Part of the SD Times 100 2026 series. See the full SD Times 100 2026 list for every category and honoree. For most of software development’s history, engineering leaders have had remarkably poor visibility into the thing they’re actually responsible for managing: how engineering work actually flows, where it gets stuck, and whether investments in …
Part of the SD Times 100 2026 series. See the full SD Times 100 2026 list for every category and honoree. Software testing has always faced the same basic tension: thoroughness takes time, and time is exactly what fast-moving engineering organizations don’t want to spend. That tension has intensified sharply in 2026. AI-assisted development means …
Part of the SD Times 100 2026 series. See the full SD Times 100 2026 list for every category and honoree. Application security has spent years maturing around a relatively stable assumption: a human wrote the code, a human can be trained to write it more securely, and tools exist to catch what humans miss. …
Part of the SD Times 100 2026 series. See the full SD Times 100 2026 list for every category and honoree. Platform engineering emerged as a discipline because giving every developer raw access to cloud infrastructure and expecting good outcomes simply doesn’t scale past a certain organization size. The companies recognized in this year’s Platform …
Part of the SD Times 100 2026 series. See the full SD Times 100 2026 list for every category and honoree. Operations and observability have always been about answering one question fast: what’s happening in our systems right now, and what do we do about it? What’s changed in 2026 is who’s doing the answering. …
Part of the SD Times 100 2026 series. See the full SD Times 100 2026 list for every category and honoree. Every conversation about AI strategy eventually arrives at the same uncomfortable truth: a model is only as good as the data it can reach. Engineering leaders who spent the last few years focused on …
AI is being dropped into nearly every corner of modern work, but most businesses still cannot say with much honesty what it is truly contributing. They can say it is speeding things up. They can say it is integrated. They can say their teams are “using AI,” but that is not the same as understanding its value. In …
Part of the SD Times 100 2026 series. See the full SD Times 100 2026 list for every category and honoree. For two decades, “integration” meant connecting Application A to Application B and calling it done. In 2026, that definition no longer holds. Every enterprise now runs a web of SaaS platforms, internal microservices, data …
Part of the SD Times 100 2026 series. See the full SD Times 100 2026 list for every category and honoree. No category in this year’s SD Times 100 generated more debate internally than this one, and not because the companies in it are unworthy. It’s because “AI coding tool” stopped being a useful description …
In the last year, we’ve seen AI cause a seismic shift in software development and delivery. Artificial intelligence is generating code faster than ever seen Meanwhile, AI also has caused a seismic shift in the SD Times 100. For 2026, we’ve ejected a few legacy categories that seem less important in the era of AI, …
Organizations have spent years searching for ways to improve efficiency through automation. The usual strategy is familiar: identify repetitive tasks, automate them, measure the time savings, and expand from there. On paper, it sounds logical. In practice, many initiatives never move beyond isolated successes. The problem is not that the technology falls short. More often, …
Most enterprises adopted generative AI by inserting it into the easiest possible place: coding itself. That approach makes sense operationally. AI-assisted coding tools integrate neatly into existing workflows. Developers can immediately generate scaffolding, autocomplete repetitive logic, summarize code, or accelerate test creation without requiring major organizational change. But writing code was never the dominant constraint …
AI is no longer an experiment. It’s become central to enterprise technology, according to the Reveal 2026 Top Software Development Challenges Survey from Infragistics. AI’s promised acceleration and ambitions for productivity and performance gains after several transformative years of innovation, is now colliding with economic reality and talent shortages. AI adoption isn’t slowing down, but …
For about six years, I’ve supported enterprise customers at a major global technology company, working mostly in cloud support and messaging systems, i.e. the information backbone that lets large applications talk to each other without falling over. Across more than 1,200 customer engagements, I’ve sat with government agencies, critical-infrastructure operators, and Fortune 500 companies on …
AI adoption in software engineering is accelerating, but the real story lies in how top-performing teams are turning it into measurable impact. While many organisations remain stuck in experimentation, leading teams are successfully translating AI-driven productivity gains into improved delivery performance. The difference isn’t the tools, it’s how they’re applied within the system. …
Most QA teams are stuck measuring how many tests they ran. But in a tightened economy, leadership wants to know one thing: What is the ROI? On May 27th, join SD Times for Supercast 2: The ROI of Intelligent Quality. We’re shifting the conversation from simple test automation to real business outcomes. …
Engineering leaders are under more pressure than ever. AI coding tools are being rolled out across teams at breakneck speed. Executives want to see measurable impact. DORA metrics and throughput numbers tell part of the story, but they can’t tell you why deployment frequency dipped last quarter, or whether your developers actually trust the AI-generated …
Building Context Aware Systems Developers Can Rely On AI is rapidly becoming embedded in the software development lifecycle. Yet many organizations are discovering a hard truth: intelligence without context is unreliable. Models generate plausible output, but they lack awareness of system architecture, internal policies, API contracts, ownership structures, and downstream impact. In enterprise environments, that …
Join the premier event series to uncover the latest in AI in Test trends related to MCP, Agents, and AI driven automation. Speakers will present solutions you to learn how to deliver value for your organizations. …
Your engineering team is using AI coding tools, but when the CEO, CFO, or board asks, “What’s the actual ROI?”, you’re stuck between “It feels faster” and “I can’t actually prove it.” License counts are useless, and velocity metrics can’t isolate the AI variable. Join GitKraken’s VP of Engineering, Stasia Zamyshlyaeva, as she shares her …
AI adoption in software engineering is accelerating, but the real story lies in how top-performing teams are turning it into measurable impact. While many organisations remain stuck in experimentation, leading teams are successfully translating AI-driven productivity gains into improved delivery performance. The difference isn’t the tools, it’s how they’re applied within the system. …
Most QA teams are stuck measuring how many tests they ran. But in a tightened economy, leadership wants to know one thing: What is the ROI? On May 27th, join SD Times for Supercast 2: The ROI of Intelligent Quality. We’re shifting the conversation from simple test automation to real business outcomes. …
Engineering leaders are under more pressure than ever. AI coding tools are being rolled out across teams at breakneck speed. Executives want to see measurable impact. DORA metrics and throughput numbers tell part of the story, but they can’t tell you why deployment frequency dipped last quarter, or whether your developers actually trust the AI-generated …
Building Context Aware Systems Developers Can Rely On AI is rapidly becoming embedded in the software development lifecycle. Yet many organizations are discovering a hard truth: intelligence without context is unreliable. Models generate plausible output, but they lack awareness of system architecture, internal policies, API contracts, ownership structures, and downstream impact. In enterprise environments, that …
Join the premier event series to uncover the latest in AI in Test trends related to MCP, Agents, and AI driven automation. Speakers will present solutions you to learn how to deliver value for your organizations. …
Your engineering team is using AI coding tools, but when the CEO, CFO, or board asks, “What’s the actual ROI?”, you’re stuck between “It feels faster” and “I can’t actually prove it.” License counts are useless, and velocity metrics can’t isolate the AI variable. Join GitKraken’s VP of Engineering, Stasia Zamyshlyaeva, as she shares her …
