'AI coding tools are now the default': Top engineering teams double their output as nearly two-thirds of code production shifts to AI-Generation and could reach 90% within a year

Date:
Thu, 26 Mar 2026 23:45:00 +0000

Description:
AI tools are now standard in software engineering, doubling output for top teams while autonomous agents take on routine coding.

FULL STORY ======================================================================Copy link Facebook X Whatsapp Reddit Pinterest Flipboard Threads Email Share this article 0 Join the conversation Follow us Add us as a preferred source on Google Newsletter Tech Radar Pro Are you a pro? Subscribe to our newsletter Sign up to the TechRadar Pro newsletter to get all the top news, opinion, features and guidance your business needs to succeed! Become a Member in Seconds Unlock instant access to exclusive member features. Contact me with news and offers from other Future brands Receive email from us on behalf of our trusted partners or sponsors By submitting your information you agree to the Terms & Conditions and Privacy Policy and are aged 16 or over. You are
now subscribed Your newsletter sign-up was successful Join the club Get full access to premium articles, exclusive features and a growing list of member rewards. Explore An account already exists for this email address, please log in. Subscribe to our newsletter Over half of engineering teams now consistently use AI coding tools Top adopters report double pull request throughput compared with low adopters Autonomous agents now handle an increasing share of routine coding tasks The integration of AI tools in software engineering has shifted from experimental to operational, with more than half of engineering teams now relying on AI consistently, new research has claimed.

A report from Jellyfish claims nearly two-thirds (64%) of companies generate
a majority of their code with AI assistance, showing a clear rise in adoption across the industry. If current trends continue without interruption, this proportion could reach 90% within a single year. Article continues below You may like What vibe coding means for API platforms and the future of DevRel Even the most advanced AI models fail more often than you think on structured outputs Devs don't trust AI code - but many say they still don't check it anyways AI adoption drives productivity gains The incentive for this shift appears linked to measurable productivity gains rather than improvements in code quality.

AI coding tools are now the default option for engineering teams, and the productivity gains are real, said Nicholas Arcolano, Ph.D., head of research at Jellyfish.

This trajectory suggests that AI is no longer an auxiliary tool but rather
the primary engine of software development for organizations that choose to adopt it aggressively.

While AI does not automatically improve code maintainability, the volume
gains alone have made it the standard tool for many teams. Are you a pro? Subscribe to our newsletter Sign up to the TechRadar Pro newsletter to get
all the top news, opinion, features and guidance your business needs to succeed! Contact me with news and offers from other Future brands Receive email from us on behalf of our trusted partners or sponsors By submitting
your information you agree to the Terms & Conditions and Privacy Policy and are aged 16 or over.

Top-performing companies in AI-driven sectors have experienced significant increases in output, and firms which adopt AI most aggressively report double the pull request throughput compared with low adopters over three months.

In practical terms, these teams are producing and shipping code at a pace
that leaves competitors behind.

A rapidly growing trend within this adoption is the use of autonomous agents, which generate pull requests entirely without human intervention - although these agents currently make up a small portion of overall code production, their presence is expanding quickly. What to read next Anthropic claims half of its agent tool calls are to do with software engineering - so are developers letting AI take over? 'If organizations focus only on short-term efficiency... they risk hollowing out the next generation of technical leaders': Microsoft execs say senior workers must mentor juniors to fix AI mistakes Cursor claims more than 30,000 Nvidia engineers commit 3x more code and make coding 'a lot more fun than it used to be', but is it too good to be true?

In the 90th percentile of companies, contributions from autonomous agents
rose from 10% of pull requests in January 2026 to 14% in February.

This indicates that AI-driven automation is not only supplementing human developers but is gradually taking on a larger share of routine coding tasks.

Despite these productivity gains, AI adoption does not guarantee fewer errors or improved code quality, therefore the focus for organizations has shifted toward monitoring operational output rather than assuming that faster production equates to better code.

For top engineering teams, AIs value lies in its ability to accelerate development cycles and increase throughput.

As AI coding tools become the default in engineering workflows, top teams are completing tasks faster, and autonomous agents are taking on an increasing share of pull requests.

This shift affects how engineering teams plan, execute, and scale their work, and no team wants to be left behind for not following the trend.

For leaders, the focus is on integrating AI strategically to sustain high throughput, streamline operations, and maintain a competitive edge. Follow TechRadar on Google News and add us as a preferred source to get our expert news, reviews, and opinion in your feeds. Make sure to click the Follow button!

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