🔵 OpenAI and Google reveal new Workspace Agents and Shopify's CEO teases "the start of something really big"

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

Summary

OpenAI and Google have introduced new workplace AI agents designed to automate complex, recurring tasks for product teams. Google's Workspace Intelligence unifies scattered data across Workspace apps and external tools like Asana and Salesforce, enabling features such as custom interactive visualizations in Sheets and automated multi-step tasks. OpenAI's agents, powered by Codex, allow teams to build custom workflows for tasks like lead qualification or product feedback analysis, integrating with business tools and taking direct actions. Concurrently, Perplexity released its local "Personal Computer" AI, Figma enhanced mobile prototyping, and Claude expanded its connectors to over 200 services. Shopify's CEO teased a future web experience with AI-generated, image-based pages, while data indicates mixed internal AI adoption at Google, a surge in AI-generated scam ads, and a shift towards outcome-based pricing for enterprise AI solutions like Adobe's CX Enterprise AI suite.

Key takeaway

For Product Managers evaluating new tools to enhance team efficiency, consider integrating AI agents from Google or OpenAI to automate repetitive tasks like sprint planning, lead qualification, or product feedback analysis. These agents can significantly reduce manual effort and context switching, freeing your team to focus on strategic initiatives. Prioritize solutions that offer robust integration with your existing tech stack and support outcome-based metrics to align with evolving pricing models.

Key insights

AI agents are transforming workplace productivity by automating complex, multi-step workflows across diverse applications and data sources.

Principles

• AI agents reduce context switching.
• Outcome-based pricing for AI is emerging.
• AI can generate web experiences on demand.

Method

Define a recurring team workflow, then use an AI agent platform (e.g., ChatGPT) to guide the agent's setup, tool access, approval processes, and context retention for automated execution.

In practice

• Use Claude Code to onboard new codebases.
• Explore Extra for email management.
• Design financial models for outcome-based pricing.

Topics

• Workspace Agents
• Generative AI
• Product Management Tools
• AI Adoption
• Outcome-Based Pricing

Best for: Product Manager, CTO, VP of Engineering/Data, AI Product Manager, Director of AI/ML, Product Designer

Related on AIssential

• 😺 LIVE NOW: Learn Workspace Agents 101 (Build, Run, & Scale) — OpenAI's new Workspace Agents offer cloud-based, action-oriented AI integration for enterprise tools, replacing Custom GPTs.
• More than chatbots: why business AI agents are Big Tech’s next product battleground — AI agents are becoming a critical battleground for Big Tech, shifting platforms from attention capture to transactional mediation.
• 🗞️ Google brought AI agents into the planet’s biggest application, Google Map. — AI integration is transforming major applications and development workflows, driving demand for specialized engineering skills.
• How AI Agents Reshape Knowledge Work: Autonomy, Efficiency, and Scope — AI agents, by automating multi-step execution, dramatically boost efficiency and expand the scope of complex, cross-domain knowledge work.
• Peter Yang on Small Teams, Coding Agents, and Why Human Ambition Has No Ceiling — AI agents are transforming software interaction and development, enabling radically smaller teams and automating knowledge work through conversational interfaces.
• 🗞️ OpenAI’s new paper shows how they are now seeing the first version of office work where agents do most of the execution. — AI agents are transforming work and driving economic growth, yet human-AI collaboration and infrastructure remain critical bottlenecks.

Open in AIssential →

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