Gradient Dissent: Conversations on AI

Arvind Jain on Building Glean and the Future of Enterprise AI

In this episode of Gradient Dissent, Lukas Biewald sits down with Arvind Jain, CEO and founder of Glean. They discuss Glean's evolution from solving enterprise search to building agentic AI tools that understand internal knowledge and workflows. Arvind shares how his early use of transformer models in 2019 laid the foundation for Glean’s success, well before the term "generative AI" was mainstream.They explore the technical and organizational challenges behind enterprise LLMs—including security, hallucination suppression—and when it makes sense to fine-tune models. Arvind also reflects on his previous startup Rubrik and explains how Glean’s AI platform aims to reshape how teams operate, from personalized agents to ever-fresh internal documentation.Follow Arvind Jain: https://x.com/jainarvindFollow Weights & Biases: https://x.com/weights_biasesTimestamps: [00:01:00] What Glean is and how it works [00:02:39] Starting Glean before the LLM boom [00:04:10] Using transformers early in enterprise search [00:06:48] Semantic search vs. generative answers [00:08:13] When to fine-tune vs. use out-of-box models [00:12:38] The value of small, purpose-trained models [00:13:04] Enterprise security and embedding risks[00:16:31] Lessons from Rubrik and starting Glean [00:19:31] The contrarian bet on enterprise search [00:22:57] Culture and lessons learned from Google [00:25:13] Everyone will have their own AI-powered "team" [00:28:43] Using AI to keep documentation evergreen [00:31:22] AI-generated churn and risk analysis [00:33:55] Measuring model improvement with golden sets[00:36:05] Suppressing hallucinations with citations [00:39:22] Agents that can ping humans for help [00:40:41] AI as a force multiplier, not a replacement [00:42:26] The enduring value of hard work

How DeepL Built a Translation Powerhouse with AI with CEO Jarek Kutylowski

In this episode of Gradient Dissent, Lukas Biewald talks with Jarek Kutylowski, CEO and founder of DeepL, an AI-powered translation company. Jarek shares DeepL’s journey from launching neural machine translation in 2017 to building custom data centers and how small teams can not only take on big players like Google Translate but win.They dive into what makes translation so difficult for AI, why high-quality translations still require human context, and how DeepL tailors models for enterprise use cases. They also discuss the evolution of speech translation, compute infrastructure, training on curated multilingual datasets, hallucinations in models, and why DeepL avoids fine-tuning for each individual customer. It’s a fascinating behind-the-scenes look at one of the most advanced real-world applications of deep learning.Timestamps: [00:00:00] Introducing Jarek and DeepL’s mission [00:01:46] Competing with Google Translate & LLMs [00:04:14] Pretraining vs. proprietary model strategy [00:06:47] Building GPU data centers in 2017 [00:08:09] The value of curated bilingual and monolingual data [00:09:30] How DeepL measures translation quality [00:12:27] Personalization and enterprise-specific tuning[00:14:04] Why translation demand is growing [00:16:16] ROI of incremental quality gains [00:18:20] The role of human translators in the future [00:22:48] Hallucinations in translation models [00:24:05] DeepL’s work on speech translation [00:28:22] The broader impact of global communication [00:30:32] Handling smaller languages and language pairs [00:32:25] Multi-language model consolidation [00:35:28] Engineering infrastructure for large-scale inference [00:39:23] Adapting to evolving LLM landscape & enterprise needs

GitHub CEO Thomas Dohmke on Copilot and the Future of Software Development

In this episode of Gradient Dissent, Lukas Biewald sits down with Thomas Dohmke, CEO of GitHub, to talk about the future of software engineering in the age of AI. They discuss how GitHub Copilot was built, why agents are reshaping developer workflows, and what it takes to make tools that are not only powerful but also fun.Thomas shares his experience leading GitHub through its $7.5B acquisition by Microsoft, the unexpected ways it accelerated innovation, and why developer happiness is crucial to productivity. They explore what still makes human engineers irreplaceable and how the next generation of developers might grow up coding alongside AI.Follow Thomas Dohmke: https://www.linkedin.com/in/ashtom/Follow Weights & Biases:https://twitter.com/weights_biases https://www.linkedin.com/company/wandb

From Pharma to AGI Hype, and Developing AI in Finance: Martin Shkreli’s Journey

In this episode of Gradient Dissent, Lukas Biewald talks with Martin Shkreli — the infamous "pharma bro" turned founder — about his path from hedge fund manager and pharma CEO to convicted felon and now software entrepreneur. Shkreli shares his side of the drug pricing controversy, reflects on his prison experience, and explains how he rebuilt his life and business after being "canceled."They dive deep into AI and drug discovery, where Shkreli delivers a strong critique of mainstream approaches. He also talks about his latest venture in finance software, building Godel Terminal “a Vim for traders", and why he thinks the AI hype cycle is just beginning. It's a wide-ranging and candid conversation with one of the most controversial figures in tech and biotech.Follow Martin Shkreli on TwitterGodel Terminal: https://godelterminal.com/Follow Weights & Biases on Twitterhttps://www.linkedin.com/company/wandb Join the Weights & Biases Discord Server:https://discord.gg/CkZKRNnaf3

Inside Cursor: The future of AI coding with Co-founder Sualeh Asif

In this episode of Gradient Dissent, host Lukas Biewald talks with Sualeh Asif, the CPO and co-founder of Cursor, one of the fastest-growing and most loved AI-powered coding platforms. Sualeh shares the story behind Cursor’s creation, the technical and design decisions that set it apart, and how AI models are changing the way we build software. They dive deep into infrastructure challenges, the importance of speed and user experience, and how emerging trends in agents and reasoning models are reshaping the developer workflow.Sualeh also discusses scaling AI inference to support hundreds of millions of requests per day, building trust through product quality, and his vision for how programming will evolve in the next few years.⏳Timestamps:00:00 How Cursor got started and why it took off04:50 Switching from Vim to VS Code and the rise of CoPilot08:10 Why Cursor won among competitors: product philosophy and execution10:30 How user data and feedback loops drive Cursor’s improvements12:20 Iterating on AI agents: what made Cursor hold back and wait13:30 Competitive coding background: advantage or challenge?16:30 Making coding fun again: latency, flow, and model choices19:10 Building Cursor’s infrastructure: from GPUs to indexing billions of files26:00 How Cursor prioritizes compute allocation for indexing30:00 Running massive ML infrastructure: surprises and scaling lessons34:50 Why Cursor chose DeepSeek models early36:00 Where AI agents are heading next40:07 Debugging and evaluating complex AI agents42:00 How coding workflows will change over the next 2–3 years46:20 Dream future projects: AI for reading codebases and papers🎙 Get our podcasts on these platforms:Apple Podcasts: https://wandb.me/apple-podcastsSpotify: https://wandb.me/spotifyYouTube: https://wandb.me/youtubeFollow Weights & Biases:https://x.com/weights_biaseshttps://www.linkedin.com/company/wandb