Tag: software

  • AI Is Accelerating How Fast We Build the Wrong Thing

    AI Is Accelerating How Fast We Build the Wrong Thing

    AI coding assistants have made it trivially easy to ship software faster — and that is precisely the problem. Human developers used to absorb the gaps in a vague spec by asking questions, reading between the lines and quietly steering toward something useful. AI tools do not work that way. They take incomplete requirements at face value and build them literally, which means small ambiguities at the front of the process compound into expensive mistakes at the back. The result is shops moving at AI speed in directions they never meant to go.

    Jeff Keyes, Field CTO at Allstacks and a 30-year veteran of Microsoft, Atlassian and Planview, sat down with Alan Shimel to preview his Flowtopia 2026 talk on a new operating model for product management. His thesis is blunt: the smartest organizations he is working with have flipped the script and stopped treating AI transformation as an engineering problem. The real leverage sits upstream, in how product teams scope work and write requirements before a single line of code — human or machine — gets generated.

    Keyes and Shimel work through why more than 80% of companies still cannot point to meaningful ROI from their AI tooling investments. The pattern Keyes keeps seeing is faster output stacked on top of unclear intent, which produces velocity metrics that look impressive while value realization stalls. He argues requirements quality has quietly become the highest-leverage variable in AI-assisted development, and that PM craft — not prompt craft — is what separates the teams pulling ahead from the ones spinning.

    What that operating model actually looks like in practice is where the preview gets concrete. Keyes lays out how PM teams need to rebuild around clarity, traceability and feedback loops that hold up when an agent, not a junior dev, is doing the implementation. With AI accelerating both the right work and the wrong work in equal measure, the organizations that fix product management first will compound an advantage the rest of the field cannot catch.

  • Survey: Software Quality Continues to Be Sacrificed in the Name of Speed

    Survey: Software Quality Continues to Be Sacrificed in the Name of Speed

    A global survey of 2,750 IT, DevOps leaders and software developers finds nearly half of respondents (45%) admit their organization prioritizes delivery speed over software quality, with 63% acknowledging their organization deploys code without fully testing it. Only 13% of respondents said their organization is focused on improving software quality.

    Conducted by Censuswide on behalf of Tricentis, a provider of an application testing automation platform, more than one-third (34%) of respondents say ongoing maintenance and unresolved technical debt are the largest obstacles to delivering high-quality software. Other issues include poor communication between software development and quality assurance teams (33%) and a disconnect between leadership and development teams (29%).

    The primary reasons cited for not testing code are the need to expedite release cycles (46%) and accidental slips (40%). Just under a quarter (24%) also admitted they are not confident in their test coverage.

    More troubling still, 81% said software quality issues cost their business between $500,000 and $5 million every year, with nearly 40% estimating losses of more than $1 million. Two-thirds (66%) of respondents also conceded their organization is likely to suffer an outage or major disruption in the next year, with nearly a quarter (23%) deeming their organization to be at extreme risk.

    Many respondents noted there is a lack of clear quality metrics provided by the organization (29%), a disconnect between leadership and development teams over what defines quality (28%), and budget constraints (25%). The top five benefits they seek from better software quality include improved team efficiency (17%), stronger customer satisfaction and retention (15%), reduced security and compliance risk (14%), increased revenue (14%), and faster delivery (14%).

    Lee McClendon, chief digital and technology officer for Tricentis, said when it comes to software engineering there continues to be too much emphasis on speed over quality. The irony is that addressing quality issues in the latter stages of a DevOps workflow only serves to slow organizations down further when work needs to be redone, he added.

    There is simply too much focus on metrics that track how fast software is developed versus how well, noted McClendon.

    On the plus side, a total of 80% of respondents said they believe that advances in artificial intelligence (AI) will enable them to improve software quality without adversely impacting the rate at which software is being developed. Nearly 90% also said they can effectively measure the return on investment on generative AI tools and platforms. However, two-thirds (66%) noted it takes investments in software development and delivery at least three years to pay off, with over one-third (34%) anticipating AI technology investments will take even longer.

    The majority (82%) also said they are excited about AI agents taking on repetitive tasks in the software development lifecycle, while 84% believe AI will help teams deliver under increasingly tight deadlines. A full 89% said they trust AI agents to make decisions that impact software delivery. At the same time, bias remains a key concern for 38% of respondents, and the same percentage are wary of over-reliance on AI tools.

    Finally, nearly all respondents expect autonomous testing will be useful for quality assurance (QA) testing, with the biggest impact being improving software performance (28%), overall quality (28%), analyzing test results (25%) and test case maintenance (23%).

    Hopefully, the quality of applications will improve in the age of AI, but the one thing that is certain is that when it comes to achieving that goal there is still a lot of room for improvement.