Stay ConnectedThe Every Podcast is Every’s flagship show. Co-hosts Dan Shipper and Natalia Quintero talk with founders, researchers, writers, and operators about what they’re building and how they use AI in their own work. The show also takes you behind the scenes at Every. We share how our team is using and exploring AI, including what we’re trying, what’s working, and what we’re learning along the way.
Formerly known as AI & I.
Read more at every.to.
Copyright: © Dan Shipper
This episode contains sponsored content in partnership with Salesforce.
At Dreamforce 2025, Every CEO Dan Shipper sat down with Silvio Savarese, chief AI scientist at Salesforce, to discuss how one of the world’s largest software companies is shaping the future of AI for the enterprise.
Together, Dan and Savarese explore how his team at Salesforce develops AI solutions that now power more than 13,000 businesses—including OpenAI, Dell, and FedEx—helping them become truly Agentic Enterprises that operate with greater scale, speed, and precision. Examples include a large language model built for Salesforce developers years before ChatGPT’s release, and Agentforce, the company’s agentic layer that enables a hybrid future of work where humans and AI agents collaborate to achieve more than either could alone.
They also discuss how Agentforce gives enterprises a deeply unified AI platform that connects their data with agent functionality—making it both powerful and practical. The conversation touches on how Salesforce builds trust with enterprise customers amid the jagged frontier of AI by ensuring consistency in results, while continuing to push the boundaries of what agents can do autonomously. Savarese shares how enterprise-grade simulation environments help them strike that balance, and reflects on how AI agents will ultimately transform how businesses and individuals alike get things done.
@Salesforce #SalesforcePartner #DF25
Want even more? Sign up for Every to unlock our ultimate guide to prompting ChatGPT here: https://every.ck.page/ultimate-guide-to-prompting-chatgpt. It’s usually only for paying subscribers, but you can get it here for free.
To hear more from Dan Shipper: Subscribe to Every: https://every.to/subscribe Follow him on X: https://twitter.com/danshipper
Timestamps:
00:00 – Start
01:16 – Inside Salesforce’s early AI innovations
02:50 – How Agentforce works and what it can do
07:03 – The real challenges of deploying AI at scale
08:57 – Why Salesforce builds simulation environments for AI
12:35 – The future of agents and enterprise AI
This episode contains sponsored content in partnership with Salesforce.
At Dreamforce 2025, Every CEO Dan Shipper sat down with Silvio Savarese, chief AI scientist at Salesforce, to discuss how one of the world’s largest software companies is shaping the future of AI for the enterprise.
Together, Dan and Savarese explore how his team at Salesforce develops AI solutions that now power more than 13,000 businesses—including OpenAI, Dell, and FedEx—helping them become truly Agentic Enterprises that operate with greater scale, speed, and precision. Examples include a large language model built for Salesforce developers years before ChatGPT’s release, and Agentforce, the company’s agentic layer that enables a hybrid future of work where humans and AI agents collaborate to achieve more than either could alone.
They also discuss how Agentforce gives enterprises a deeply unified AI platform that connects their data with agent functionality—making it both powerful and practical. The conversation touches on how Salesforce builds trust with enterprise customers amid the jagged frontier of AI by ensuring consistency in results, while continuing to push the boundaries of what agents can do autonomously. Savarese shares how enterprise-grade simulation environments help them strike that balance, and reflects on how AI agents will ultimately transform how businesses and individuals alike get things done.
@Salesforce #SalesforcePartner #DF25
Want even more? Sign up for Every to unlock our ultimate guide to prompting ChatGPT here: https://every.ck.page/ultimate-guide-to-prompting-chatgpt. It’s usually only for paying subscribers, but you can get it here for free.
To hear more from Dan Shipper: Subscribe to Every: https://every.to/subscribe Follow him on X: https://twitter.com/danshipper
Timestamps:
00:00 – Start
01:16 – Inside Salesforce’s early AI innovations
02:50 – How Agentforce works and what it can do
07:03 – The real challenges of deploying AI at scale
08:57 – Why Salesforce builds simulation environments for AI
12:35 – The future of agents and enterprise AI
At Every, the team credits Claude Code with transforming the way they work.
They now ship to codebases they barely know, each new feature makes the next easier to build, and even non-technical teammates confidently use the terminal.
