Tag: software development
Survey Surfaces Sharp Increase in Amount of Code Written by AI
A global survey of 705 developers and IT leaders finds 42% of respondents reporting that artificial intelligence (AI) now writes at least half their code, with only 21% of developers now spending ...
Git 2.56 Takes Aim at Messy Merges, Slow Diffs and Branch Sprawl
Tom Smith | | AI coding agents, CI/CD, coding agents, developer tools, devops, GIT, Git 2.56, Git performance, Git repositories, merge conflicts, monorepos, platform engineering, software development, source control, version controlGit 2.56 improves merge safety, speeds up large-repository operations and adds cleanup tools that could prove especially useful for AI coding agents and busy DevOps teams ...
IT Outsourcing Versus In-House Development
Sambhav Aggarwal | | AI-assisted development, cloud infrastructure, Cybersecurity, developer productivity, devops, DevOps outsourcing, digital transformation, engineering costs, engineering strategy, engineering teams, global talent, hybrid teams, in-house development, IT outsourcing, product development, QA outsourcing, scalable development, software delivery, software development, software engineering, software outsourcing, software partners, technical talent, time to marketThe debate isn't new — but the stakes are. In 2026, the gap between companies that get this decision right and those that don't is measured in product cycles, burn rate, and ...
Anthropic Adds a Coordinator to Claude Projects for Running AI Work in Parallel
Tom Smith | | agentic AI, AI agents, AI coding agents, AI Development, AI project management, AI workflows, Anthropic, autonomous coding, Claude Code, Claude Projects, cloud development, code review, coding automation, developer productivity, developer tools, devops, Git branches, human-in-the-loop, multi-agent orchestration, parallel development, platform engineering, pull requests, software development, software engineeringAnthropic’s redesigned Claude Projects coordinates parallel Claude Code sessions, delegates work across branches and brings the results back through familiar pull-request review workflows ...
Factory Raises $200M as It Builds Agents Across the Software Lifecycle
Jaime Hampton | | AI agents, AI coding, AI Software Engineering, devops, factory, generative AI, software developmentEnterprise coding agent startup Factory announced it has raised $200 million at a $5 billion valuation, more than tripling its valuation from its last funding round five months ago. Founded in 2023, ...
Stop Chasing 100% Test Coverage: Why DevOps Teams Need to Test Smarter, Not More
Adonis Celestine | | AI testing, application security, CI/CD, continuous testing, devops, PRisMA, Product Risk Management, QA, QFD, Quality Assurance, Quality Functional Deployment, Rapid Risk Assessment, regression testing, release management, risk-based testing, RRA, software development, software quality, software testing, test automationEvery software team eventually runs into the same question: How much testing is enough? For years, the default answer has been "more." More automated tests. More regression suites. More environments. More devices ...
Hybrid Software Development: Benefits and Challenges
Roman Davydov | | development teams, devops, Hybrid Software Development, IT strategy, outsourcing, software developmentFortunately, companies do not always have to choose between in-house vs outsourcing. Instead they can adopt a hybrid development strategy, which combines the capacities of internal and external IT teams. This approach ...
GitHub Puts Guardrails on Copilot’s Sandbox Inside JetBrains IDEs
Tom Smith | | AI agents, AI coding agents, AI Governance, Copilot sandbox, Developer Security, developer tools, Enterprise AI, filesystem controls, GitHub Copilot, GitHub Copilot JetBrains, IDE security, JetBrains, managed policies, MCP governance, network controls, OpenTelemetry, platform engineering, sandbox security, software developmentJetBrains IDEs are where a lot of enterprise backend work happens — Java, Kotlin, Spring, big monorepos with a lot to break. So when an AI coding agent starts running shell commands ...
Rust’s First Debugging Survey Shows Most Developers Skip the Debugger Entirely
Tom Smith | | async Rust, dbg macro, developer experience, developer tools, GDB, LLDB, platform engineering, print debugging, runtime debugging, Rust compiler, Rust debugger, Rust debugging, Rust developers, Rust tooling, software debugging, software development, systems programming, ustMost Rust developers don't use a debugger. That's the headline finding from the Rust compiler team's first dedicated debugging survey, and it's worth sitting with for a second. Rust has spent years ...
GitHub’s New Copilot Feature Takes the Guesswork Out of Picking AI Models
Tom Smith | | agentic AI, AI agents, AI coding assistants, AI cost optimization, AI Governance, AI model routing, Code Generation, developer tools, devops, github, GitHub Copilot, model selection, multi-model orchestration, platform engineering, Project HydraFusion, software developmentGitHub’s Project HydraFusion brings multi-model orchestration to Copilot, automatically routing coding tasks across AI models to balance quality, cost and complexity ...
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 ...
