Steve Newman, creator of Writely and founder of the Golden Gate Institute for AI, shares the personal AI toolkit and vibe-coding practices that have reshaped how he works. He walks through bespoke tools including an attention firewall, a reading app for surfacing new ideas, a coding-agent dashboard, workflow automations, and a universal logging system for debugging with Claude. They also discuss information security, mobile and voice workflows, Steve’s “anti-tokenmaxxing” philosophy, and his views on AI takeoff, robotics, and climate change.
Google: Try Gemini’s Nano Banana image generation model in Google AI Studio or the Gemini app to create custom illustrated worksheets in seconds, and explore the app’s quizzes and guided learning features.
Sponsors:
AvePoint:
AvePoint is building the control layer for AI agents so you can securely govern, audit, and recover every action at scale. Design trusted agentic outcomes from day one at https://avpt.co/tcr
VCX:
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Claude:
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Tasklet:
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CHAPTERS:
(00:00) About the Episode
(03:25) Special Sponsor
(04:47) Building personal productivity tools (Part 1)
(14:23) Sponsors: AvePoint | VCX
(16:45) Building personal productivity tools (Part 2)
(17:32) Security tradeoffs and caution
(26:00) Touring the custom toolkit (Part 1)
(26:05) Sponsors: Claude | Tasklet
(29:56) Touring the custom toolkit (Part 2)
(38:01) Stack choices and dashboards
(45:12) Hooks, repos, and syncing
(58:08) Logging, agents, and tools
(01:11:18) Hard parts and iteration
(01:18:57) Mobile workflows and UIs
(01:26:19) AI-era engineering changes
(01:35:54) Software jobs outlook
(01:41:35) Thresholds, Mythos, and RSI
(01:57:07) AI and climate
(02:01:37) Golden Gate mission
(02:07:50) Episode Outro
(02:12:01) Outro
PRODUCED BY:
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Nathan Labenz discusses the latest developments in California's AI bill SB 1047 with experts Nathan Calvin, Dean W. Ball, and Steve Newman. In this episode of The Cognitive Revolution, we explore the updated version of the bill, its implications for frontier AI companies, and the debate surrounding its potential impact. Join us for an insightful analysis of this crucial legislation and its role in shaping AI governance.
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CHAPTERS:
(00:00:00) About the Show
(00:00:22) Sponsor: WorkOS
(00:01:22) About the Episode
(00:07:03) Introduction and Recap of SB 1047
(00:13:40) Key Changes and Current Status of SB 1047
(00:19:51) Sponsors: Oracle | Brave
(00:21:55) Dean's Perspective on SB 1047
(00:33:30) Sponsors: Omneky | Squad
(00:35:16) Steve's AI Sensemaking Project
(00:39:03) Differing Views on AI Regulation Necessity
(00:46:34) Nathan's Case for SB 1047
(00:55:07) Dean's Response and Liability Concerns
(01:10:48) Potential Scenarios and Impacts of SB 1047
(01:29:29) Final Thoughts and Predictions on SB 1047
(01:38:16) Closing Remarks on AI Policy Challenges
(01:39:51) Outro
Dive into the nuanced debate over California's SB 1047 AI legislation with Nathan Calvin, Dean Ball, and Steve Newman. Our expert panel discussion explores the bill's intent, dispels misconceptions, and debates its potential impact on technology and regulation. Learn about AI's tail risks, the role of government, and hear suggestions for improving the legislation. Share your thoughts and join the conversation around shaping a positive AI future.
You can reach out and share your thoughts by using the contact form here : https://www.cognitiverevolution.ai/contact/
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SPONSORS:
The Brave search API can be used to assemble a data set to train your AI models and help with retrieval augmentation at the time of inference. All while remaining affordable with developer first pricing, integrating the Brave search API into your workflow translates to more ethical data sourcing and more human representative data sets. Try the Brave search API for free for up to 2000 queries per month at https://bit.ly/BraveTCR
Omneky is an omnichannel creative generation platform that lets you launch hundreds of thousands of ad iterations that actually work customized across all platforms, with a click of a button. Omneky combines generative AI and real-time advertising data. Mention "Cog Rev" for 10% off https://www.omneky.com/
Head to Squad to access global engineering without the headache and at a fraction of the cost: head to https://choosesquad.com/ and mention "Turpentine" to skip the waitlist.
CHAPTERS:
(00:00:00) Introduction
(00:05:45) Opinions
(00:11:57) The Bill
(00:17:05) Elevated discussion
(00:18:51) Sponsors: Brave | Omneky
(00:20:18) AI Doctor
(00:22:55) Centralized Regulator
(00:26:29) SB 1047
(00:27:47) Critical infrastructure
(00:31:51) Should we regulate?
(00:39:00) Sponsors: Squad
(00:40:28) Safety standards for training
(00:46:09) What is 10^26 flops?
(00:52:10) Regulating general purpose technology
(00:53:42) AI regulation
(00:58:31) Societal adaptation
(01:01:18) AI safety
(01:04:20) AI regulations
(01:07:19) The current state of the industry
(01:10:08) What industry wants changed
(01:25:42) Safety is hard to legislate
(01:33:06) How to decide the trajectory of AI?
(01:45:52) Testing, Transparency, Whistleblower Provision
(01:55:17) Closing thoughts
Steve Newman is the Founder & CEO @ Scalyr, the startup that helps your devops team solve more problems in less time with log monitoring and analysis in seconds. Steve has raised over $27.5m in funding with Scalyr from many friends of the show including Susa Ventures, Bloomberg Beta, Shasta and GV. As for Steve, prior to Scalyr, he was the Founder of Writely which was acquired by Google to become the little known, Google Docs. Before that he founded 2 prior startups, Ann Arbour Softworks (acq by Ashton-Tate) and BitCraft (acquired by Macromedia). If that was not enough, Steve also sat on the Technical Advisory Board at Box for over 3 years.
In Today's Episode We Discuss:
How Steve made his way into the world of startups and SaaS over 30 years ago? What is the founding story with Scalyr and what was that a-ha moment?
Why does Steve believe that you should involve customers very early in the process of developing your narrative? Where does Steve see most startups go wrong when it comes to messaging? How does one structure the feedback mechanism? How does one determine between feedback you integrate and feedback you do not?
Why does Steve believe that you should not focus too much on numbers in the early days? What makes them deceiving at this stage? If not numbers, what should early stage founders be focusing on and measuring? Why does Steve believe that ARR is not the leading metric? What metrics should early stage SaaS founders really be prioritising?
How does Steve respond to PG's "to scale, you have to do unscalable things"? What challenges and nuance does Steve present that founders must be wary of? How does Steve's thinking here affect his view towards customisation? Why does manual input not put a cap on scalability? What are the parameters for manual involvement to be scalable?
Steve's 60 Second SaaStr:
What does Steve know now that he wishes he had known at the beginning?
Who does Steve believe is crushing it in the world of SaaS today?
The hardest element about the move from tech co-founder to CEO?
Read the full transcript on our blog.
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