bottleneck — Harness AI addresses the major bottleneck in software development: post-coding processes such as testing, security, deployment, and maintenance. – Darryl K. Taft

"You could spend 35 to 45 hours a week just managing and maintaining a CI/CD pipeline," notes Harness CEO Jyoti Bansal. "Your build failed? That's another hour. Cloud costs spiking? There goes your afternoon." Their platform aims to automate these processes using context-aware AI agents.

Amplifying the Good and the Bad: 10 More AI Coding Lessons — Dieter Randolph reflects on how AI transforms coding from a solo task into a dialogue, requiring developers to manage the pace and interaction. – Dieter Randolph

"The Future Feels More Social Than Solitary: Coding no longer feels lonely. Whether you love or dislike that shift, it's undeniable. The act of creation now involves dialogue, even if one of the partners isn't human."

Quick Bytes

The AI coding landscape continues to evolve rapidly, with tools becoming more specialized and integrated into developer workflows. The research showing senior developers embracing AI more readily than juniors suggests experience remains valuable even as AI capabilities grow. What's your experience with these tools? Hit reply and let us know!

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