Vibe-Coding an Attention Firewall, w/ Steve Newman, creator of The Curve

2026-04-19 · Source: The Cognitive Revolution · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Software Development & Engineering, Emerging Technologies & Innovation · Depth: Intermediate, extended

Summary

Steve Newman, creator of Writely (which became Google Docs) and founder of the Golden Gate Institute for AI, shares his personal AI toolkit and "vibe-coding" practices in an interview. Newman, a veteran software engineer, details a dozen bespoke applications that have rewired his digital interaction, focusing on managing information overload and regaining focused time. Key tools include an attention firewall for urgent messages, a personal reading app that flags meaningful ideas from newsletters, a dashboard for coding agent status, a Chrome extension for workflow automation, and a universal logging solution for debugging. He emphasizes an "anti-tokenmaxxing" philosophy, prioritizing his time over agent idle time, and discusses his approach to information security and the challenges of integrating with various platforms like WhatsApp and Twitter. The conversation also touches on broader implications of AI for software engineering, climate change, and the mission of the Golden Gate Institute for AI.

Key takeaway

For AI Engineers and Software Developers seeking to optimize personal productivity, consider building custom AI-powered UIs and workflow automations. Focus on creating tools that adapt to your specific needs, rather than conforming to existing SaaS applications. Prioritize robust logging across all components to enable efficient AI-driven debugging, and don't hesitate to iterate rapidly, even if it means doing things "wrong" initially, to discover optimal solutions.

Key insights

Personalized AI toolkits significantly enhance productivity by automating information management and streamlining workflows.

Principles

• Prioritize human time over agent idle time.
• Embrace iterative, "fail fast" development with AI.
• Universal logging is crucial for effective AI debugging.

Method

Develop microservices for AI projects to manage context, use a mono-repo for local code, and integrate diverse data sources via APIs and direct database access, ensuring robust logging for debugging.

In practice

• Build an "attention firewall" to filter urgent communications.
• Create a custom RSS reader for summarized content.
• Implement a dashboard for real-time agent status monitoring.

Topics

• Vibe-Coding
• Personal AI Toolkit
• Attention Firewall
• LLM Summarization
• AI Agent Management

Best for: AI Engineer, Software Engineer, Director of AI/ML

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Editorial summary, takeaway, and curation by AIssential. Original article published by The Cognitive Revolution.