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These guys literally dropped a masterclass on the basics of technical AI: 3:22 - How LLMs actually work 5:24 - What temperature is 7:05 - What context windows are 7:59 - Building a tool from scratch 10:28 - Why MCP exists 12:03 - What makes an agent an agent...

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Aakash Gupta

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74,673 просмотров • 8 дней назад •via X (Twitter)

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424,191 просмотров • 3 месяцев назад

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E159: Hyperliquid: Housing all of Finance jeff.hl came back on the When Shift Happens Podcast to talk about the Hyperliquid journey since the TGE and what the future holds for one of the most loved and prolific protocols in the space Hyperliquid Timestamps 0:00 Intro 2:01 Singapore 2:27 Reminiscing on the Token Launch 5:00 Was This Scale Of Wealth Expected? 6:28 Doing The Right Thing In Crypto 9:07 The Responsibility that comes with Billions of $ 11:10 Jupiter KAST 11:51 Bringing Hyperliquid to the masses 15:21 Pre TGE and Post TGE: Operational difference 20:13 Choices on what to build Internally vs Externally 22:05 How to build a reliable team 24:51 Did the Team celebrate the HYPE wealth Generation event? 26:45 How to test talents for High Integrity 28:31 How much does the Hyperliquid team sleep? 30:05 Employee Vesting Fears 31:41 Dealing with FUD 32:28 How Does Jeff Personally Handle FUD 35:02 Token "Buybacks" critics 37:20 Why Hyperliquid can't have Discretionary "Buybacks" 39:04 HyperEVM, explained Simply 40:00 Paradex Zodl 40:41 HyperEVM: Success so Far? 44:05 HIP-3, explained Simply 47:44 What makes Hyperliquid's approach different 48:19 Why Should People Care? 51:33 Bring All Finance On Chain 52:08 Why Is The Hyperliquid Approach Better? 53:47 Key Numbers showing that Hyperliquid Is Doing it right 59:01 What Has the Unit team demonstrated with spot trading on Hyperliquid in 2025 1:03:29 HIP-4: Outcome Markets 1:08:01 Trezor Sui 1:08:58 What does "Housing All Of Finance" mean? 1:10:51 Why Hyperliquid is not a crypto company 1:12:23 Why Does Hyperliquid have A Stablecoin USDH (Native Markets) 1:14:39 What Is Kinetiq & Why Does It Matter? 1:16:15 Why Is What HyperLend Is Building Important For HyperLiquid 1:23:39 Where did Fairness cost the most? 1:24:47 What should Hyperliquid be Remembered for? 1:25:24 Why should people stay in Crypto when there's an AI brain drain? 1:28:10 Closing Thoughts
1:29:06

E159: Hyperliquid: Housing all of Finance jeff.hl came back on the When Shift Happens Podcast to talk about the Hyperliquid journey since the TGE and what the future holds for one of the most loved and prolific protocols in the space Hyperliquid Timestamps 0:00 Intro 2:01 Singapore 2:27 Reminiscing on the Token Launch 5:00 Was This Scale Of Wealth Expected? 6:28 Doing The Right Thing In Crypto 9:07 The Responsibility that comes with Billions of $ 11:10 Jupiter KAST 11:51 Bringing Hyperliquid to the masses 15:21 Pre TGE and Post TGE: Operational difference 20:13 Choices on what to build Internally vs Externally 22:05 How to build a reliable team 24:51 Did the Team celebrate the HYPE wealth Generation event? 26:45 How to test talents for High Integrity 28:31 How much does the Hyperliquid team sleep? 30:05 Employee Vesting Fears 31:41 Dealing with FUD 32:28 How Does Jeff Personally Handle FUD 35:02 Token "Buybacks" critics 37:20 Why Hyperliquid can't have Discretionary "Buybacks" 39:04 HyperEVM, explained Simply 40:00 Paradex Zodl 40:41 HyperEVM: Success so Far? 44:05 HIP-3, explained Simply 47:44 What makes Hyperliquid's approach different 48:19 Why Should People Care? 51:33 Bring All Finance On Chain 52:08 Why Is The Hyperliquid Approach Better? 53:47 Key Numbers showing that Hyperliquid Is Doing it right 59:01 What Has the Unit team demonstrated with spot trading on Hyperliquid in 2025 1:03:29 HIP-4: Outcome Markets 1:08:01 Trezor Sui 1:08:58 What does "Housing All Of Finance" mean? 1:10:51 Why Hyperliquid is not a crypto company 1:12:23 Why Does Hyperliquid have A Stablecoin USDH (Native Markets) 1:14:39 What Is Kinetiq & Why Does It Matter? 1:16:15 Why Is What HyperLend Is Building Important For HyperLiquid 1:23:39 Where did Fairness cost the most? 1:24:47 What should Hyperliquid be Remembered for? 1:25:24 Why should people stay in Crypto when there's an AI brain drain? 1:28:10 Closing Thoughts