To explore how this happened, AI & I host Dan Shipper invited Claude Code’s creators—Cat Wu (@_catwu) and Boris Cherny (@bcherny) from Anthropic AI—to discuss what they’ve learned from building one of the most beloved AI engineering tools in the world.
This episode is a must-watch for anyone—technical or not—who wants to understand how to use Claude Code like the people who built it.
If you found this episode interesting, please like, subscribe, comment, and share.
Want even more?Sign up for Every to unlock our ultimate guide to prompting ChatGPT here: https://every.ck.page/ultimate-guide-to-prompting-chatgpt. It’s usually only for paying subscribers, but you can get it here for free.
To hear more from Dan Shipper:Subscribe to Every: https://every.to/subscribeFollow him on X: https://twitter.com/danshipper
Build your first AI-powered app at ai.studio/build.
Timestamps:
00:00:00 - Start
00:01:26 - Introduction
00:02:25 - Claude Code’s origin story
00:07:03 - How Anthropic dogfoods Claude Code
00:14:06 - Boris and Cat’s favorite slash commands
00:15:49 - How Boris uses Claude Code to plan feature development
00:21:53 - Everything Anthropic has learned about using sub-agents well
00:26:16 - Use Claude Code to turn past code into leverage
00:33:14 - The product decisions for building an agent that’s simple and powerful
00:36:38 - Making Claude Code accessible to the non-technical user
00:45:12 - The next form factor for coding with AI
Links to resources mentioned in the episode:
At Every, the team credits Claude Code with transforming the way they work.
They now ship to codebases they barely know, each new feature makes the next easier to build, and even non-technical teammates confidently use the terminal.
To explore how this happened, AI & I host Dan Shipper invited Claude Code’s creators—Cat Wu (@_catwu) and Boris Cherny (@bcherny) from Anthropic AI—to discuss what they’ve learned from building one of the most beloved AI engineering tools in the world.
This episode is a must-watch for anyone—technical or not—who wants to understand how to use Claude Code like the people who built it.
If you found this episode interesting, please like, subscribe, comment, and share.
Want even more?
Sign up for Every to unlock our ultimate guide to prompting ChatGPT here: https://every.ck.page/ultimate-guide-to-prompting-chatgpt. It’s usually only for paying subscribers, but you can get it here for free.
To hear more from Dan Shipper:
Subscribe to Every: https://every.to/subscribe
Follow him on X: https://twitter.com/danshipper
Build your first AI-powered app at [ai.studio/build](http://ai.studio/build).
Timestamps:
00:00:00 - Start
00:01:26 - Introduction
00:02:25 - Claude Code’s origin story
00:07:03 - How Anthropic dogfoods Claude Code
00:14:06 - Boris and Cat’s favorite slash commands
00:15:49 - How Boris uses Claude Code to plan feature development
00:21:53 - Everything Anthropic has learned about using sub-agents well
00:26:16 - Use Claude Code to turn past code into leverage
00:33:14 - The product decisions for building an agent that’s simple and powerful
00:36:38 - Making Claude Code accessible to the non-technical user
00:45:12 - The next form factor for coding with AI
Links to resources mentioned in the episode:
- Cat Wu: https://x.com/_catwu
- Boris Cherny: https://x.com/bcherny
- Claude Code: https://www.claude.com/product/claude-code
Good writing has always been downstream of good thinking. The average language model can help you write faster—but can it help you think better?
Danny Aziz wrestled with this question while building the new version of Spiral, an AI writing partner informed by our editorial taste at Every that launched yesterday.
The result is a product—and a philosophy—built by the ultimate craftsman who believes you can lean into AI without blunting your edge with slop. We had Danny on AI & I to talk about using AI without losing your craft. We get into the hidden alpha in AI tools that slow you down, how to code with AI without losing your craft, and everything Danny learned about cajoling AI to write well.
If you found this episode interesting, please like, subscribe, comment, and share!
Want even more?
Sign up for Every to unlock our ultimate guide to prompting ChatGPT here: https://every.ck.page/ultimate-guide-to-prompting-chatgpt. It’s usually only for paying subscribers, but you can get it here for free.
To hear more from Dan Shipper:
Ready to build a site that looks hand-coded—without hiring a developer? Launch your site for free at Framer.com, and use code DAN to get your first month of Pro on the house.
