Jacob Effron

At @OpenAI, Chief Scientist @merettm helps lead the research roadmap to AGI including a research intern-level AI system by September 2026 and a fully automated AI researcher by March 2028. I sat down with Jakub to check on those timelines and ask him all of my top-of-mind AI questions including: ▪️ How OpenAI thinks about extending RL beyond code and math ▪️ The current state of alignment research as more powerful models loom ▪️ The future of continual learning ▪️ How startups should think about building their own models/harnesses And he also shared some great stories around OpenAI’s pioneering work on math. YouTube: youtu.be/vK1qEF3a3WM Spotify: bit.ly/4sjUyrN Apple: bit.ly/41jAdrN 0:00 Intro 1:53 Research Intern Capability Timelines 4:59 Math Breakthroughs 7:59 RL Beyond Verifiable Tasks 12:32 RL vs In-Context 19:01 Allocating Compute Internally 28:18 AI for Science 31:40 Pattern Matching 33:23 Solving the Hardest Math Problems 37:40 Chain of Thought Monitoring 44:33 Generalization and Value Alignment in Models 47:57 Inside OpenAI 51:55 Quickfire

At @OpenAI, Chief Scientist @merettm helps lead the research roadmap to AGI including a research intern-level AI system by September 2026 and a fully automated AI researcher by March 2028. I sat down with Jakub to check on those timelines and ask him all of my top-of-mind AI questions including: ▪️ How OpenAI thinks about extending RL beyond code and math ▪️ The current state of alignment research as more powerful models loom ▪️ The future of continual learning ▪️ How startups should think about building their own models/harnesses And he also shared some great stories around OpenAI’s pioneering work on math. YouTube: youtu.be/vK1qEF3a3WM Spotify: bit.ly/4sjUyrN Apple: bit.ly/41jAdrN 0:00 Intro 1:53 Research Intern Capability Timelines 4:59 Math Breakthroughs 7:59 RL Beyond Verifiable Tasks 12:32 RL vs In-Context 19:01 Allocating Compute Internally 28:18 AI for Science 31:40 Pattern Matching 33:23 Solving the Hardest Math Problems 37:40 Chain of Thought Monitoring 44:33 Generalization and Value Alignment in Models 47:57 Inside OpenAI 51:55 Quickfire

At @OpenAI, Chief Scientist @merettm helps lead the research roadmap to AGI including a research intern-level AI system by September 2026 and a fully automated AI researcher by March 2028. I sat down with Jakub to check on those timelines and ask him all of my top-of-mind AI questions including: ▪️ How OpenAI thinks about extending RL beyond code and math ▪️ The current state of alignment research as more powerful models loom ▪️ The future of continual learning ▪️ How startups should think about building their own models/harnesses And he also shared some great stories around OpenAI’s pioneering work on math. YouTube: youtu.be/vK1qEF3a3WM Spotify: bit.ly/4sjUyrN Apple: bit.ly/41jAdrN 0:00 Intro 1:53 Research Intern Capability Timelines 4:59 Math Breakthroughs 7:59 RL Beyond Verifiable Tasks 12:32 RL vs In-Context 19:01 Allocating Compute Internally 28:18 AI for Science 31:40 Pattern Matching 33:23 Solving the Hardest Math Problems 37:40 Chain of Thought Monitoring 44:33 Generalization and Value Alignment in Models 47:57 Inside OpenAI 51:55 Quickfire

At @OpenAI, Chief Scientist @merettm helps lead the research roadmap to AGI including a research intern-level AI system by September 2026 and a fully automated AI researcher by March 2028. I sat down with Jakub to check on those timelines and ask him all of my top-of-mind AI questions including: ▪️ How OpenAI thinks about extending RL beyond code and math ▪️ The current state of alignment research as more powerful models loom ▪️ The future of continual learning ▪️ How startups should think about building their own models/harnesses And he also shared some great stories around OpenAI’s pioneering work on math. YouTube: youtu.be/vK1qEF3a3WM Spotify: bit.ly/4sjUyrN Apple: bit.ly/41jAdrN 0:00 Intro 1:53 Research Intern Capability Timelines 4:59 Math Breakthroughs 7:59 RL Beyond Verifiable Tasks 12:32 RL vs In-Context 19:01 Allocating Compute Internally 28:18 AI for Science 31:40 Pattern Matching 33:23 Solving the Hardest Math Problems 37:40 Chain of Thought Monitoring 44:33 Generalization and Value Alignment in Models 47:57 Inside OpenAI 51:55 Quickfire

What’s it like building at Abridge? “It feels like the beginning of the Internet… It’s love for software that I have never seen.” Watch to see what our builders say about working at Abridge. We’re fortunate to be backed by investors who share our vision, including @a16z @eladgil @khoslaventures @NVIDIA Ventures @IVP @SVAngel @lightspeedvp @Redpoint @sparkcapital @BessemerVP @usv We’re hiring in SF!

