Tag: AI coding assistants
Adronite Unveils AI Coding Tool Based on Embedded Context Engine
Mike Vizard | | ACE, Adronite, Adronite Context Engine, AI code generation, AI coding assistants, AI coding tool, AI-generated code, code review, codebase context, Codistry, developer tools, devops, open-weight AI models, software development, token efficiencyAdronite launches Codistry, an AI coding tool that uses a context engine to map codebases, reduce token usage and generate more production-ready code ...
Are LLMs Equally Good (or Bad) at Building Secure Software?
Pieter Danhieux | | agentic AI, AI agents, AI code security, AI coding assistants, AI coding costs, AI coding models, AI Development, AI model benchmarking, AI-generated code, application security, Developer Security, framework security, LLM security, OWASP Top 10, SAST, secure code generation, secure coding, software development, software security, token costsAn SCW study finds a large variance in how frontier and budget LLMs perform across different frameworks, and explains the striking cost variance ...
Validation Debt That Your Dashboards Are Not Showing
Saqib Jan | | AI coding assistants, devops, Enterprise AI, software quality, software testing, validation debtThe gap between how fast AI writes code and how reliably teams verify it is quietly becoming a balance-sheet risk. Enterprise leaders are learning to measure it before it forces repayment. Every ...
AI Agents Are Writing Your Infrastructure Code. Is Anyone Governing It?
Neel Shah | | agentic infrastructure, AI agent governance, AI coding assistants, AI-generated infrastructure, cloud misconfiguration, cloud security automation, continuous drift detection, devops security, IAM misconfiguration, infrastructure as code security, infrastructure compliance, infrastructure guardrails, Kubernetes security, platform engineering security, policy as code, RBAC for AI agents, secure-by-default platforms, SRE governance, StackGen Aiden, Terraform securityAI agents now generate infrastructure code at scale, but security pass rates are stuck at 55%. Here’s how teams can close the governance gap ...
The Next DevOps Bottleneck: When AI Generates More Software Than Organizations Can Manage
The organizations that benefit most from AI will probably not be the ones generating the largest amount of code. They will be the ones who build systems capable of managing software at ...
Attackers Exploit SimpleHelp Flaw to Steal Info from AI Coding Assistants, Clouds
Jeff Burt | | AI coding assistants, Anthropic Claude Security, Blackpoint Cyber, Cloud accounts, cryptocurrency, Djinn Stealer, Google Gemini, information stealer, OpenAI Codex, RMM software, SimpleHelpThreat actors are exploiting a known security flaw in the SimpleHelp remote monitoring and management (RMM) software to drop two previously unknown pieces of malware that can compromise a broad range of ...
AI-Generated Apps Without DevOps: A Security Disaster Waiting to Happen
Sannan Ali | | AI coding assistants, application security, CI/CD security, devops, Software Supply ChainA small internal tool was built over a weekend. An engineer used an AI coding assistant to generate most of the backend. A simple interface was added, a few API calls were ...
Lightrun: IT is in the Dark Over Coding Assistant Runtime Visibility
Adrian Bridgwater | | AI coding assistants, AI-generated code, AI-Powered Engineering, AI-SRE Tools, Application Performance Management (APM), automated remediation, Autonomous Engineering, developer productivity, Lightrun, Manual Debugging, Memory Usage, Observability Stacks, platform engineering, Production Failures, Real-Time Data, Redeploy Cycles, root cause analysis, Runtime Visibility, Site Reliability Engineering (SRE), software reliability, State of AI-Powered Engineering Report 2026, Static Code Generation, System Behavior, tribal knowledge, Variable States, Verification BottleneckSoftware runs, but sometimes it doesn’t… and that’s often down to a lack of runtime visibility in relation to platform engineering teams being able to trust coding assistants and AI-powered site reliability ...
Google Launches Developer Knowledge API to Give AI Tools Access to Official Documentation
Tom Smith | | AI coding assistants, AI-assisted development, API Integration, API reference entities, automation, content source of truth., current best practices, Developer Knowledge API, development workflows, devops teams, Firebase, Google Cloud, implementation guidance, knowledge transfer, language models, Markdown retrieval, MCP Server, Model Context Protocol, official documentation, outdated documentation, programmatic access, real-time information, reliable AI assistance, security and trust, structured content support, troubleshootingGoogle's new Developer Knowledge API and MCP server provide AI assistants with direct access to up-to-date Google developer documentation ...
Meta Introduces Confucius Code Agent: A New Approach to AI-Powered Software Engineering
Tom Smith | | Agent Architecture, Agent Experience, AI coding assistants, AI Development Systems, AI Software Engineering, code refactoring, Confucius SDK, developer experience, Hierarchical Working Memory, Modular Interfaces, Performance Evaluation, Persistent Memory, Problem-Solving Styles., software development, SWE-Bench-Pro Benchmark, Tool Management, user experienceExplore the Confucius Code Agent by Meta and Harvard, designed to enhance productivity in software engineering with a focus on agent architecture and operational performance ...
Best of 2025: AI in Software Development: Productivity at the Cost of Code Quality?
New research analyzing 153 million lines of code reveals AI tools may accelerate development but potentially at the expense of maintainable, quality code ...
Code Quality and Security Risks of AI-Generated Code
Joydip Kanjilal | | AI attack surface, AI code security, AI coding assistants, AI development tools, AI model limitations, AI security challenges, AI training data vulnerabilities, AI-generated code, AI-powered development risks, automated code review, ChatGPT code generation, CI/CD security scanning, code quality risks, code security best practices, dependency risks, developer awareness, GitHub Copilot risks, hallucinated code, human-led code review, inefficient algorithms, insecure AI code, insecure code patterns, poor code maintainability, secure coding practices, software development security, spaghetti code, technical debt from AI toolsAI-powered tools and coding assistants have become popular and widely used among software developers for several reasons. They promise to deliver not only speed and comfort but also a tool for filling ...