Timestamps:
00:00:00 – Start
00:01:00 – Introduction
00:05:26 – How Danny used Spiral to prepare for this podcast
00:08:29 – Why slowing down makes AI writing better
00:13:42 – The agents working under the hood for Spiral
00:14:46 – How Spiral helps you explore the canvas of possibilities
00:24:41 – Why Danny pivoted away from the old version of Spiral
00:31:51 – How to use AI without losing your craft
00:34:55 – Danny’s workflow for building Spiral as a solo engineer
00:40:39 – Code with AI while staying in control
00:45:26 – What Danny learned about getting AI to write well
00:47:52 – How Danny used DSPy to give AI taste
00:56:16 – Dan v. AI Dan: Can the machine match the man?
Links to resources mentioned in the episode:
This episode is a little different from our usual fare: It’s a conversation with our head of AI training Alex Duffy about Good Start Labs, a company he incubated inside Every. Today, Good Start Labs is spinning out of Every as a separate company with $3.6 million in funding from General Catalyst, Inovia, Every, and a group of angel investors from top-tier AI labs like DeepMind. We get into how Alex learned some of his biggest lessons about the real world from games, starting with RuneScape, which taught him how markets work and how not to get scammed. He explains why the static benchmarks we use to evaluate LLMs today are breaking down, and how games like Diplomacy offer a richer, more dynamic way to test and train large language models. Finally, Alex shares where he sees the most promise in AI—software, life sciences, and education—and why he believes games can make the models we use smarter, while helping people understand and use AI more effectively.
If you found this episode interesting, please like, subscribe, comment, and share.
Want even more?
Sign up for Every to unlock our ultimate guide to prompting ChatGPT here: https://every.ck.page/ultimate-guide-to-prompting-chatgpt. It’s usually only for paying subscribers, but you can get it here for free.
To hear more from Dan Shipper:
Timestamps
00:00:00 - Start
00:01:48 - Introduction
00:04:14 - Why evals and benchmarks are broken
00:07:13 - The sneakiest LLMs in the market
00:13:00 - A competition that turns prompting into a sport
00:15:49 - Building a business around using games to make AI better
00:22:39 - Can language models learn how to be funny
00:25:31 - Why games are a great way to evaluate and train new models
00:26:58 - What child psychology tells us about games and AI
00:30:10 - Using games to unlock continual learning in AI
00:36:42 - Why Alex cares deeply about games
00:44:37 - Where Alex sees the most promise in AI
00:50:54 - Rethinking how young people start their careers in the age of AI
Links to resources mentioned in the episode:
This episode is a little different from our usual fare: It’s a conversation with our head of AI training Alex Duffy about Good Start Labs, a company he incubated inside Every. Today, Good Start Labs is spinning out of Every as a separate company with $3.6 million in funding from General Catalyst, Inovia, Every, and a group of angel investors from top-tier AI labs like DeepMind. We get into how Alex learned some of his biggest lessons about the real world from games, starting with RuneScape, which taught him how markets work and how not to get scammed. He explains why the static benchmarks we use to evaluate LLMs today are breaking down, and how games like Diplomacy offer a richer, more dynamic way to test and train large language models. Finally, Alex shares where he sees the most promise in AI—software, life sciences, and education—and why he believes games can make the models we use smarter, while helping people understand and use AI more effectively.
If you found this episode interesting, please like, subscribe, comment, and share.
Want even more?
Sign up for Every to unlock our ultimate guide to prompting ChatGPT here: https://every.ck.page/ultimate-guide-to-prompting-chatgpt. It’s usually only for paying subscribers, but you can get it here for free.
To hear more from Dan Shipper:
Timestamps
00:00:00 - Start
00:01:48 - Introduction
00:04:14 - Why evals and benchmarks are broken
00:07:13 - The sneakiest LLMs in the market
00:13:00 - A competition that turns prompting into a sport
00:15:49 - Building a business around using games to make AI better
00:22:39 - Can language models learn how to be funny
00:25:31 - Why games are a great way to evaluate and train new models
00:26:58 - What child psychology tells us about games and AI
00:30:10 - Using games to unlock continual learning in AI
00:36:42 - Why Alex cares deeply about games
00:44:37 - Where Alex sees the most promise in AI
00:50:54 - Rethinking how young people start their careers in the age of AI
Links to resources mentioned in the episode:
Aaron Levie is AI-pilled, but he’s one of the few CEOs who sees a future where AI agents work for us, instead of replacing us—helping us to do more than we could before.