MR SHIFT 🦁

577,829 просмотров • 5 месяцев назад

E137: From exposing Bitcoin’s biggest weakness to onboarding FIFA and MapleStory - Avalanche🔺 CEO and Founder Emin Gün Sirer🔺⚔️ - founder of Ava Labs 🔺, the company behind Avalanche - shares the journey from building Karma (a pre-Bitcoin digital currency) to pioneering Avalanche, the multi-chain blockchain reshaping crypto's infrastructure. From early academic battles with Bitcoin maxis to onboarding FIFA and MapleStory Universe, this is one of the wildest rides in Web3. Timestamps 0:00 Introduction 1:59 Opening Comments 2:55 What Is Your Mission 3:39 Who Are You 6:00 Business vs PHD Program 7:21 Chip on The Shoulder 9:32 Partnerships Jupiter, Money Badgers, Mantle 10:27 Chip On The Shoulder (Continued) 11:55 What Is An Internet Currency 13:55 Why Was Bitcoin Better 15:46 Biggest Flaws In Bitcoin 19:17 Is Maximalism A Good Thing 21:18 Does Maximalism Help Bitcoin 22:05 Fascination With Bitcoin & Crypto 23:33 Evolution With Time 25:11 Broader Crypto Use 27:26 Partnerships Trezor Sui 28:15 Avalanche Explained Simply 28:48 Shiny Object, Why People Fall For It 33:08 Moving Towards Show Me Era 34:27 What Emin Did Different 36:45 What Did You Do Wrong 38:10 Does The Best Tech Win 40:03 Avalanche, Home of Layer Ones? 42:10 How Does Avalanche Scale 43:38 The Gaming Blockchain 48:21 Real World Assets on Defy 50:31 How Big Is RWA 50:58 Why Transformation Is Slow 52:36 FIFA On Avalanche Blockchain, Why? 53:28 Endgame For Avalanche 56:48 Personal Difficulties While Building 58:30 What Did You Change Afterwards 1:01:25 Why Live In New York 1:03:40 Debanked After Moving 1:09:05 Crypto Full Mainstream, How? 1:10:43 Biggest Prediction In 12 Months
1:12:36

E137: From exposing Bitcoin’s biggest weakness to onboarding FIFA and MapleStory - Avalanche🔺 CEO and Founder Emin Gün Sirer🔺⚔️ - founder of Ava Labs 🔺, the company behind Avalanche - shares the journey from building Karma (a pre-Bitcoin digital currency) to pioneering Avalanche, the multi-chain blockchain reshaping crypto's infrastructure. From early academic battles with Bitcoin maxis to onboarding FIFA and MapleStory Universe, this is one of the wildest rides in Web3. Timestamps 0:00 Introduction 1:59 Opening Comments 2:55 What Is Your Mission 3:39 Who Are You 6:00 Business vs PHD Program 7:21 Chip on The Shoulder 9:32 Partnerships Jupiter, Money Badgers, Mantle 10:27 Chip On The Shoulder (Continued) 11:55 What Is An Internet Currency 13:55 Why Was Bitcoin Better 15:46 Biggest Flaws In Bitcoin 19:17 Is Maximalism A Good Thing 21:18 Does Maximalism Help Bitcoin 22:05 Fascination With Bitcoin & Crypto 23:33 Evolution With Time 25:11 Broader Crypto Use 27:26 Partnerships Trezor Sui 28:15 Avalanche Explained Simply 28:48 Shiny Object, Why People Fall For It 33:08 Moving Towards Show Me Era 34:27 What Emin Did Different 36:45 What Did You Do Wrong 38:10 Does The Best Tech Win 40:03 Avalanche, Home of Layer Ones? 42:10 How Does Avalanche Scale 43:38 The Gaming Blockchain 48:21 Real World Assets on Defy 50:31 How Big Is RWA 50:58 Why Transformation Is Slow 52:36 FIFA On Avalanche Blockchain, Why? 53:28 Endgame For Avalanche 56:48 Personal Difficulties While Building 58:30 What Did You Change Afterwards 1:01:25 Why Live In New York 1:03:40 Debanked After Moving 1:09:05 Crypto Full Mainstream, How? 1:10:43 Biggest Prediction In 12 Months

