Tag: software development
Debian’s AI Vote Bets on Accountability Instead of a Ban
Tom Smith | | AI coding, AI Governance, AI policy, AI-assisted development, AI-generated code, code review, confidential data, Debian, developer productivity, devops, generative AI, Human Oversight, open source, software development, software securityDebian’s new AI contribution policy avoids bans and mandatory disclosure, instead making developers responsible for reviewing AI-generated work and protecting sensitive data ...
Why “Tokenmaxxing” Was Always the Wrong Way for Developers to Measure AI Productivity
Drew Thompson | | ai, AI Development, AI security, application security, developer productivity, software developmentThe term "tokenmaxxing" left the developer lexicon just as quickly as it arrived, and like most viral technology concepts, it means different things depending on who's using it. In practice, the term ...
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 ...
Claude Code’s Temporary Usage Boost Expires Tonight. Here’s What Actually Changes
Tom Smith | | AI agents, AI coding agents, AI coding costs, AI coding tools, AI subscription pricing, Anthropic, CI pipelines, Claude Code, Claude Code usage limits, developer productivity, devops, Fable 5, software development, token limits, weekly usage capsAnthropic’s temporary 50% increase to Claude Code weekly usage limits expires August 19, reducing available capacity for developers and DevOps teams without lowering subscription prices ...
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 ...
Anthropic Makes Claude Code’s Auto Mode the Default, Betting Automation Beats Manual Review
Tom Smith | | agent permissions, agentic coding, AI code generation, AI coding agents, AI Governance, AI guardrails, AI permissions, AI safety, AI security, Anthropic, autonomous coding agents, Claude Code, Claude Code auto mode, Claude Code security, coding automation, developer productivity, developer tools, human engineering the loop, human-in-the-loop, permission fatigue, prompt injection, Pull Request Automation, secure AI agents, software development, software engineeringAnthropic is making Claude Code’s auto mode the default for Pro, Max and Team users, replacing constant permission prompts with classifier-based guardrails designed to catch risky actions without slowing developers down ...
Common Risks of Outsourcing Software Development, and How to Tackle Them
Roman Davydov | | Cybersecurity, devsecops, project management, software development, software development outsourcing, Third-Party RiskBoth SMBs and large enterprises often choose software development outsourcing over developing software in-house. It is no surprise, as partnering with external developers enables companies to bridge IT talent gaps that cannot ...
JetBrains Open-Sources KotlinLLM, a Research Prototype for Runtime Code Generation
Tom Smith | | agentic AI, AI coding tools, Apache License 2.0, asLlm, generative AI, IntelliJ IDEA plugin, JetBrains Research, Kotlin, Kotlin/JVM, KotlinLLM, LLM-generated code, mockLlm, persistent code generation, reviewable AI code, runtime code generation, Smart macros, software development, statically typed programmingJetBrains open-sources KotlinLLM, letting compiled Kotlin apps generate and persist LLM-written code at runtime instead of calling a model live ...
Anaconda Doesn’t Want to Be Just the Python Company Anymore
The question is no longer whether Anaconda wants to be more than the Python company. It is how much of the AI development stack DeSanto ultimately intends to own ...
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 ...
Five Technology Shifts In: Why the Hype Curve Lies in Both Directions
Jim Grunder | | AI adoption, AI tools, developer productivity, Engineering leadership, software developmentI've lived through five major technology shifts: mainframe to Windows in the early ‘90s, internet computing in the late ‘90s and early 2000s, Agile in the mid-2000s, cloud through the 2010s, and ...
