Tag: developer productivity
GitHub Puts Copilot in the Approval Seat for Pull Requests
Tom Smith | | AI code review, AI coding, AI Governance, automated code review, branch protection, code review, Copilot code review, developer productivity, developer tools, devops, Engineering Governance, github, GitHub approvals, GitHub Copilot, PR approvals, pull requests, software development, software lifecycleGitHub Copilot can now submit binding pull request approvals, moving AI code review from advisory feedback into the merge decision itself ...
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 ...
Your AI Coding Budget Is Becoming a Variable Cloud Bill
Carla Castillo | | agentic coding, AI coding assistants, AI coding costs, AI cost management, AI credits, AI developer tools, AI Governance, cloud economics, cost per developer, developer productivity, devops, engineering spend, FinOps for AI, GitHub Copilot, model mix, platform engineering, premium models, SaaS budgeting, token billing, usage based billingAI coding assistants are becoming a variable, usage-based engineering cost, forcing platform and DevOps teams to apply FinOps practices to models, credits, utilization and multi-vendor spend ...
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 ...
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 ...
Developer Resistance to AI Isn’t Fear – It is Identity
Lukasz Lazewski | | 1000x developer, agentic coding, AI adoption, AI agents, AI code review, AI coding tools, AI Orchestration, AI transformation, AI-assisted coding, AI-generated code, coding with AI, developer accountability, developer experience, developer identity, developer motivation, developer productivity, developer resistance to AI, developer trust in AI, developer workflow, Engineering leadership, Future of Programming, human-AI collaboration, software architecture, software developers, software engineeringDeveloper resistance to AI is less about job loss than a deeper shift from hands-on coding to supervising, validating and orchestrating AI-generated work ...
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 ...
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 ...
GitHub Brings Stacked Pull Requests Out of the Shadows
Tom Smith | | AI coding agents, branch protection, code quality, code review, continuous integration, developer productivity, DevOps workflows, gh-stack, GitHub Copilot, GitHub public preview, GitHub stacked pull requests, merge queues, pull request size, software engineering, Stacked PRsGitHub introduces native stacked pull requests, helping development teams break large changes into smaller, dependency-ordered PRs that are faster and easier to review ...
The Innovation Puzzle 2.0: Connecting Vision and Value
Suneetha Uppalapati | | AI Governance, AI strategy, developer productivity, digital transformation, enterprise architecture, enterprise innovationThe tech landscape constantly evolves, making it tempting to chase every new trend. Ironically, in today's business world, the word "innovation" has become almost synonymous with technology adoption. Yet after years of ...
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 ...
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 ...
