RunLayer and Rippling Drop Their Lawsuits, But AI Founders Should Take Notes

Slack Turns Group Chats into AI Software Factories with ‘Slack Code’

Slack launched dedicated ‘vibe coding’ channels that let teams build software using AI agents directly inside message threads.

Slack wants developers to build software without ever leaving their group chats.

The messaging giant has launched “Slack Code,” a new feature that adds dedicated “vibe coding” channels directly into the platform. Users can now tag AI coding agents inside any message thread to write software, run tests, and open GitHub pull requests using plain English.

The system turns conversation threads into active development environments.

Engineers simply describe a feature or bug fix in a thread rather than switching back and forth between IDEs, terminal windows, and chat channels. Autonomous AI agents read the discussion context, spin up isolated cloud sandboxes, write the code, and present working preview links. Human developers then inspect the output, request tweaks, and approve the final deployment.

This integration targets the biggest friction point in modern tech: context loss.

Engineering teams make hundreds of critical product decisions inside Slack threads every day. By anchoring AI agents directly to those discussions, Slack eliminates the tedious manual translation between product specifications and code repositories. Non-technical team members can now actively build real code prototypes without opening a local terminal.

Granted, conversational prompts cannot replace rigorous engineering architecture or disciplined code reviews.

AI agents still make mistakes, and human engineers must carefully verify every pull request before merging. But Slack Code fundamentally elevates the chat app from a passive discussion board into an active production tool.

By bringing vibe coding directly into team channels, Slack plans to turn everyday chatter into real, working software.

Cerebras Unveils CS-4 to Challenge NVIDIA’s AI Inference Grip

Cerebras launched its CS-4 server system featuring dinner-plate-sized chips to accelerate AI chatbot responses.

Cerebras Systems wants to control the instant answers generated by AI chatbots.

Cerebras unveiled the CS-4, its newest server platform on Wednesday. The system packs three massive, dinner-plate-sized WSE-3 Turbo chips into a single rack. TSMC builds these giant processors on a 5-nanometer node- with the chips delivering an eye-popping 750 petaflops of AI compute power.

Cerebras targets a crucial phase of AI: inference. It’s what drives live responses in chatbots. Inference demands immediate speed, while training complex models takes months.

Cerebras claims the CS-4 generates text up to 30 times faster than standard GPU clusters. The solution eliminates the data traffic that clogs traditional multi-chip systems by keeping four trillion transistors on single silicon wafers. Custom networking also drops wafer-to-wafer latency down to 2 microseconds.

This strategic pivot hits the mark.

Companies spend billions training AI, but users judge AI on response time. Users leave if a chatbot hesitates. Generating thousands of tokens per second transforms laggy digital assistants into natural conversational partners.

Cerebras still faces tough financial realities. The startup lost $6.9 million last quarter while spending heavily on data center capacity. NVIDIA also maintains a massive moat with its entrenched CUDA software platform.

However, Cerebras presents a compelling challenge to traditional chip design. By bypassing standard hardware bottlenecks, the CS-4 raises the bar for chatbot performance- and forces competitors to accelerate.