Legora sets the bar for operating at AI speed. Watching them become one of the fastest growing software companies of all time these past few years has provided constant lessons on what’s required to win in this new world. Fresh off @WeAreLegora's $550M Series D, CEO @MaxJunestrand joined @loganbartlett and me on Unsupervised Learning to provide a masterclass on building an AI-native company. He shared some amazing lessons around - Constantly rebuilding for the bleeding edge of model capabilities - Partnering with customers for both immediate impact and long-term transformation - Running Legora differently from traditional software companies He also included some spicy takes on - Why foundation models entering legal is good for Legora - Pricing AI products - The future of the legal industry It’s impossible to listen to Max and not pick up the infectious energy that makes Legora such a special company. Check out the full episode: YouTube: youtu.be/wzRZp-1EuaE Spotify: bit.ly/3Nc53za Apple: bit.ly/40ufr8m 0:00 Intro 1:16 Legora’s Series D Story 3:24 Why You Need Low Ego to Build in AI 5:58 From 60% to 100% Accuracy in One Summer 7:04 Law Firm Economics Shift 14:09 Pricing Seats Vs Outcomes 18:31 Why Foundation Models Entering Legal Helps Legora 30:10 Convincing a 75-Year-Old Partner to Go All In 33:02 Hiring Legal Engineers 34:32 Running an AI-Native Company 35:57 The Opus 4.5 Christmas Breakthrough 40:02 Building With Customers 44:01 All In On US Expansion 51:22 Stockholm Startup DNA

Legora sets the bar for operating at AI speed. Watching them become one of the fastest growing software companies of all time these past few years has provided constant lessons on what’s required to win in this new world. Fresh off @WeAreLegora's $550M Series D, CEO @MaxJunestrand joined @loganbartlett and me on Unsupervised Learning to provide a masterclass on building an AI-native company. He shared some amazing lessons around - Constantly rebuilding for the bleeding edge of model capabilities - Partnering with customers for both immediate impact and long-term transformation - Running Legora differently from traditional software companies He also included some spicy takes on - Why foundation models entering legal is good for Legora - Pricing AI products - The future of the legal industry It’s impossible to listen to Max and not pick up the infectious energy that makes Legora such a special company. Check out the full episode: YouTube: youtu.be/wzRZp-1EuaE Spotify: bit.ly/3Nc53za Apple: bit.ly/40ufr8m 0:00 Intro 1:16 Legora’s Series D Story 3:24 Why You Need Low Ego to Build in AI 5:58 From 60% to 100% Accuracy in One Summer 7:04 Law Firm Economics Shift 14:09 Pricing Seats Vs Outcomes 18:31 Why Foundation Models Entering Legal Helps Legora 30:10 Convincing a 75-Year-Old Partner to Go All In 33:02 Hiring Legal Engineers 34:32 Running an AI-Native Company 35:57 The Opus 4.5 Christmas Breakthrough 40:02 Building With Customers 44:01 All In On US Expansion 51:22 Stockholm Startup DNA

Legora sets the bar for operating at AI speed. Watching them become one of the fastest growing software companies of all time these past few years has provided constant lessons on what’s required to win in this new world. Fresh off @WeAreLegora's $550M Series D, CEO @MaxJunestrand joined @loganbartlett and me on Unsupervised Learning to provide a masterclass on building an AI-native company. He shared some amazing lessons around - Constantly rebuilding for the bleeding edge of model capabilities - Partnering with customers for both immediate impact and long-term transformation - Running Legora differently from traditional software companies He also included some spicy takes on - Why foundation models entering legal is good for Legora - Pricing AI products - The future of the legal industry It’s impossible to listen to Max and not pick up the infectious energy that makes Legora such a special company. Check out the full episode: YouTube: youtu.be/wzRZp-1EuaE Spotify: bit.ly/3Nc53za Apple: bit.ly/40ufr8m 0:00 Intro 1:16 Legora’s Series D Story 3:24 Why You Need Low Ego to Build in AI 5:58 From 60% to 100% Accuracy in One Summer 7:04 Law Firm Economics Shift 14:09 Pricing Seats Vs Outcomes 18:31 Why Foundation Models Entering Legal Helps Legora 30:10 Convincing a 75-Year-Old Partner to Go All In 33:02 Hiring Legal Engineers 34:32 Running an AI-Native Company 35:57 The Opus 4.5 Christmas Breakthrough 40:02 Building With Customers 44:01 All In On US Expansion 51:22 Stockholm Startup DNA

Big day at @WeAreLegora! We have raised $550 million at a $5.55 billion valuation in a Series D funding round, led by @Accel, to accelerate expansion across the United States. To all our customers and partners, this celebration is as much yours as it is ours.