
AI coding agents still need human cleanup on nearly three out of four tasks in a real-world test
Co-Design Bench shows top models like GPT-6 Astra complete only 26% of real tasks, requiring human cleanup.
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Co-Design Bench shows top models like GPT-6 Astra complete only 26% of real tasks, requiring human cleanup.

Postman’s installer auto-approves its own startup hook for Codex, raising consent concerns for developers.

Poisoned Markdown instruction files let agents alter MCP configuration, bypass approvals and leak OAuth tokens; one real attempt was blocked at a customer.

Northwestern researchers found AI vulnerability patches often stop crashes yet fail the maintainers' own tests.

Glow Labs found AI coding agents leaked 13,000+ internal screenshots, including customer billing records, to public GitHub repos across 300+ organizations.

AI coding agents uploaded 13,000+ internal screenshots, including billing records, to public GitHub repos across 300+ organizations, invisible to security teams.

Enterprise comparison finds Copilot and Kiro indemnify generated code, while Cognition's Devin terms exclude outputs.
Anthropic added AGENTS.md support to its Claude Code CLI, letting developers feed repository-specific instructions to the coding agent.

Researchers disclosed Plugin4Shell, a zero-click RCE in Claude Code, Codex, Gemini CLI, and Copilot caused by unverified Git plugin checkouts.

Researchers disclosed Plugin4Shell, a zero-click RCE in AI coding agents' Git SHA-pinned plugin updates, affecting Claude Code, Codex, Copilot, and Gemini CLI.

Docker fixed CVE-2026-77179 (CVSS 9.4), a virtio-fs symlink flaw letting code inside macOS Sandboxes VMs read and modify host files; update to 0.42.0.
Simon Willison argues developers disheartened by AI coding agents should move past existential crisis and refocus on broader engineering problems.

Quesma's $1,500 benchmark found RTK cuts reported token output but changes Claude Code and DeepSeek coding costs by only about 5% on Terminal-Bench 2.1.
Researchers present SMART, an ML performance-modeling library regenerated by AI coding agents from natural-language design docs instead of code.
Datadog Security Labs tested Sonnet 5, Composer 2.5, and GPT 5.5 to see if plan mode yields more secure code than default mode.
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