{{first_name | Leader}}, welcome back.
Coding agents, enterprise playbooks, AI jobs, and tools that benefit your everyday workflows.
These are today's updates.
See how startups automate compliance with AI, powered by Vanta*
Meta enters the AI coding race.
Google reshuffles AI leadership while cloud demand surges.
Google Maps becomes more agentic.
Funding, jobs, and enterprise AI resources
Plus the winning prompt: AI department productivity audit ⬇️
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. Top News.
Meta released its first AI coding agent, Muse Code, in beta this week. It's built by AI chief Alexandr Wang's team and runs on Muse Spark 1.2, a coding-focused model version released alongside it. The agent plans changes, writes code, and validates results across large repos, just like Claude Code and Codex.
Wang said Meta is trying to win on price, with pay-as-you-go rates similar to Muse Spark 1.1's API pricing. Zuckerberg posted about the release directly on X, calling it a "terminal coding agent" for "complete software engineering tasks."
The launch comes right after Meta's stock took a hit from a light revenue forecast and shrinking free cash flow, so this is also Zuckerberg trying to show something for all that AI spending. Capex guidance for the year is now $134-145 billion.
Jeff Dean, Google's chief scientist and a 27-year veteran, is leaving to start his own company, Discovery Loop, focused on AI for science and engineering. Demis Hassabis is also stepping back from running DeepMind day-to-day, moving into a chairman role, with Koray Kavukcuoglu taking over as head of the AI division and leading Gemini 4.
Alphabet's stock dropped 4% on the news. It comes right after Google reported 82% growth in cloud revenue for the quarter, so investors are getting a strong cloud story and a leadership shakeup at the same time.
Some researchers inside Google are reportedly frustrated that they aren’t getting enough computing capacity for their own projects, while Google Cloud sells TPUs to outside customers, including Anthropic. Dean's departure is described as friendly, and Google is investing in his new startup.
Google is rolling out new agentic features in Ask Maps, its AI assistant inside Google Maps. You can ask something like "where can I get vegan avocado toast near home" and it'll pull up restaurants, then let you place the order through partners like Square or Toast (Uber Eats is coming soon).
The same tool can now search for hotels using natural-language criteria (budget, vibe, distance from the gym) and compare prices and availability before sending you to the partner site to book. It also identifies and informs about local events like comedy shows or concerts, with links to buy tickets.
Google's also adding Personal Intelligence, an opt-in feature that connects Ask Maps to your Gmail so it can factor in things like upcoming flights automatically. Food ordering and hotel search are rolling out in the US first, while other features like the live transit widget are going out to over 150 countries.
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. Market.
Funding
Valar Atomics raised $1B to mass-produce nuclear reactors for AI data centres
Sylebra Capital raised $277M to back high-growth public technology companies
Roles In AI
Manager, Data Analytics at headspace
Resident Solutions Architect at Glean
Socials
. Prompt of the Day.
AI Department Productivity Audit
When to use this?
When you want to identify manual tasks that are slowing your department and identify where AI can deliver the biggest productivity gains.
You are an enterprise operations consultant specializing in AI transformation. Help me audit my team's workflows to identify where AI can improve productivity, reduce manual work, and shorten decision cycles.
Start by asking me about:
My department and primary responsibilities
The recurring tasks my team performs daily, weekly, and monthly
The software stack we use
Team size and roles
Current bottlenecks, delays, and repetitive work
Then create a table with:
Workflow or task
Time spent per week
Pain points
AI opportunity
Recommended tools or agents
Estimated hours saved
Implementation difficulty (Low/Medium/High)
Expected business impact
Finally:
Rank the top five highest-ROI AI opportunities.
Suggest a 30-day implementation roadmap.
Highlight quick wins that require little or no engineering support.
Flag any governance, security, or compliance considerations before deployment.
Estimate the potential productivity gains for the department if these recommendations are implemented.P.S. Get more such prompts in the Prompting Playbook (free for you)
Stay curious, {{first_name | leaders}}
PS. If you missed the last issue, you can find it here.