Agentic-Coding

The benchmark war just shifted terrain. Z.AI — the Chinese AI startup behind the GLM family — released GLM-5.1 today under an MIT license, and the numbers are hard to ignore: 58.4 on SWE-Bench Pro, edging past GPT-5.4 (57.7) and Claude Opus 4.6 (57.3). But the more interesting story isn’t the benchmark score. It’s the philosophy behind how Z.AI got there. Not About Reasoning Tokens — About Autonomous Work Time While most frontier labs have been chasing better logic through more reasoning tokens, Z.AI is optimizing for something different: productive horizons. How long can an agent work autonomously on a single task without going off the rails? ...

OpenAI’s Codex just got a major upgrade at the model level. As of April 4, GPT-5-Codex is the default model across Codex CLI, the Codex IDE extension, and Codex cloud environments. This isn’t GPT-5 — it’s a distinct variant, purpose-built for agentic coding workflows. What Is GPT-5-Codex? GPT-5-Codex is a GPT-5 variant optimized specifically for the demands of autonomous coding agents. Where GPT-5 is a general-purpose model, GPT-5-Codex is trained and tuned for: ...

If you’ve been following the “vibe coding” wave — the idea that you can describe what you want in plain English and an AI agent turns it into real software — Google just made the most aggressive move yet to own that space. On March 19, 2026, Google officially relaunched Google AI Studio with a complete full-stack vibe coding experience, powered by the new Antigravity coding agent and deep Firebase integration. This isn’t just a smarter autocomplete. This is an agent that can take a single text prompt and produce a production-ready, authenticated, database-backed web application. ...

In the fast-moving world of agentic AI tooling, few stories are more striking than what’s happening at Cursor. The AI-powered coding assistant startup is reportedly in talks with investors for a new funding round that would value the company at approximately $50 billion — nearly double the $29.3 billion valuation it secured just last fall. That’s not a typo. In less than six months, Cursor may have doubled its worth on paper. ...

One of the most persistent anxieties in agentic coding is the “what is this thing about to do to my repo?” problem. You describe a task. The agent starts executing. And somewhere between your request and the outcome, files get modified, commands get run, and irreversible things happen — sometimes incorrectly. Google just shipped a thoughtful solution to this problem in Gemini CLI: plan mode. Plan mode restricts the AI agent to read-only tools until you explicitly approve its proposed plan. No file writes. No command execution. Just analysis and a detailed proposal — which you review, approve (or reject), and then execute with confidence. ...

JetBrains developers — the IntelliJ IDEA, PyCharm, GoLand, and Rider community that numbers over 10 million globally — have just received a significant upgrade to their AI coding capabilities. GitHub Copilot’s JetBrains plugin has shipped a major update bringing custom agents, sub-agent coordination, plan agent as generally available features, and MCP auto-approve into preview — closing a meaningful gap with the VS Code Copilot experience. The update was confirmed by the official GitHub Changelog on March 11, 2026, making this one of the most reliably sourced stories this week (99/100 confidence from our Analyst). ...

Anthropic has built its brand on safety. Claude is consistently positioned as the thoughtful, cautious model — the one that pushes back on dangerous requests, that thinks about consequences, that errs on the side of care. So the DryRun Security research published today will raise some eyebrows: when used as an agentic coding agent building real applications, Claude produces the highest number of unresolved high-severity security flaws among the leading AI coding agents tested. ...

DryRun Security’s 2026 Agentic Coding Security Report found that Claude, when operating as an autonomous coding agent, produces more unresolved high-severity security flaws than Codex or Gemini. But here’s the thing: all AI coding agents produce security vulnerabilities. The model matters less than your review process. This guide walks you through a practical security audit workflow for AI-generated code, applicable regardless of which model or agent you’re using. Before You Start: Understand the Risk Profile AI-generated code has specific vulnerability patterns that differ from human-written code. Knowing what to look for saves time. ...

DryRun Security’s 2026 Agentic Coding Security Report landed a finding that should make every engineering team pause: 87% of pull requests written by AI coding agents (Claude, Codex, Gemini) introduced at least one security vulnerability. Not occasionally — consistently, across all three leading models, in real application development scenarios. This isn’t a reason to stop using AI coding agents. The productivity gains are real. But it is a strong signal that AI-generated code needs a security review process as rigorous as — or more rigorous than — what you’d apply to human-written code. ...

Something that once sounded like science fiction just became engineering reality. Anthropic’s Boris Cherny — the creator of Claude Code — confirmed on X this week that the AI coding tool is now 100% written by itself. Not mostly. Not mostly-ish with some human help. One hundred percent. The post was simple: “Can confirm Claude Code is 100% written by Claude Code.” It has since surpassed 133,000 views, and for good reason: this is one of the clearest milestone moments of recursive AI improvement we’ve seen from a production system. ...