Tag: technical debt
AI is Coding Us Into a Corner
Charlie Gero | | AI coding tools, AI dependency, AI hallucinations, AI patching, AI-generated code, application security, code review, code vulnerabilities, developer productivity, developer trust, frontier models, future software maintenance, Human Oversight, junior developers, secure coding, software engineering skills, software security, technical debtAI-powered patching and coding is putting us on a track towards a deepening dependency on future frontier models. The modern tools we use today to fix yesterday’s coding problems are quietly creating ...
AI-Assisted Development Under Deadline: What It Takes to Ship Production Code on an Unfamiliar Stack
Ihor Riazantsev | | AI code risk, AI coding tools, AI-assisted development, AI-generated code, Claude Code, code consistency, code review, devops teams, engineering discipline, feature isolation, manual testing, memory leak debugging, Next.js development, production readiness, production validation, production-ready code, rapid feature delivery, React development, software architecture, software engineering judgment, technical debt, TypeScript development, unfamiliar codebaseHow Claude Code accelerated development on an unfamiliar stack while proving that production-ready AI-generated code still requires human judgment ...
AI Moved the Bottleneck From Writing Code to Understanding and Trusting It
Ted Julian | | AI code generation, AI code security, AI coding tools, AI investment ROI, AI-generated code, application security, automated code review, code quality, code review, codebase visibility, compliance, dependency risk, developer productivity, devsecops, Engineering leadership, engineering metrics, engineering ROI, production incidents, pull request review, SCA, software composition analysis, software delivery, software development productivity, software governance, technical debtAI coding boosts velocity, but without stronger review, governance and codebase visibility, teams risk higher costs, security gaps and production failures. TL;DR ...
AI Is Exposing a Growing Blind Spot in Open Source Security
Aaron Mitchell | | ai, application security, open source, software development, Software Supply Chain, technical debtWith AI, teams across organizations are now building internal applications faster than ever, often pulling in open source libraries and frameworks without much thought about long-term support, lifecycle management, or security ownership ...
Survey Surfaces Multiple Challenges Measuring AI Coding Productivity
Mike Vizard | | AI coding tools, AI slop, code review, developer burnout, developer productivity metrics, Harness survey, software engineering, technical debt, token-maxxingA Harness survey reveals that while 89% of organizations see AI boosting developer productivity, a third of the workday is consumed by untracked AI tasks like fixing bugs, code reviews, and managing ...
Open Source Contribution is About More Than Just Altruism
Laura Czajkowski | | community engagement, Linux Foundation, open source ROI, open source software, private forks, Software Supply Chain, technical debt, upstream contributionPassive consumption of open source software creates hidden costs, including $670,000 annually in internal workarounds; however, organizations that shift to upstream contribution report up to 5x returns through improved talent retention and ...
GitHub’s Spec Kit Puts the Spec Back in Software Development
Tom Smith | | AI coding agents, devops automation, GitHub Copilot, GitHub Spec Kit, software governance, Spec-Driven Development (SDD), technical debt, vibe codingGitHub’s open-source Spec Kit aims to eliminate "vibe coding" by prioritizing durable specifications over vague prompts, providing a structured, agent-agnostic workflow for Copilot, Claude, and Gemini ...
The Velocity Trap: Why Shipping Faster Is Making Systems Worse
Muhammad Yawar Malik | | engineering culture, observability, reliability, Site Reliability Engineering (SRE), software delivery, technical debtThere is a particular flavour of engineering dysfunction that looks, from the outside, like peak performance. Deployments are frequent. Sprint velocity is high. The feature backlog is shrinking. Leadership is pleased. And ...
When Code Becomes Cheap, Engineering Becomes Governance
Alan Shimel | | AI code generation, AI-assisted development, apprenticeship, architecture, code governance, code oversight, democratization of coding, developer productivity, developer supervision, end of programming myth, governance era, industrialized programming, integration risk, maintainability, operations, security risk, software reliability, systems thinking, technical debt, validationAI agents can now generate in minutes what once took teams weeks, but the real shift is not faster coding. It is the collapse of code scarcity. As software production becomes industrialized, ...
Beyond Automation: How Generative AI in DevOps is Redefining Software Delivery
Albert Hilton | | AI risks management, automation, Code Generation, data privacy, DevOps transformation, DevOps workflows, GenAI in DevOps, generative AI, human-in-the-loop, productivity gains, software development, technical debtGenerative AI (GenAI) is revolutionizing DevOps by automating manual tasks, enhancing productivity, and reducing errors. By integrating GenAI, teams can streamline workflows and democratize expert knowledge. However, managing risks such as data ...
Survey: Java Developers Wrestling With Massive Amounts of Technical Debt
Mike Vizard | | AI coding tools, AI functionality, artificial intelligence, cloud computing costs, Common Vulnerability and Exposure (CVE), cost-driven migration, dead code, developer productivity, Java applications, Java developers, Java versions, Java Virtual Machine (JVM), language model integration., large data access, long-term support, migration to OpenJDK, observability, OpenJDK, Oracle pricing concerns, security features, technical debt, vulnerabilitiesA global survey of 2,039 Java developers published today finds 63% reporting that dead and unused code adversely affects their team’s productivity, with 22% describing the impact of that technical debt as ...
Beyond the Prompt: A Quality-First Framework for AI-Assisted Engineering
Parthiban Rajasekaran | | agile development, AI-assisted development, Change Failure Rate, Code Review Practices, continuous improvement, Delivery Systems, DevOps practices, engineering teams, Fast Delivery, governance, incident management, kubernetes, mean time to restore, observability, Resilient Systems, Risk-Based Tiering, software quality, technical debtDiscover strategies for managing AI-generated technical debt and maintaining quality in software delivery as engineering teams accelerate their development processes ...
