Tag: AI coding tools
Developer Productivity in the Vibe Coding Era: Is AI Really Moving the Needle?
Hadi Chami | | AI coding tools, AI in software development, code quality, developer productivity, vibe codingLet me be clear. I do not like the term “vibe coding.” The label is sloppy and the concept it pushes is even sloppier. It lumps together two very different practices and ...
Endor Labs Adds AI SAST Tool to Discover Vulnerabilities in Code
Mike Vizard | | agentic AI, AI code analysis, AI coding tools, application security, broken access control, code scanning, code security, developer security tools, devsecops, false positives reduction, LLM code vulnerabilities, multimodal static analysis, OWASP Top 10, secure design, Software Supply Chain Security, Static Application Security TestingEndor Labs launches an agentic AI-powered SAST tool that drastically reduces false positives, identifies deeper code flaws and helps DevSecOps teams secure AI-generated code across 40+ languages ...
JFrog Adds Ability to Track Usage of AI Coding Tools
Mike Vizard | | AI API management, AI code auditing, AI coding tools, AI compliance tracking, AI Governance, AI in DevOps, AI model inventory, AI risk mitigation, AI-generated code, application security, code risk detection, devsecops, Large Language Models, LLM security, MLOps, SCA, secure coding practices, Shadow AI detection, software composition analysis, software provenance, Software Supply Chain Security, software vulnerabilities, source code scanningJFrog introduces AI-Generated Code Detection and Shadow AI Detection tools to identify AI-created code, track model usage, and enhance DevSecOps governance across software supply chains ...
MIT Researchers Propose a New Way to Build Software That Actually Makes Sense
Tom Smith | | AI coding tools, AI-assisted development, clean code architecture, code maintainability, code visibility, concept catalogs, devops automation, DevOps reliability, Large Language Models, LLM software development, modular software design, software engineering innovation, software transparency, system synchronizationMIT researchers propose a new framework to make software clearer and safer by organizing code into “concepts” and “synchronizations” for better visibility ...
Visual Studio Copilot Gets Planning Mode for Complex Tasks
Tom Smith | | agentic development, AI coding tools, AI for developers, AI-assisted coding, Claude Sonnet 4, Copilot AI, Copilot Planning, Copilot planning benchmark, Copilot planning feature, Copilot preview, DevOps AI tools, GPT-5 Copilot, Intent-Driven Development, Microsoft Copilot, Microsoft developer tools, planning-driven development, software development automation, SWE-bench results, Visual Studio 2022, Visual Studio CopilotMicrosoft launches the Planning feature for Visual Studio Copilot, now in public preview for Visual Studio 2022 17.14. Planning gives developers a structured way to manage multistep coding tasks, improving transparency, performance, ...
How Software Engineers and Students Use AI to Move Faster than Ever (Without Breaking Things)
Vivek Vaidya | | agentic AI, AI adoption, AI and students, AI coding tools, AI collaboration, AI engineers, AI evolution, AI in education, AI in software development, AI in universities, AI innovation, AI revolution, AI skills, AI skills gap, AI startups, AI Tools for Developers, AI transformation, AI workforce adaptation, AI-native companies, AI-native design, AI-native learning, AI-powered development, AI/ML, artificial intelligence, augmented development, augmented intelligence, Cursor, developer productivity, digital transformation, Enterprise AI, future of work, human-AI collaboration, LLMs, machine learning, super{set}, VC investment in AIWe’re living through the AI revolution — or more accurately, the age of augmented intelligence. From agentic AI tools transforming software development to AI-native education shaping the next generation, super{set} explores how ...
CodeRabbit Adds CLI Support to Code Review Platform Based on AI
Mike Vizard | | AI code review, AI coding tools, AI in DevOps, AI trust layer, CLI support, code dependencies, code graph analysis, custom pre-merge checks, developer productivity, DevOps workflows, Git repositories, MCP client, Model Context Protocol, open source code review, secure code review, software quality, unit test generationCodeRabbit expands its AI-powered code review platform with CLI support, auto unit test generation, custom pre-merge checks, and an MCP client. Backed by $60M in new funding, CodeRabbit helps developers catch routine ...
Empromptu Unveils Vibecoding Platform for Building Enterprise-Class Apps
Mike Vizard | | AI app scalability, AI application development, AI coding platform, AI coding tools, AI developer workflows, AI DevOps, AI output controls, AI response optimization, AI vs low-code platforms, enterprise AI applications, enterprise software development, explainable AI, LLMOps, RAG, retrieval-augmented generation, SOC-2 compliant AI, vibecodingEmpromptu has launched its AI coding platform for building enterprise-class applications, featuring RAG, LLMOps, explainability, and SOC-2 compliance. Designed for scalability, accuracy, and predictable pricing, it aims to outperform vibecoding tools and ...
Can Vibe Coding Work on an Enterprise Level?
Armelle Dawson | | AI coding tools, AI productivity tools, AI-generated code, enterprise AI coding, enterprise AI governance, low-code AI apps, slopsquatting risks, vibe coding, vibe coding risks, vibe coding securityVibe coding promises AI-generated apps in seconds, but is it enterprise-ready? Explore risks, governance needs, and productivity potential ...
Qwiet AI Extends Microsoft Support in Platform for Fixing Vulnerabilities
Mike Vizard | | AI agents, AI coding tools, application security, AutoFix, Azure Boards, Azure DevOps, devsecops, github, SARIF, SAST, software security, Swift, vulnerability remediationQwiet AI extends its AI-driven application security platform with deeper Microsoft DevOps integrations, enhanced automation, and expanded AutoFix capabilities to proactively remediate code vulnerabilities ...
Context Engineering is the Key to Unlocking AI Agents in DevOps
Harshil Shah | | AI agents, AI coding tools, AI developer tools, AI IDEs, AI in DevOps, AI software development, AI workflows, AI-Driven DevOps, AI-powered development, context engineering, context provisioning, devops automation, intelligent agents, MCP protocol, SDLC AIAI agents can code, test, and deploy—but only with the right context. Learn how context engineering unlocks DevOps-ready AI for the full SDLC ...
Sonar Surfaces Multiple Caveats When Relying on LLMs to Write Code
New SonarSource research shows LLMs like GPT-4o, Claude Sonnet 4, and Llama-3.2 produce highly functional yet risky code — with frequent high-severity vulnerabilities, hard-coded credentials, and messy “code smells” that raise long-term ...
