How Salesforce Is Using AI to Power the Enterprise

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 #DF25Want 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/danshipperTimestamps:00:00 – Start01:16 – Inside Salesforce’s early AI innovations02:50 – How Agentforce works and what it can do07:03 – The real challenges of deploying AI at scale08:57 – Why Salesforce builds simulation environments for AI12:35 – 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/danshipperBuild your first AI-powered app at [ai.studio/build](http://ai.studio/build).Timestamps: 00:00:00 - Start00:01:26 - Introduction00:02:25 - Claude Code’s origin story00:07:03 - How Anthropic dogfoods Claude Code00:14:06 - Boris and Cat’s favorite slash commands00:15:49 - How Boris uses Claude Code to plan feature development00:21:53 - Everything Anthropic has learned about using sub-agents well00:26:16 - Use Claude Code to turn past code into leverage00:33:14 - The product decisions for building an agent that’s simple and powerful00:36:38 - Making Claude Code accessible to the non-technical user00:45:12 - The next form factor for coding with AILinks 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:Subscribe to Every: https://every.to/subscribe Follow him on X: https://twitter.com/danshipper 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 – Start00:01:00 – Introduction00:05:26 – How Danny used Spiral to prepare for this podcast00:08:29 – Why slowing down makes AI writing better00:13:42 – The agents working under the hood for Spiral00:14:46 – How Spiral helps you explore the canvas of possibilities00:24:41 – Why Danny pivoted away from the old version of Spiral00:31:51 – How to use AI without losing your craft00:34:55 – Danny’s workflow for building Spiral as a solo engineer00:40:39 – Code with AI while staying in control00:45:26 – What Danny learned about getting AI to write well00:47:52 – How Danny used DSPy to give AI taste00:56:16 – Dan v. AI Dan: Can the machine match the man?Links to resources mentioned in the episode:Danny Aziz: Danny Aziz (@DannyAziz97) / X Give Spiral a go: Spiral The article Every published about DSPy: I’ve Stopped Writing Prompts—DSPy Does It Better  

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:Subscribe to Every: https://every.to/subscribeFollow him on X: https://twitter.com/danshipperTimestamps00:00:00 - Start00:01:48 - Introduction00:04:14 - Why evals and benchmarks are broken00:07:13 - The sneakiest LLMs in the market00:13:00 - A competition that turns prompting into a sport00:15:49 - Building a business around using games to make AI better00:22:39 - Can language models learn how to be funny00:25:31 - Why games are a great way to evaluate and train new models00:26:58 - What child psychology tells us about games and AI00:30:10 - Using games to unlock continual learning in AI00:36:42 - Why Alex cares deeply about games00:44:37 - Where Alex sees the most promise in AI00:50:54 - Rethinking how young people start their careers in the age of AILinks to resources mentioned in the episode:Alex Duffy: alex duffy (@alxai_)Good Start Labs: https://goodstartlabs.com/, good start (@goodstartlabs)The book Alex is reading about the importance of games: Playing with Reality: How Games Shape Our WorldThe book Dan recommends by the psychoanalyst D.W. Winnicott: Playing and Reality

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:Subscribe to Every: https://every.to/subscribeFollow him on X: https://twitter.com/danshipperMeet 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 - Start00:01:30 – Introduction00:02:36 – Why AI won’t take your job00:06:42 – Jevons Paradox and the future of work00:10:40 – How Aaron’s experience with the cloud era shapes his view of AI00:19:44 – Why every knowledge worker is becoming a manager of AI agents00:25:21 – What Aaron’s learned from bringing AI into every corner of Box00:33:57 – What’s overhyped in AI today00:43:31 – How Aaron balances everyday execution with innovationLinks to resources mentioned in the episode:Aaron Levie: Aaron Levie (@levie)Box: https://www.box.com/Dan’s essay on the shift toward the allocation economy: "The Knowledge Economy Is Over. Welcome to the Allocation Economy"Dwarkesh’s podcast with Richard Sutton: https://www.dwarkesh.com/p/richard-sutton

