JetBrains DataGrip, a cross-platform database IDE, is now free for non-commercial use including learning, hobby projects, open-source development, and content creation. The change follows similar moves for RustRover, CLion, Rider, WebStorm, and RubyMine. All commercial features remain available in the free version, including AI-powered code completion, multi-database support, and Git integration. Commercial users must still purchase licenses. The free license lasts one year with automatic renewal and requires anonymous telemetry sharing.

GitHub now allows developers to resolve merge conflicts directly in the web interface with one-click buttons. When a pull request has conflicts, users can choose to accept incoming changes, current changes, or both without leaving their browser. This feature brings the convenience of code editor merge tools like those in Visual Studio Code to the GitHub web workflow, eliminating the need to switch contexts or use local development environments.

A developer successfully built and deployed a complete full-stack game in just 7 days using AI assistance, despite having no prior experience with React, JavaScript, or FastAPI. The project utilized Gemini Code Assist in VS Code as a co-pilot and mentor, demonstrating how AI tools can accelerate learning and development. The experience highlights that AI serves as an enabler rather than a replacement, with humans providing direction and vision while AI handles implementation details.

Major tech companies like GitHub, Google, Dropbox, and Microsoft are measuring AI's impact on software development using a combination of traditional engineering metrics (change failure rate, PR throughput) and AI-specific metrics (time savings, adoption rates, customer satisfaction). The research reveals that 85% of engineers use AI tools at work, but measuring their true impact requires tracking both speed and quality metrics together. Companies are finding AI particularly effective for code migrations and grunt work, while being cautious about data security and long-term code maintainability. The measurement approach combines system data, periodic surveys, and experience sampling to get a complete picture of AI's effect on developer productivity.

A product's data model—the core concepts and objects it prioritizes—determines whether new features create compounding advantages or just add to a feature list. Companies like Slack (persistent channels), Notion (blocks), Figma (shared canvas), and Rippling (employee records) succeeded by choosing non-obvious data models that became impossible for competitors to replicate without rebuilding from scratch. As AI commoditizes code execution, the data model becomes the primary moat. Horizontal tools innovate on how products are built, while vertical tools succeed by elevating the right domain objects. The key is identifying the atomic unit of work in your domain and ensuring every new feature strengthens that central concept.

Visual Studio Code version 1.105 introduces AI-powered merge conflict resolution, OS notifications for task completion and chat responses, and native macOS authentication. The release expands MCP marketplace support for installing servers directly from the Extensions view, adds fully-qualified tool names to avoid conflicts, and improves chat features with recent session history, chain of thought display, and better edit tools for custom models. Additional enhancements include terminal dictation controls, test coverage reporting in the runTests tool, and support for nested AGENTS.md files for workspace-specific AI instructions.

Microsoft released Amplifier, an experimental development environment that enhances AI coding assistants with 20+ specialized agents, a knowledge extraction system, parallel worktree workflows, and automatic conversation transcript preservation. The tool provides pre-loaded patterns, context management, and automation to transform AI assistants into more capable development partners. It requires Python 3.11+, UV, Node.js, and works primarily in WSL2, though it's explicitly marked as early-stage research software with no stability guarantees or official support.