Without live web data, your AI agent is basically useless | Jennifer Burns, Bright Data

Welcome to the new episode of the TNW Podcast, the show where we discuss the latest developments in the technology ecosystem and feature interviews with some of the most influential people in the industry.In today’s episode, we’re happy to present an interview with Kristin Fracchia, who leads growth and marketing at Gamma, which creates AI presentations, documents, and more. Kristin explains how Gamma went from an idea one investor called the worst they had ever heard to well over 100M users, 80% of them outside the US, and why it doesn’t try to convert every free user.We dig into the “made with Gamma” viral loop, the 500+ creators Gamma works with every month, and why every launch is judged by how many users come back. We also get into how Kristin landed her job with a cold email to the CEO, and why she thinks marketers now have a second buyer that isn’t human.Feel free to email us with any questions, suggestions, and opinions at [email protected]:00 Intro00:21 What Gamma does01:15 Slides as a means to an end02:07 100M users and a generous free plan03:42 Gamma's founding and 2023 breakout04:24 The "worst idea ever" pitch04:36 Why Kristin joined Gamma05:58 How to cold email a CEO06:41 Gamma's team and culture07:42 The viral loop and 500+ creators08:45 Prosumer and business users09:28 Competing with Google and Microsoft11:19 What 30M gammas a month reveal12:42 Bringing back users who tried it before14:24 The second buyer that isn't human

Welcome to the new episode of the TNW Podcast, the show where we discuss the latest developments in the technology ecosystem and feature interviews with some of the most influential people in the industry.In today’s episode, we’re happy to present an interview with Daniel Dines, founder and CEO of UiPath, the automation company he started in Romania in 2005. Daniel explains why everything that can be delivered with software should be delivered in software, with AI stepping in only where software can’t, and why AI still can’t learn on the job, the gap UiPath’s new Cartographer agent is built to close.We also get into UiPath’s long road to product-market fit, why he never compromises on chemistry when hiring, how juniors should learn now that AI agents do their old tasks, and why he came back as CEO. His advice for young people: embrace the unknown, be a cartographer, be an explorer.Feel free to email us with any questions, suggestions, and opinions at [email protected]:00 Intro01:44 Why UiPath's culture is humble but bold03:50 The long road to product-market fit07:20 Never compromise on chemistry08:36 AI agents vs junior hires11:24 How the Cartographer agent learns a business14:05 What enterprises get wrong about AI17:32 Writing a book with AI agents19:33 Life as UiPath's CEO21:51 From communist Romania to founding UiPath27:31 Why Daniel came back as CEO31:06 UiPath's vision and going public32:37 Should we slow down AI?33:03 Can AI have a will?34:59 Advice for young people

Episode Show Notes / DescriptionWelcome to the new episode of the TNW Podcast, the show where we discuss the latest developments in the technology ecosystem and feature interviews with some of the most influential people in the industry.In today’s episode, we’re happy to present an interview with Jennifer Burns, Senior Director of PR and Communications at Bright Data, which she describes as the #1 web data infrastructure company. Jennifer explains why AI agents are basically useless without live web data, and why anything a person can see without a login should be open to AI too.We dig into the lawsuit X brought against Bright Data, why paywalled content is off limits, the company’s growth from 20,000 to 50,000 customers, and robots learning from public web data. We also get into Jennifer’s 20 years in journalism and her advice for AI companies: know your story, own it, and make sure everyone in the company can explain it.Feel free to email us with any questions, suggestions, and opinions at [email protected]:00 Intro00:26 What Bright Data does01:30 Connecting the old web to AI agents03:02 Public vs private data04:36 20 years as a journalist05:18 The X lawsuit, gatekeeping and paywalls06:55 Why Jennifer joined Bright Data07:51 From 20,000 to 50,000 customers08:54 What's next for Bright Data09:48 Robots and the context layer11:41 How AI agents use the web13:13 A day in PR at Bright Data14:25 Why she runs 5 AI agents15:41 PR advice for AI companies16:57 Advice for new grads