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:Subscribe to Every: https://every.to/subscribeFollow him on X: https://twitter.com/danshipperReady 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 - Start00:01:14 - Introduction00:02:54 - Why Alex likes running barefoot00:05:09 - APIs and MCP, the connectors of the new internet00:10:53 - Why MCP servers are hard to get right00:20:07 - Design principles for reliable MCP servers00:23:50 - Scaling MCP servers for large APIs00:25:14 - Using MCP for business ops at Stainless00:28:12 - Building a company brain with Claude Code00:33:59 - Where MCP goes from here00:41:10 - Alex’s take on the security model for MCPLinks to resources mentioned in the episode:Alex Rattray: Alex Rattray (@RattrayAlex), Alex Rattray Stainless: https://www.stainless.com/

The future has a way of showing up early to some places. In software engineering, one of those places is Cognition—the startup that made headlines in early 2024 with Devin, the world’s first autonomous coding agent, and more recently with its acquisition of the AI code editor Windsurf.Scott Wu, Cognition’s cofounder and CEO, has a front-row seat to what comes next. In this episode of AI & I, we talk with Wu about why the fundamentals of computer science still matter in an AI-first world, the direction he sees for the short- and long-term future of programming, and why he believes we may already be living with AGI.Timestamps: 00:00:00 – Start00:02:02 – Introduction00:02:32 – Why Scott thinks AGI is here00:09:27 – Scott’s personal journey as a founder00:16:55 – Why the fundamentals of computer science still matter00:22:30 – How the future of programming will evolve00:26:50 – A new workflow for the AI-first software engineer00:29:33 – How Devin stacks up against Claude Code00:40:05 – Reinforcement learning to build better coding agents00:50:05 – What excites Scott about AI beyond CognitionIf 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 Links to resources mentioned in the episode:Scott Wu: Scott Wu (@ScottWu46) Learn more about Cognition: https://cognition.ai/ Try the world’s first autonomous coding agent: https://devin.ai/ 

Naveen Naidu built an app that found product-market fit backwards.Most apps launch first and then try to find users. Monologue, Naveen’s AI voice dictation app that came out of beta yesterday, did the opposite. It built a following of thousands of users during its incubation period at Every—many of them switching over from venture capital-backed competitors—all while the app barely had a landing page.The growth has continued in the 24 hours since launch, with an average of 1 million words being transcribed weekly, and in this episode of AI & I, we sit down with Naveen to talk about his journey as the single engineer behind a viral app. We get into the false starts and side projects that taught Naveen how to ship fast, the brutal feedback that kept Monologue honest, why Every decided to build in a crowded category, and the AI coding tools that let one developer do the work of a team.Get free early access to Amazon's Alexa Plus: https://www.amazon.com/dp/B0DCCNHWV5?ref_=aucc_us_dis_everyalexa_q3_25Timestamps:00:01:27 – Introduction00:03:51 – A live demo of Monologue00:06:27 – Hard lessons from Naveen’s years in the wilderness00:12:29 – Building a muscle to ship fast00:21:11 – The spark that became Monologue00:26:09 – Dogfooding your way to a killer feature00:29:45 – Why the harshest product feedback is the most valuable00:31:47 – Every’s strategy for launching an app in a crowded space00:40:08 – Giving Monologue the Every “smell”00:45:09 – Naveen’s one-person AI stack to build beautiful appsIf 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/danshipperLinks to resources mentioned in the episode: https://www.monologue.to/

