A blog post argues that generative AI threatens product managers as much as developers, since AI-assisted coding makes it cheap for anyone, including developers, to prompt and build features themselves. The author contends that as code becomes cheap, developers gain time to build product intuition, eroding the traditional split between 'tech' and 'product' roles. The piece compares the effect to Instagram's impact on professional photography, where most mid-tier practitioners lost their edge while top talent became more valuable.
lucaskostka.com
· 2026-10-30
Industry executives from firms including Queue Associates, Envision IT and Think AI argue that software companies must link AI tools to specific operational problems and measurable results to turn customer interest into sustained revenue. The piece cites Gartner's forecast of $1.468 trillion in global software spending for 2026, a 15.5% year-over-year rise, and IDC's projection of roughly $497 billion in AI infrastructure spending in 2026, growing about 56% annually and surpassing $1 trillion by 2029.
entrepreneur.com
· 2026-10-30
A developer essay sketches a hypothetical 2031 workday in which AI agents complete most coding tasks overnight, opening pull requests with tests and recorded demos, while leaving ambiguous business decisions for a human to resolve. The piece draws a parallel to earlier predictions that compilers would make programming obsolete, arguing that each layer of automation shifts rather than removes human judgment. The author frames this as a plausible near-future extension of present-day agentic coding tools rather than a confirmed roadmap.
hrih.si
· 2026-10-21
A Dark Reading roundtable discussion examined how AI tools are adding new security complexities to the software development lifecycle. Participants pointed to improved collaboration, stronger identity visibility, and lower testing costs as practical steps CISOs can take to manage these risks before expanding AI use in development.
darkreading.com
· 2026-10-20
A developer says they received a permanent ban from the r/java subreddit after posting a Swing WebView component they built using AI tools. They say the ban stemmed from rule #9, a newly added policy prohibiting sharing any software developed with AI assistance, which they hadn't noticed before posting.
sjhannah.com
· 2026-10-20
In a Sep 25, 2026 post titled 'Code is clay now,' writer Alberto Denia argues that agentic coding tools have drastically lowered the cost of changing code, making it behave more like clay than stone. He describes this as enabling a 'modeling' approach to building software, where developers sketch rough versions and iteratively reshape them rather than planning meticulously upfront.
albertodenia.com
· 2026-10-19
Describing what you want and accepting the code that comes back is genuinely productive for some work and quietly expensive for other work. The dividing line is fairly predictable.
gokawiil.com
· 2026-10-19
In an essay, Linear's team describes how the company has built its product by prioritizing founder and team intuition developed through customer conversations and experience, rather than relying mainly on data-driven processes. The piece argues that two teams with the same technology and customers can produce very different products because of differing perspectives and values.
karrisaarinen.com
· 2026-10-18
A new essay on 'Recreational Programming' argues that developers should maintain personal coding projects purely for enjoyment, separate from their professional work. The piece quotes the idea that the aim isn't to emulate any particular programmer's career, but to preserve the sense of curiosity that first drew people to coding.
cphiri.dev
· 2026-10-13
A new analysis argues that although AI tools now let developers write, refactor, and document code far faster than two years ago, overall software shipping speed has barely improved. It attributes this gap to software development lifecycles still built around sprints, manual quality gates, and review handoffs designed for an era when writing code itself was the slowest step.
fastcompany.com
· 2026-10-13
A study covering more than 700 software companies found that AI coding agents raised lines of code by 30 percent, commits by 20 percent, and pull requests by 23 percent, but did not meaningfully increase the rate at which firms resolved tracked features or issues in tools like Jira. Researchers attribute the gap to code review, which took 49 percent longer on average after AI tools were adopted, with more revisions required and more reviewer comments per pull request.
tech.slashdot.org
· 2026-10-12
Harvard researchers Fiona Chen and James Stratton analyzed Jellyfish analytics covering 300 million work events across more than 700 software firms and 700,000 employees from 2021 to March 2026. They found that while AI coding assistants and agents increase the volume of code generated, firms show little evidence of increased software output or reduced employment, because human code review becomes a bottleneck, with longer reviews, more revision requests, and more reviewer comments.
arstechnica.com
· 2026-10-09
GoKawiil