Aaron’s been the CEO of Box for 20 years–long enough to see a few tech revolutions up close—and taking the company AI-first gave him a glimpse of what the next one means for us. We get into why jobs aren’t going away, the new shape of work, and what it takes to build an AI-first company from the inside.
If you found this episode interesting, please like, subscribe, comment, and share.
Want even more?
Sign up for Every to unlock our ultimate guide to prompting ChatGPT here: https://every.ck.page/ultimate-guide-to-prompting-chatgpt. It’s usually only for paying subscribers, but you can get it here for free.
To hear more from Dan Shipper:
Meet NotebookLM, the AI research tool and thinking partner that can analyze your sources, turn complexity into clarity and transform your content: https://notebooklm.google.com/
Timestamps:
00:00:00 - Start
00:01:30 – Introduction
00:02:36 – Why AI won’t take your job
00:06:42 – Jevons Paradox and the future of work
00:10:40 – How Aaron’s experience with the cloud era shapes his view of AI
00:19:44 – Why every knowledge worker is becoming a manager of AI agents
00:25:21 – What Aaron’s learned from bringing AI into every corner of Box
00:33:57 – What’s overhyped in AI today
00:43:31 – How Aaron balances everyday execution with innovation
Links to resources mentioned in the episode:
Aaron Levie is AI-pilled, but he’s one of the few CEOs who sees a future where AI agents work for us, instead of replacing us—helping us to do more than we could before.
Aaron’s been the CEO of Box for 20 years–long enough to see a few tech revolutions up close—and taking the company AI-first gave him a glimpse of what the next one means for us. We get into why jobs aren’t going away, the new shape of work, and what it takes to build an AI-first company from the inside.
If you found this episode interesting, please like, subscribe, comment, and share.
Want even more?
Sign up for Every to unlock our ultimate guide to prompting ChatGPT here: https://every.ck.page/ultimate-guide-to-prompting-chatgpt. It’s usually only for paying subscribers, but you can get it here for free.
To hear more from Dan Shipper:
Meet NotebookLM, the AI research tool and thinking partner that can analyze your sources, turn complexity into clarity and transform your content: https://notebooklm.google.com/
Timestamps:
00:00:00 - Start
00:01:30 – Introduction
00:02:36 – Why AI won’t take your job
00:06:42 – Jevons Paradox and the future of work
00:10:40 – How Aaron’s experience with the cloud era shapes his view of AI
00:19:44 – Why every knowledge worker is becoming a manager of AI agents
00:25:21 – What Aaron’s learned from bringing AI into every corner of Box
00:33:57 – What’s overhyped in AI today
00:43:31 – How Aaron balances everyday execution with innovation
Links to resources mentioned in the episode:
If your MCP server has dozens of tools, it’s probably built wrong.
You need tools that are specific and clear for each use case—but you also can’t have too many. This creates an almost impossible tradeoff that most companies don’t know how to solve.
That’s why we interviewed Alex Rattray, the founder and CEO of Stainless. Stainless builds APIs, SDKs, and MCP servers for companies like OpenAI and Anthropic. Alex has spent years mastering how to make software talk to software, and he came on the show to share what he knows. We get into MCP and the future of the AI-native internet.
If you found this episode interesting, please like, subscribe, comment, and share.
Want even more?
Sign up for Every to unlock our ultimate guide to prompting ChatGPT here: https://every.ck.page/ultimate-guide-to-prompting-chatgpt. It’s usually only for paying subscribers, but you can get it here for free.
To hear more from Dan Shipper:
Ready to build a site that looks hand-coded—without hiring a developer? Launch your site for free at Framer.com, and use code DAN to get your first month of Pro on the house.
Timestamps:
00:00:00 - Start
00:01:14 - Introduction
00:02:54 - Why Alex likes running barefoot
00:05:09 - APIs and MCP, the connectors of the new internet
00:10:53 - Why MCP servers are hard to get right
00:20:07 - Design principles for reliable MCP servers
00:23:50 - Scaling MCP servers for large APIs
00:25:14 - Using MCP for business ops at Stainless
00:28:12 - Building a company brain with Claude Code
00:33:59 - Where MCP goes from here
00:41:10 - Alex’s take on the security model for MCP
Links to resources mentioned in the episode:
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