🔵 Slack gets 30 New Features at Once

2025-07-07 · Source: Department of Product · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Software Development & Engineering, Emerging Technologies & Innovation · Depth: Intermediate, medium

Summary

Slack has undergone a significant repositioning, introducing over 30 new features and rebranding itself as an "agentic operating system." Key additions include a desktop companion that follows users across applications, meeting intelligence for automated CRM updates and action logging, and AI-skills for standardizing recurring tasks. Slackbot now functions as an MCP client, routing work to 2,600+ connected apps. This update reflects a broader trend of increased release velocity driven by AI, as seen with Claude and Notion. Concurrently, Google's Stitch design agent has gained an "enhance prompt" tool for improving designs and teaching design language. Pinterest saved 7,000 engineering hours monthly by building an MCP ecosystem, and Softr's AI Cobuilder allows for rapid internal tool creation without development. Zapier's CEO unveiled an AI Fluency framework for hiring, and Command Line Interface API requests grew 3.4x from March 2025 to February 2026, indicating a shift in product usage.

Key takeaway

For AI Product Managers navigating rapid feature development, you should prioritize understanding how increased AI-driven velocity impacts user experience and potential feature bloat. Focus on defining concrete evaluation tests (Evals) instead of traditional PRDs to systematically improve product quality and ensure new features genuinely solve user problems, rather than just adding complexity. Monitor API usage trends to identify unmet needs and proactively integrate those solutions into your core product for broader adoption.

Key insights

AI-driven development accelerates feature velocity, transforming platforms into agentic operating systems and necessitating new skill frameworks.

Principles

• AI agents enable rapid prototyping and feature development.
• Centralized platforms can become "agentic operating systems."
• API usage growth requires understanding developer needs.

Method

Product teams can simulate high-stakes meetings using AI personas and agendas. Release notes can be tailored for different audiences using AI prompts. AI can also generate working prototypes from behavioral briefs.

In practice

• Use AI to simulate critical product meetings.
• Employ AI prompts to customize release notes for various stakeholders.
• Explore AI Cobuilders for rapid internal tool development.

Topics

• Agentic Operating Systems
• AI-Powered Feature Development
• Model Context Protocol
• AI Fluency Framework
• Command Line Interface

Best for: AI Product Manager, Product Manager, Software Engineer, Product Designer

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Editorial summary, takeaway, and curation by AIssential. Original article published by Department of Product.