MR SHIFT 🦁

93,102 просмотров • 11 месяцев назад

When Mudith Jayasekara and I met Gabe Pereyra, we were expecting just another vanilla intro call and instead had the best yarn about research, the state of LLMs, and where intelligence is actually heading. It's rare to meet a founder this deep in the weeds who's also building for one of the most important verticals in this new age of intelligence So it was awesome to sit down with Gabe for an extended discussion on what it take to build agents that can reliably complete work over hours, days, or even longer? We talked about why agents today struggle with search and long context windows and how techniques like KV-cache compaction, synthetic data, and continual learning could help. 0:00 Introduction 0:36 Getting legal agents to review the whole data room 2:08 Data rooms larger than any context window 5:28 How far open-source models can go 7:58 Where specialist models fit in legal AI 10:59 Training legal models when client data is off-limits 13:06 Teaching a model how a law firm works 13:59 What belongs in context vs. model weights 15:36 From firm-wide AI to a model for every lawyer 18:37 What training adds beyond retrieving the right cases 20:26 Why context windows have plateaued 24:01 How models could learn continuously on the job 26:12 Can AI recursively improve AI research? 27:07 Research agents can run experiments but not choose them 30:00 Why open-ended research is hard to train 33:47 Why deployment, not intelligence, is the bottleneck 35:08 The cost of frontier intelligence 36:59 Different neolabs, different paths to intelligence 39:26 Using open datasets to compare research methods 41:13 Conclusion
41:50

When Mudith Jayasekara and I met Gabe Pereyra, we were expecting just another vanilla intro call and instead had the best yarn about research, the state of LLMs, and where intelligence is actually heading. It's rare to meet a founder this deep in the weeds who's also building for one of the most important verticals in this new age of intelligence So it was awesome to sit down with Gabe for an extended discussion on what it take to build agents that can reliably complete work over hours, days, or even longer? We talked about why agents today struggle with search and long context windows and how techniques like KV-cache compaction, synthetic data, and continual learning could help. 0:00 Introduction 0:36 Getting legal agents to review the whole data room 2:08 Data rooms larger than any context window 5:28 How far open-source models can go 7:58 Where specialist models fit in legal AI 10:59 Training legal models when client data is off-limits 13:06 Teaching a model how a law firm works 13:59 What belongs in context vs. model weights 15:36 From firm-wide AI to a model for every lawyer 18:37 What training adds beyond retrieving the right cases 20:26 Why context windows have plateaued 24:01 How models could learn continuously on the job 26:12 Can AI recursively improve AI research? 27:07 Research agents can run experiments but not choose them 30:00 Why open-ended research is hard to train 33:47 Why deployment, not intelligence, is the bottleneck 35:08 The cost of frontier intelligence 36:59 Different neolabs, different paths to intelligence 39:26 Using open datasets to compare research methods 41:13 Conclusion

