🔥 Node.js Security, and the Latest in Astro & Chrome DevTools

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Daily Issue #131 | Subscribe to DS | Daily Sandbox Pro

Hello Developers!

Engineering teams in 2025 are embracing AI to reshape collaboration and innovation. Keep your Node.js apps secure with npx is-my-node-vulnerable, ensuring your version is free from security risks. Astro 5.2 brings Tailwind 4 and new community tools, while Chrome 133’s DevTools update enhances debugging with persistent AI chat history and performance insights. Plus, learn how View Transitions affect page responsiveness and streamline animations with new snippets.

Dive in and keep coding!

How engineering teams can thrive in 2025 - Engineering teams in 2025 aren’t just adapting to AI—they’re using it to redefine how they build, collaborate, and innovate.

Keep Your Node.js Apps Secure with npx is-my-node-vulnerable - This package compares your Node.js version against the Node.js Security Database, providing immediate feedback about potential security risks.

What's new in Astro - 🚀 Astro 5.2 drops with Tailwind 4 and more, Starlight 0.31 improves search and styling, plus community updates and tools!

View Transitions Snippets - When using View Transitions you’ll notice the page becomes unresponsive to clicks while a View Transition is running.

What's new in DevTools, Chrome 133 - Persistent AI chat history, improved Performance panel with image insights, customizable keyboard navigation, and script ignore lists for cleaner flame charts.

More news here →

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Last week, I recommended Goose, a local AI agent that runs independently. The agent had been created by Jack Dorsey, and as such it peeked my interest to see if it had any value. I spent the weekend testing it, and here’s what I found:

What worked well:

• Easy Setup – Installing the desktop app and connecting it to OpenAI and Anthropic was seamless. I just entered my API keys, and it was ready to go.

• Intuitive Interface – The UI felt smooth and familiar, on par with other AI tools.

• Local File Access – Goose could navigate my local file system (after I set a starting directory) and analyze files on demand.

• Practical Problem-Solving – I had it review a backend file with a broken database query. It quickly identified the issue and suggested a solid fix.

<cfquery datasource="#query.dsn#">
    UPDATE items SET
    privacy_id = <cfqueryparam value ="#arguments.privacy_id#" cfsqltype="bigint">
    WHERE (id = <cfqueryparam value="#arguments.item_id#" cfsqltype="bigint">)
    ;
</cfquery>

The above query did not have <cfqueryparam> tags and thuse was vulnarable to SQL injections.

What did not work well:

• Despite its strengths, Goose—like all AI tools today—still lacks the ability to analyze an entire project holistically. This would be a game-changer, especially for workflows that span frontend to backend development.

• Another limitation is that the LLM itself isn’t running locally, making it nearly impossible to train it on custom data effectively. True local training would unlock far more powerful use cases.

I'll be diving deeper into Goose this week and will share my findings by the end of the week. Stay tuned!

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