AI Coding

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Checking agent-generated code usually means hopping between tabs. Learn how to view diffs, run terminal commands, and preview web apps side by side in the GitHub Copilot app. The post GitHub Copilot app for Beginners: Using the diff, terminal, and browser appeared first on The GitHub Blog.

Google has open-sourced Mantis, a stack-agnostic toolkit of security review skills for AI coding agents. It runs the full vulnerability lifecycle: sweep the code, filter false positives, reproduce the bug in a sandbox, patch it, re-attack the patch, then score the risk. Apache 2.0, and documented as demonstration-only. The post Google Open-Sources Mantis: A Modular Skills Toolkit That Lets Coding Agents Find, Reproduce and Patch Vulnerabilities appeared first on MarkTechPost.

AI models now power all manner of agents, from coding assistants that write and debug software to customer service systems The post Claude did best on a new benchmark for agents that build agents. It still passed fewer than a quarter of the tests. appeared first on The New Stack.

This article presents five no-cost ways to access AI coding agents and models: free model access through OpenCode Zen, OpenAI Codex on the ChatGPT free plan, Kilo Code's Auto Free routing, OpenRouter's free model API, and Google Antigravity's $0 individual plan.

Catenary is a spatial canvas IDE for AI coding agents, presenting a visual, canvas-based workspace for code and AI-driven development. It is currently listed on Product Hunt with a discussion thread and link.

Project HydraFusion is a research preview from GitHub that reframes model selection as an optimization problem. Instead of picking one model, it dynamically chooses a workflow for each request — drafting, critiquing, or escalating across models from multiple providers. Currently available in GitHub Copilot CLI only, it bills per token at each model's standard rate.

GitHub is introducing Project HydraFusion, a research preview in GitHub Copilot that automatically orchestrates models from multiple providers—using single, cascade, or critique workflows—to balance quality, cost, and latency for each coding task. In offline agentic benchmark evaluations, HydraFusion matched or exceeded the Claude Opus 5 baseline on verified quality while cutting estimated workflow cost by 36–67%.

Coder has launched Coder Agent Relay with SpaceXAI as its launch partner, allowing regulated enterprises to run coding-agent tools in self-hosted Coder workspaces while Cursor handles inference and planning in the cloud. Coder CEO Rob Whiteley says the real issue isn't raw token spend but uneven adoption, and that deployment architecture often leads security teams to block Cursor outright.

Learn how to run parallel agents in the GitHub Copilot app, and experience the moment it stops feeling scary and starts feeling powerful.

GitHub shares how GitHub Copilot reduces AI coding cost by optimizing the completed task rather than individual tool calls. Four improvements—selectively compressing noisy output, removing unused line numbers, behavior-tested prompt compression, and batched background-result delivery—cut inference cost, prompt tokens, or AI Credits by roughly 1–5 percent without material quality regressions.

Paint.NET's author, Rick Brewster, reveals that to run on WINE, they used Claude, an AI tool, to create a clean-room reverse-engineered rewrite of Direct2D. This 180,000-line codebase is described as a product of 'vibe coding,' lacking thorough review, yet Claude's reverse-engineering prowess was impressive, albeit requiring substantial babysitting.

Atos partnered with AWS to host a three-day AI League event that upskilled 400 engineers in agentic AI through hands-on building of multi-agent systems. Engineers used native AWS services such as Amazon Bedrock and AgentCore, competed on a live leaderboard, and tackled challenges testing skills like guardrails, code generation, memory, and pathfinding. The article explains the format, architecture, and lessons for enterprises.

Foremerge is an open-source coordination protocol that prevents conflicts among AI coding agents by having them declare their intent before editing. Built on Git, it compares plans semantically using a shared database and warns of collisions before any agent starts coding, without locking files or relying on model judgment.

Back to Blog The Problem Modern AI work already spans multiple tools. You might research in Gemini, think things through in ChatGPT, build in Claude Code or Cursor, and keep follow-up discussions going across all of the…

Introducing wrapture New from Graham Dumpleton (of wrapt, mod_wsgi, and New Relic's Python agent fame), who describes Wrapture as taking the monkeypatching ideas from wrapt and extending them to apply to testing and tracing at the same time. Wrapture (full documentation here) makes it easy to wrap any function or method such that all access can be traced, or can be overridden to return a different value. It acts as both an alternative to unittest.mock and a way to implement tracing against an existing project: Attaching observation to code you do not control, recording what flows through it, and doing so without disturbing the program being watched, is a problem I have never really stopped thinking about. Wrapture includes OpenTelemetry support and even has an entirely configuration-based…

Three weeks ago we published an audit tracing a widely repeated 97%-failure-rate statistic back to a content-marketing article with no source, and along the way found a data-integrity bug in the most-reused public n8n w…

Cursor began rolling out Origin, its own code hosting platform, to paid users on Monday morning. Roughly three and a half hours later, GitHub's status page lit up with what became a six-hour-and-forty-two-minute global…

hotSecurity Aug 30, 2026 • 3 min read AI coding agents followed abandoned package references Researchers found 120 unclaimed package or domain references across corporate llms.txt files. AI agents could use them to inst…

Tags: AI, LLMs, Coding, Technical Debt, Software Engineering Superhuman AI coding still makes software worse. AI is probably better than humans at writing code now. But skill at coding is not exactly the same thing as s…

NatashaTheRobot Aug 30, 2026 I’ve been seeing a lot of posts lately saying that software engineers who use AI miss the flow state. This is a bit surprising to me because if anything, using AI puts me into an ULTRA INTEN…

MCPSTRICT TYPESCRIPTZERO-CONFIG Persistent, Project-Local Memory for AI Coding Agents Coding agents forget decisions between sessions. OpenContext MCP exposes a lightweight Model Context Protocol server that enables AI…

AI-assisted development Use Cursor, Claude, Copilot, or any coding agent to build on Lumify — with MCP tools, machine-readable docs, and copy-paste prompts that prevent hallucinated endpoints. API key Sign in, or get an…

Elon v Altman has a real consequence.