Welcome to the new episode of the TNW Podcast, the show where we discuss the latest developments in the technology ecosystem and feature interviews with some of the most influential people in the industry.In today’s episode, we’re happy to present an interview with Avani Prabhakar, Chief People and AI Enablement Officer of Atlassian, the company that builds teamwork and collaboration tools for knowledge workers. Avani explains why Atlassian treats AI as a people transformation rather than a tech one, and why deploying AI turned out to be the easy part.We dig into the AI wallet every employee gets, why she monitors token usage instead of rewarding it, how Atlassian defines an AI super user, the Teamwork Graph context layer that saved about 48% of tokens, and why she warns against AI mandates and ROI-first business cases. Her advice for leaders: when you don’t have the answer, say “I don’t know.”Feel free to email us with any questions, suggestions, and opinions at [email protected]:00 Intro00:16 What Atlassian does00:44 Why AI is a people transformation04:24 AI rollout mistakes to avoid08:35 Token maxing and AI wallets10:17 Bringing IT and people teams together11:28 What blocks AI adoption13:27 Why a written culture helps AI15:01 Team Anywhere and mandates16:03 Becoming Atlassian's customer zero17:04 Avani's path from GE to Atlassian19:27 Don't pick a career out of fear21:12 How Atlassian hires for values22:20 Keeping people engaged

Episode Show Notes / DescriptionWelcome to the new episode of the TNW Podcast, the show where we discuss the latest developments in the technology ecosystem and feature interviews with some of the most influential people in the industry.In today’s episode, we’re happy to present an interview with Job van der Voort, founder and CEO of Remote, which makes it easy to hire and pay anybody anywhere. Job explains what Remote learned when it made its own AI course mandatory, including why some teams believed payroll work couldn’t use AI, and why his focus is on helping the people he already has get better.We also get into what Remote sees in the job market, why more PhDs now label data for AI companies, the growing challenge of Europe’s labor rules, and how Remote competes with local payroll providers while staying profitable and private. His advice for anyone starting out: join a startup, fail a lot, and stick around.Feel free to email us with any questions, suggestions, and opinions at [email protected]:00 Intro00:30 What Remote does for companies01:07 From neuroscience PhD to Remote02:24 Getting more from the team Remote has03:45 Making the AI course mandatory05:06 Reinventing how the work gets done06:07 What Remote sees in the job market07:37 How AI is changing contract work09:45 Are companies replacing people with AI agents?10:23 Funding, profits, and IPO plans10:49 Uncertainty and Europe's labor rules12:36 Remote's MCP server and AI agents14:41 Competing with local payroll firms17:40 Robotics, hardware, and acquisitions19:06 Advice for 20-year-olds in tech

Welcome to the new episode of the TNW Podcast, the show where we discuss the latest developments in the technology ecosystem and feature interviews with some of the most influential people in the industry.In today’s episode, we’re happy to present an interview with Steve Lucas, chairman and CEO of Boomi, a data activation company that delivers integration, automation, and AI capability to over 30,000 companies. Steve explains why he expects AI to bring 10x more work before there’s 10x less, and why he thinks the SaaS apocalypse is overrated.We dig into why telling your team to use AI doesn’t work, how AI handles about half of Boomi’s accounts payable with humans in the loop, and why AI projects get stuck on data. Steve shares how Boomi tripled revenue in 4 years and why his book, Digital Impact, argues AI may give us back our humanity. His advice for anyone starting out: be curious.Feel free to email us with any questions, suggestions, and opinions at [email protected]:00 Intro00:42 From Microsoft to Marketo02:22 Why companies need a platform like Boomi04:01 Where the name Boomi comes from04:58 How Boomi rolls out AI internally06:25 10x more work and the SaaS apocalypse08:41 Where companies get stuck with AI09:21 Which AI agents drive ROI10:39 Have we already reached AGI?11:48 How Steve spends his days14:12 Digital Impact and 350 productivity apps16:00 How Boomi tripled revenue17:40 Why saying no is the hardest part19:29 What's next: AI governance20:40 Advice for new grads: be curious

