
Slack has launched a new feature called Slack Code, which allows teams to collaborate on coding projects with AI agents in dedicated channels. Users can tag AI agents such as Anthropic's Claude or Cognition's Devin to assist with tasks, providing real-time code comparisons and HTML previews. The channels automatically archive upon task completion, offering an efficient way to manage coding projects. Available on all Slack plans, this feature integrates with AI agents from Slack's marketplace, aiming to enhance team collaboration and productivity.
Read originalEarlier coverage that leads up to this article, and what followed. Lines connect each piece to the closest one after it, converging here.
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Slack introduces collaborative vibe-coding channels
5 developments
© The Verge AIOpenAI is shifting ChatGPT from a static text stream to an interactive interface by integrating visuals and tools directly into responses. This Intelligent UI feature, powered by the new GPT-6 models, allows users to engage with diagrams, calculators, and games without leaving the chat window. The update prioritizes utility over pure conversation, enabling tasks like retirement planning or learning Mahjong through in-line interactive elements. While Plus and Pro users get the more capable Sol model, free users receive the efficient Luna variant, making this a broad consumer-facing upgrade rather than a niche developer tool.
© The Verge AIThe Surface Laptop Ultra marks the commercial debut of Nvidia’s RTX Spark, an Arm-based chip designed to bring serious local AI inference to Windows laptops. Starting at $2,599, this device signals a shift toward premium hardware capable of running large models locally, moving beyond cloud dependency for enterprise and creative workflows. Microsoft pairs this with 'Hybrid Intelligence' features in Copilot, allowing the agent to access local files and take OS-level actions like filing taxes or managing emails. This isn't just a new laptop; it's the first concrete proof that Arm-based PC silicon can handle the thermal and memory demands of 120B+ parameter models on-device.
© The Verge AIMicrosoft is shifting Copilot from a chat interface to an active agent capable of manipulating local files and system settings. The new 'Hybrid Intelligence' approach combines cloud reasoning with local execution, allowing the AI to search folders, rename documents, and draft emails without leaving the desktop environment. This moves beyond simple text generation into tangible OS-level automation, effectively turning Copilot into a personal assistant that can handle multi-step workflows like tax filing preparation. The capability arrives over the next few months, marking a significant step toward autonomous desktop agents.
© GitHub ChangelogGitHub is replacing its regex-based secret scanning with a purpose-built AI model that understands code context to catch unstructured credentials like passwords without standard token formats. This shift moves security from pattern matching to semantic understanding, catching leaks that traditional tools miss before they hit repository history via push protection. The upgrade is automatic for existing GHSP/GHAS customers, but new opt-in features in Copilot and push protection will consume AI Credits, introducing a usage-based cost layer to what was previously free. This marks a significant pivot in how developers handle security, blending LLM capabilities directly into the CI/CD pipeline.
© GitHub ChangelogGitHub Copilot finally addresses the security risks of autonomous coding by introducing local sandboxing across its CLI, app, and VS Code extensions. Powered by Microsoft’s MXC technology, this feature creates a strict execution boundary that restricts agent access to files, networks, and credentials based on developer-defined policies. This is a critical step for enterprise adoption, allowing organizations to enforce security controls without blocking the utility of agentic workflows. It shifts Copilot from a passive assistant to a controlled autonomous actor with clear operational limits.
© GitHub ChangelogGitHub finally bridges the gap between cloud-heavy Copilot and local inference by letting the CLI discover models from a running Ollama instance. Version 1.0.94-0 introduces a /model command that surfaces supported local weights alongside cloud options, allowing developers to switch contexts without restarting the session. This isn't just a toggle; it requires tool calling and streaming support, forcing a quality baseline for local providers. The move signals GitHub's recognition that enterprise workflows increasingly demand hybrid setups where sensitive code stays on-prem while general assistance remains in the cloud.