Charlie O'Neill

88,859 просмотров • 9 дней назад

Agents Already Spent $76 Million: Circle's AI Agent stack, x402, stablecoins and the Agentic Economy Shoal Signal with Corey Cooper, Senior Manager, DevRel at Circle, hosted by Zaddycoin We cover how Circle is building the agent money stack with $USDC, Arc, x402, why EIP-3009 makes payments gasless, who is actually transacting today, whether SaaS is dead, and why agents buying their own services points to a trillion dollar TAM. 0:00 What Circle is building for agents 3:01 Why x402 matters for builders 6:54 USDC, gasless transfers, and facilitators 10:57 The Circle agent stack and nano payments 14:17 Who is using x402 and for what 16:46 Pay-per-use flattens the internet 19:50 A new persona, and $76 million transacted 23:03 What is missing for agent to agent 28:05 Every app has APIs, the TAM is trillions 29:26 Is SaaS dead 31:57 Discovery as the real value layer 36:28 How Circle curated its marketplace 41:23 Why it has to run on stablecoins 46:00 Cash App to agent in one second 49:38 Where the alpha is, trading on Robinhood 52:08 Try it yourself
54:16

Agents Already Spent $76 Million: Circle's AI Agent stack, x402, stablecoins and the Agentic Economy Shoal Signal with Corey Cooper, Senior Manager, DevRel at Circle, hosted by Zaddycoin We cover how Circle is building the agent money stack with $USDC, Arc, x402, why EIP-3009 makes payments gasless, who is actually transacting today, whether SaaS is dead, and why agents buying their own services points to a trillion dollar TAM. 0:00 What Circle is building for agents 3:01 Why x402 matters for builders 6:54 USDC, gasless transfers, and facilitators 10:57 The Circle agent stack and nano payments 14:17 Who is using x402 and for what 16:46 Pay-per-use flattens the internet 19:50 A new persona, and $76 million transacted 23:03 What is missing for agent to agent 28:05 Every app has APIs, the TAM is trillions 29:26 Is SaaS dead 31:57 Discovery as the real value layer 36:28 How Circle curated its marketplace 41:23 Why it has to run on stablecoins 46:00 Cash App to agent in one second 49:38 Where the alpha is, trading on Robinhood 52:08 Try it yourself

Shoal Research

20,578 просмотров • 1 месяц назад

My first interview with Lulu Cheng Meservey, Founder of Rostra. 0:07 How to Destroy a Terrorist Group 3:01 What Makes a Great Cult Leader 4:42 Unleashing Palmer Luckey 7:34 Why Elon Is Unpredictable 10:41 Demanding a Hardcore Culture After the X Acquisition 13:41 How Napoleon Rallied Troops to Volunteer for a Suicide Mission 18:24 Choosing Who to Alienate 20:59 Picking Someone to Fight For 22:59 Deterrence and Shaping Incentives 25:19 Why Google Had an Activist Problem 29:12 Tyrant Mode: Stopping a Leaky Culture 32:11 Building Loyalty 35:58 Why Visuals Are So Powerful 37:40 Time to Train AlexNet: Jensen Huang and Inventing Metrics 39:36 Why People Root for You 42:15 Recruit Based on the Spirit Not the Letter 43:20 The Three Levels of Story 51:01 Secret Truths and Trusting Yourself 55:25 Cicero’s Impossible Trial 58:11 Offense vs Defense 1:03:44 The Roman Concept of Auctoritas
1:05:25

My first interview with Lulu Cheng Meservey, Founder of Rostra. 0:07 How to Destroy a Terrorist Group 3:01 What Makes a Great Cult Leader 4:42 Unleashing Palmer Luckey 7:34 Why Elon Is Unpredictable 10:41 Demanding a Hardcore Culture After the X Acquisition 13:41 How Napoleon Rallied Troops to Volunteer for a Suicide Mission 18:24 Choosing Who to Alienate 20:59 Picking Someone to Fight For 22:59 Deterrence and Shaping Incentives 25:19 Why Google Had an Activist Problem 29:12 Tyrant Mode: Stopping a Leaky Culture 32:11 Building Loyalty 35:58 Why Visuals Are So Powerful 37:40 Time to Train AlexNet: Jensen Huang and Inventing Metrics 39:36 Why People Root for You 42:15 Recruit Based on the Spirit Not the Letter 43:20 The Three Levels of Story 51:01 Secret Truths and Trusting Yourself 55:25 Cicero’s Impossible Trial 58:11 Offense vs Defense 1:03:44 The Roman Concept of Auctoritas

Ti Morse

314,725 просмотров • 2 месяцев назад