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Waterfall 2.0: Controlling LLM-Driven Software Development with Stage-Gated Discipline
Georgy Starikov | | ADRs, Agile vs Waterfall, AI coding, AI development lifecycle, AI Software Engineering, AI-assisted engineering, architecture decision records, combi-shaper, engineering workflows, generative AI development, knowledge corpus, LLM engineering, LLM software development, MCP, Model Context Protocol, software architecture, software testing, system design, Waterfall 2.0Waterfall 2.0 reimagines classic stage-gated software development for the LLM era, combining fast AI generation with structured validation, cheap backtracking and a shared knowledge corpus ...
Why API Test Generation Is a Judgment Problem, Not a Code Generation Problem
Abhishek Saikia | | adaptive test coverage, AI API testing, AI quality engineering, AI test generation, API test generation, API testing, Automated testing, cross-field testing, DevOps Testing, fine-tuning, LLM testing, QA automation, RAG, software testing, test assertions, test coverageWhen we started using large language models for API test generation at KushoAI, the results were impressive on the surface. Tests appeared in seconds. Coverage breadth went up. The team was excited ...
Why Cryptographic Inventory Is the First Step Toward Quantum Readiness
Michael Carter | | CBOM, CI/CD security, crypto-agility, cryptographic dependencies, cryptographic discovery, cryptographic inventory, cryptography bill of materials, devops security, devsecops, Kubernetes security, ML-KEM, NIST PQC migration, post-quantum cryptography, PQC, quantum readiness, Software Supply Chain SecurityPost-quantum readiness starts with visibility. DevOps teams need a continuous cryptographic inventory to map algorithms, keys, certificates, libraries, infrastructure and third-party dependencies before PQC migration begins ...
npm v12 Shuts Down a Popular Malware Trick — But the Threat Isn’t Going Away
For years, one of the easiest ways to sneak malware onto a developer's machine has been to hide in plain sight. Install a package from npm, and any lifecycle script bundled with ...
AI Agents Are Writing Code Faster Than Anyone Can Review It. Tessl Is Betting On Standards To Close That Gap
Every team that has turned coding agents loose on real work has run into the same wall. The agents write fast. They write a lot. And somewhere between the tenth and twentieth ...
Critical Flaw in isolated-vm Can Lead to Sandbox Escape, RCE Threat
Jeff Burt | | Activepieces, AI security, C/C++, Endor Labs, isolated-vm, JavaScript security, Mastra, n8n, Node.js security, remote code execution, Sandbox, software vulnerability, TOCTOU, V8 Isolate, vm2Developers for years have been using vm2, an open-source Node.js library, to run untrusted JavaScript inside a secure and isolated sandbox environment. It uses Node.js’s built-in modules and JavaScript Proxies and lets ...
UiPath Test Cloud: Robots Handle Repetition, Agents Adapt and Humans Lead
Most companies don't actually struggle to ship software anymore. AI made that part fast. What they struggle with is releasing what they built with any real confidence in it. That gap between ...
GitHub Sharpens CodeQL’s Eye on Actions Workflows and Modern JavaScript
GitHub Actions pipelines have become one of the quieter attack surfaces in software development. They pull in third-party actions, cache dependencies, and pass secrets between jobs, often without anyone reviewing the workflow ...
Elevating Technical Documentation: Using Predictive AI to Standardize Visual Knowledge Bases
Nazim Ghori | | AI documentation, AI visual validation, architecture diagrams, CI/CD documentation, computer vision, developer documentation, developer experience, devops automation, DevOps documentation, documentation automation, documentation drift, documentation quality, documentation quality gates, Git workflows, knowledge bases, OCR, predictive AI, screenshot validation, technical documentation, visual validationEvery release changes documentation alongside the code. Developers depend on that documentation during implementation, maintenance and troubleshooting. A diagram becomes misleading once services are renamed or integrations change without a corresponding documentation ...
How to Avoid Repeating the “Automate Everything” Mistake Due to AI FOMO
Alexey Golubev | | AI engineering, AI FOMO, AI Governance, AI implementation, AI in DevOps, AI maturity model, AI productivity, AI ROI, AI SDLC maturity, AI strategy, AI tools, AI-Driven DevOps, artificial intelligence, Cursor, DevOps AI adoption, devops automation, GitHub Copilot, Kubernetes AI, software development lifecycleThe DevOps community has already experienced technological extremes. You might recall the time when automation was thought of as a panacea for all possible engineering issues, and the slogan “Automate Everything” was ...
Why Self-Healing Tests Need a Deployment Gate
Suneet Malhotra | | artificial intelligence, CI/CD, devops, Self-Healing Automation, software testing, test automationWhen an end-to-end test fails after a front-end change, the repair often looks routine. A class name changed. A button moved. A selector that used to be unique now matches two elements ...
Cursor Launches Origin Code Hosting Platform as GitHub Rival
AI coding provider Cursor has launched Origin, a code hosting platform that puts source code and AI coding agents inside the Cursor development environment. The new coding platform expands the company into ...