Welcome to the new episode of the TNW Podcast, the show where we discuss the latest developments in the technology ecosystem and feature interviews with some of the most influential people in the industry.In today’s episode, we’re happy to present an interview with Ivan Burazin, co-founder and CEO of Daytona, the infrastructure company that gives AI agents their own computers to train and work in. Ivan explains how Daytona grew about 50% a month for 18 months without any salespeople, through in-person events and his Twitter account, which he calls the company’s second growth channel and credits for its Nvidia partnership.We also get into the pivot that took Daytona from Fortune 500 customers back to zero, why agents need Windows and GPU sandboxes, and why Ivan expects a CPU crunch bigger than the GPU crunch. His advice to young founders: learn to handle risk and failure, because everyone plateaus once they stop taking risks.Feel free to email us with any questions, suggestions, and opinions at [email protected]:00 Intro00:47 Ivan's background and the Daytona name02:17 Why customers pick Daytona over Kubernetes03:52 Winning customers in person05:12 Growing 50% a month without salespeople06:18 The 3 reasons customers choose you07:48 How Twitter led to an Nvidia partnership10:34 Kill it or grind through it12:57 Post-training and the CPU crunch13:52 The pivot back to zero14:47 Why Ivan hires for grit15:26 Living between Europe and San Francisco17:51 Why AI agents need Windows and GPUs20:18 Risk, failure and how Ivan got started24:12 Where the Daytona team is based

Welcome to the new episode of the TNW Podcast, the show where we discuss the latest developments in the technology ecosystem and feature interviews with some of the most influential people in the industry.In today’s episode, we’re happy to present an interview with Arvind Jain, founder and CEO of Glean, the enterprise AI company that connects to every system a business runs on and turns its knowledge into context for people and AI agents. Arvind explains why AI needs that context to work well, why 80 to 90% of it lives in people’s heads, and how Glean feeds it to tools like Claude.We also get into how Glean protects employee privacy, why word of mouth is still its biggest growth channel, and Arvind’s advice for graduates worried about AI. His most surprising answer is about lock-in: Glean wants to be easy to replace, because the memory its AI builds should belong to the enterprise.Feel free to email us with any questions, suggestions, and opinions at [email protected]:00 Intro01:51 How companies use Glean06:46 Why not just use Claude?10:27 Why Glean wants to be replaceable13:13 How Glean protects employee privacy15:28 How Glean got started16:56 Word of mouth and rapid growth18:25 What context really means21:06 Rapid fire: scaling and fundraising22:53 How Arvind spends his day as CEO23:36 Career lessons and advice for graduates25:34 Where the idea for Glean came from26:08 Why big companies get slow27:37 Where Glean saves people time29:34 Is Glean Asana plus Claude?

Welcome to the new episode of the TNW Podcast, the show where we discuss the latest developments in the technology ecosystem and feature interviews with some of the most influential people in the industry.In today’s episode, we’re happy to present an interview with Michael Atalla, Chief Marketing Officer of UiPath, the Romanian-born business orchestration and automation company. Michael explains why AI agents won’t replace humans: they can’t grasp intent or learn on the job, so the exceptions that need trust and judgment stay with people. He also argues that AI should augment our skills and that cutting junior jobs is a mistake.We also get into the AI agent his marketing team built for ad data, the Process Atlas and Cartographer launches at FUSION, why low-risk AI pilots stall, and why AI slop means marketing still needs humans. His advice for anyone starting a career in tech is simple: move.Feel free to email us with any questions, suggestions, and opinions at [email protected]:00 Intro00:51 Robots, agents, and orchestration explained01:59 What companies use UiPath for03:10 Why Michael joined UiPath04:29 How UiPath automates its own marketing07:30 Process Atlas and Cartographer at FUSION11:34 What AI agents still can't do13:12 How Romania shaped UiPath's culture15:46 Why AI pilots get stuck17:06 UiPath's vision beyond the AI hype18:14 How AI is changing marketing20:58 Will AI agents replace humans?22:15 Why cutting junior jobs is a mistake24:13 From writing code to CMO24:59 Advice for anyone starting in tech

Welcome to the new episode of the TNW Podcast, the show where we discuss the latest developments in the technology ecosystem and feature interviews with some of the most influential people in the industry.In today's episode, we're happy to present an interview with Tom Eggemeier, CEO of Zendesk, the customer and employee service company helping businesses automate their interactions with AI. Tom explains how Zendesk's AI revenue grew from about $0 to a projected $400M in 2 years, and why the company is moving from seats to outcome-based pricing.We also get into why companies should always offer a human option, what AI means for jobs, and Tom's own use of AI, including how Meta's Muse agent saved him $3,105 on internet, TV, and mobile bills in 5 days. His prediction: within 2 years, more than 50% of customer interactions will be a personal AI agent talking to a company's AI agent.Feel free to email us with any questions, suggestions, and opinions at [email protected].