An AI copilot is an AI assistant embedded directly in a software application. It...

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AI coding bot vendors tell you to use a context file with instructions for the chatbot on how to edit your project. Claude Code wants a CLAUDE.md, or there’s AGENTS.md in general. [Anthropic] But does your AGENTS.md do…

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The product is the crane A long-horizon harness you run. Not a plugin pack inside someone else’s. Most things branded “harness engineering” are skills, agents, and slash commands that sit inside Claude Code or Copilot.…

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AI coding company Replit is throwing its weight behind the model-routing trend by making its “intelligent model routing” system the The post Replit’s new default: Auto mode picks the best model for each task appeared first on The New Stack.

The Independent AI Coding Community AI Tools Search & browse all AI tools AI Jobs International roles · opportunities Creative Studio Image · Video · Training AI Models Curated models, explained AI Skills Handy prompts,…

Managing library updates can be tedious at times. Learn how the GitHub Copilot app can handle this type of repetitive task. The post GitHub Copilot app for Beginners: Automate Dependabot pull request triage appeared first on The GitHub Blog.

Everyone's using AI coding agents. Here's how to make yours actually useful.

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arXiv:2608.23622v1 Announce Type: new Abstract: Large language models (LLMs) have shown strong capabilities in reasoning, planning, and tool use, but many scientific and engineering tasks require more than plausible text and code generation. They require understanding how a system responds to intervention, which in practice depends on controlled experimentation. In this work, we propose a multi-agent framework that enables LLM agents to conduct controlled experiments with scientific simulation models for pharmaceutical process design. Given a user query and a baseline configuration, the system constructs a structured task representation, designs experiments, executes comparative simulation, interprets the resulting outcomes, and synthesizes evidence-based recommendations for process param…

TL;DR — Key Takeaways JetBrains has launched Junie Local, an on-device version of its AI coding agent that runs entirely on supported Macs without cloud inference or token charges. Junie Local uses a JetBrains-tuned, 4-…

The AI-coding stack: a map for a landscape that won't sit still seed · Aug 17, 2026 Every week ships a new AI coding tool, and every announcement uses the same words: agent, context, autonomous, 10x. I’ve argued before…

Many developers have been changing their workflows to incorporate AI coding agents more heavily, thanks to powerful frontier large language models and increasingly sophisticated harnesses like Claude Code or Codex, but…

There was a brief window where AI agent security felt like a future problem. Organizations deployed copilots, coding assistants, and autonomous workflows on the assumption that the worst case was a bad recommendation or a hallucinated answer. That window closed in the first half of 2026, when a cluster of vulnerabilities and a landmark incident […]

Turn a feature into a demo video Describe a product or feature and Mirenta generates a looping, animated walkthrough — browser chrome, a moving cursor, clicks, and callouts included.

Code maintainability plummets in the AI coding era AI code is rotting codebases. July 07, 2026 You have 1 article left to read this month before you need to register a free LeadDev.com account. Estimated reading time: 4…

Posted at August 23, 2026 It was a summer holiday, sometime in the late 1990s. I was a young kid, around 8 or so. My dad had taught me the rules of chess before and we played from time to time. But this time was differe…

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While most AI coding tools default to cloud-hosted models, local model runtimes have become a viable alternative for developers who The post Junie now runs entirely offline. Can you spare a 64 GB M5 Mac? appeared first on The New Stack.

You can now code your own mini games and 'gizmos' with no experience. Creating is just half the fun.

arXiv:2608.20349v1 Announce Type: new Abstract: Large Language Models (LLMs) exhibit extreme sensitivity to surface-level prompt variations, in which minor lexical changes can trigger disproportionate performance fluctuations. Moving beyond black-box optimization and coarse-grained templates, we present the first large-scale, n-gram token-level mechanistic analysis of prompt stability, leveraging a dataset of 132,000 prompt variants. Our investigation reveals a fundamental Scaling Law of Prompt Performance Stability: higher average task performance is strongly associated with lower variance and greater robustness across prompt perturbation. We identify two core linguistic drivers underlying this robustness: (1) Domain-Specific Terminology, which tightly anchors semantic boundaries, and (2…

An anonymous provider has been handing out free access to a frontier-class coding model on OpenRouter Inc. since Aug. 20, and no company has admitted to building it. The model is listed as “Ox Alpha” and costs nothing for input or output tokens. OpenCode, an open-source terminal agent, debuted the model on the same day […] The post Nobody knows who built AI coding model Ox Alpha or where the code goes appeared first on SiliconANGLE.