Coding Assistance

Continue is an open-source coding autopilot for VS Code that replaces manual ChatGPT copy-pasting with an integrated LLM assistant. It emphasizes transparency, hackability, and user control by supporting any LLM (local or cloud), collecting development data locally, and offering extensive customization through slash commands, context sources, and policies. The platform enables developers to maintain privacy while leveraging AI assistance and automatically gather data to improve their own LLM models.

OpenClaw v2026.7.2-beta.1 introduces remote coding sessions on cloud workers, native automation and mobile capabilities, safer channel operations, guided Control UI setup, improved gateway and session recovery, and new Linux packaging options. The release encompasses 2425 merged PRs with major enhancements to session management, coding agents, security boundaries, and reliability across multiple platforms including mobile, desktop, and headless systems.

Claude Code v2.1.197 introduces Claude Sonnet 5 as the new default model, featuring a native 1M-token context window for enhanced processing capabilities. The update includes promotional pricing of $2/$10 per million tokens through August 31, making it more cost-effective for users. This release represents a significant upgrade in model performance and context handling for the Claude Code platform.

Claude Code v2.1.170 introduces Claude Fable 5, a powerful Mythos-class model now available for general use with capabilities exceeding all previously released models. The release also fixes a critical bug where sessions launched from VS Code's integrated terminal failed to save transcripts and weren't resumable. Users should update to access Fable 5's enhanced capabilities and benefit from the session persistence fix.

This cookbook demonstrates building a vulnerability-discovery agent using the Claude Agent SDK that automatically threat-models C source code, hunts memory-safety bugs using built-in file tools (Read, Grep, Glob), and generates structured security reports. The agent operates in a multi-turn session with a bootstrap threat-modeling phase, an interview phase for owner input, and automated vulnerability finding and triage loops. The approach reduces false positives compared to traditional static analyzers by using Claude's reasoning to identify high-confidence memory-safety issues in a read-only sandbox environment.