Frederic Lardinois writes that Harness field CTO Martin Reynolds is addressing the surge in pull requests caused by coding agents, which can increase new code volume from 1.5x to as much as 50x. To manage this "review bottleneck," Harness has launched a rebuilt Code Repository and an AI Code Review product designed specifically for high-frequency agent traffic rather than just human teams. The company's approach focuses on using a software delivery knowledge graph to provide reviewers with context quickly, helping them distinguish critical code changes from routine dependency updates.
- Coding agents can increase the volume of pull requests by 10x to 50x compared to traditional developer workflows.
- Harness rebuilt its repository service as an "AI-first" platform that is Kubernetes-based and runs across multiple clouds.
- The new AI Code Review tool integrates with existing GitHub repositories, allowing teams to use it without migrating their entire codebase.
- Coding agents can increase the volume of pull requests by 10x to 50x compared to traditional developer workflows.
- Harness rebuilt its repository service as an "AI-first" platform that is Kubernetes-based and runs across multiple clouds.
- The new AI Code Review tool integrates with existing GitHub repositories, allowing teams to use it without migrating their entire codebase.
Anurag Singh writes that Cursor’s strength is its capacity for deep project understanding through efficient context management rather than simple model speed. Instead of pushing a whole repository into an LLM's window, the IDE employs search tools to provide only relevant code segments as tasks arise. This curated approach ensures models receive high-quality information and instructions tailored to their specific capabilities, allowing them to maintain existing architectural patterns more effectively.
* The tool uses Instant Grep via a local text index instead of scanning every file from scratch.
* Cursor is significantly more effective in complex or large projects where it can identify and reuse established implementations.
* Its search ability helps prevent the common problem of generating redundant helper functions that already exist within the codebase.
* The tool uses Instant Grep via a local text index instead of scanning every file from scratch.
* Cursor is significantly more effective in complex or large projects where it can identify and reuse established implementations.
* Its search ability helps prevent the common problem of generating redundant helper functions that already exist within the codebase.
Simon Willison reviews Ornith-1.0, a new series of open-weights models from DeepReinforce designed for agentic coding. Built on Gemma 4 and Qwen 3.5, these models range from 9B to 397B parameters and demonstrate high proficiency in coding benchmarks and tool-use tasks.
- Available in 9B Dense, 31B Dense, 35B MoE, and 397B MoE variants
- Capable of navigating codebases and executing complex tool calls
- Built on Apache 2.0 licensed base models
- Available in 9B Dense, 31B Dense, 35B MoE, and 397B MoE variants
- Capable of navigating codebases and executing complex tool calls
- Built on Apache 2.0 licensed base models