Noah Brier uses Claude Code as his second brain—it’s the coolest notetaking setup we’ve ever seen.He has Claude running on a server in his basement hooked up to a VPN. It stores, reads, and writes to thousands of notes in his Obsidian vault. He does it all from his phone.We had him on the show to tell us exactly how he’s pulling this off. Dan and Noah get into:The nuts and bolts of the Claude Code-Obsidian setup: Noah set up Claude Code on top of his Obsidian root directory, and he walked me through how he uses it to prep for an upcoming speech—creating a project folder, pulling in relevant research from his notes, saving transcripts from chats with other LLMs, and generating daily progress updates.The “thinking partner” that lives inside Noah’s second brain: Noah points out that in the hype around AI’s ability to write, the fact that it can read is overlooked. That’s why he has an agent inside Claude Code with strict guardrails to stay in “thinking mode.” It logs his questions, tracks insights, and catches him up on research if he returns to a project after a few days away.How Noah does deep work on his phone: Noah rigged a home server in his basement, put his Obsidian vault in it—and then runs Claude Code on top. Noah says that being able to think, write, research, and ship code from his phone has fundamentally changed the way he works.This episode is a must-watch for anyone curious about who wants to learn how to use Claude Code to build a true second brain.If you found this episode interesting, please like, subscribe, comment, and share! Start building in Google AI Studio at ai.dev. 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. 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: 00:01:19 - Introduction00:04:28 - How you can do deep work on your phone00:06:14 - Why Noah thinks Grok has the best voice AI00:11:39 - The nuts and bolts of Noah’s Claude Code-Obsidian setup00:23:59 - Using an agent in Claude Code as a “thinking partner”00:35:07 - Noah’s Thomas’ English Muffin theory of AI00:44:04 - The white space still left to explore in AI00:50:41 - How Noah is preparing his kids for AI01:01:54 - How he brought his Claude Code setup to mobileLinks to resources mentioned in the episode:Noah Brier: ⁠https://www.noahbrier.com/⁠, ⁠Noah Brier (@heyitsnoah) / X⁠Alephic, his AI strategy consultancy: ⁠alephic.com⁠ The conference he leads about marketing and AI: ⁠http://BRXND.AI⁠ A newsletter he writes about AI: ⁠newsletter.brxnd.ai⁠  The declassified relic from World War II they talk about: ⁠Simple Sabotage Field Manual⁠ The apps Noah used to set up Claude Code on his phone: ⁠Termius⁠, ⁠Tailscale⁠ 

We had ⁠Dean Leitersdorf⁠ on the pod and he did something no guest had ever done.Mid-sentence, he transformed from a startup founder in a black t-shirt to a wizard with light shooting from his hands. Then, he was in a white-walled game universe, and when he picked up the tissue box on his table, it morphed into a gun which he could shoot by moving his arm.He did it with one of his products, ⁠Mirage⁠: It takes any live video feed (like Dean on the pod) and instantly renders each frame into a new style of your choosing—40 milliseconds from input to output.Dean is the co-founder and CEO of the creators of ⁠Decart⁠ which makes Mirage. They recently raised $100 million at a $3.1 billion valuation to build a new era of real-time generative AI experiences like this.Realtime generative video models are going to change video games forever, and Dean is on the forefront: imagine creating endless variations on existing titles, like GTA-V with a frigid winter filter, or taking a bare-bones vibe-coded prototype and using Mirage to texture it. But games are just the beginning, Dean sees Mirage as opening the door to a new medium, a new experience created by AI. In this episode, we take a look at how Mirage works under the hood, and what the Decart team learned about the future of software while wrestling with its toughest research problems. We also debate AGI—how close it really is, what counts as progress, and what kind of society it might create. This episode is a must watch for anyone interested in the future of gaming, creativity, or if you just want your mind blown by what’s already possible. 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 Timestamps: Introduction: 00:00:47A demo of Mirage, the first real-time video-to-video model in the world: 00:02:38How Mirage can take your vibe-coded game to the next level: 00:06:22The new architecture of modern software: 00:08:45How Mirage works so blazingly fast: 00:16:34Inside Decart’s invention of a new “live stream diffusion” model: 00:20:33Solving the error accumulation problem for real-time video: 00:21:17How Dean thinks about inventing a new creative medium: 00:29:55Dean’s take on the post-AGI world: 00:39:43Why AI brings back the age of the generalist: 00:51:15Links to resources mentioned in the episode:Dean Leitersdorf: @DLeitersdorfDecart: ⁠https://about.decart.ai/⁠ Try Mirage and Delulu: ⁠https://mirage.decart.ai/⁠, ⁠https://play.google.com/store/apps/details?id=ai.decart.delulu⁠, ⁠https://apps.apple.com/il/app/delulu-by-decart/id6749955738⁠  More about Yan LeCun’s error accumulation problem: ⁠https://x.com/ylecun/status/1640123182983045120⁠