app01 Thu, 22 Oct 2026 09:31:08 +0000 Fireside (https://fireside.fm) Valley101 - Episodes Tagged with “Business” https://valley101.fireside.fm/tags/business Wed, 21 Oct 2026 18:45:00 -0700 Valley101 is an independent media that tells deeply reported stories about the people, companies, and technologies shaping the future. We cover AI, semiconductors, startups, and the global technology industry through documentaries, explainers, and conversations with the people building it. Subscribe for more stories from Silicon Valley and beyond. Contact: video@sv101.net en-us episodic Stories and people shaping frontier tech, from the heart of Silicon Valley. Valley101,Inc Valley101 is an independent media that tells deeply reported stories about the people, companies, and technologies shaping the future. We cover AI, semiconductors, startups, and the global technology industry through documentaries, explainers, and conversations with the people building it. Subscribe for more stories from Silicon Valley and beyond. Contact: video@sv101.net no SiliconValley, tech, AI, business Valley101,Inc liuhj60@gmail.com Episode 2: Inside OpenClaw Foundation with Vincent Koc: Post-Claw Era, "Chinese Aunties", and Agent Sensation https://valley101.fireside.fm/2 4e277cde-db4f-430b-973b-6f1bdd24c6c1 Wed, 21 Oct 2026 18:45:00 -0700 Valley101,Inc full 1 Valley101,Inc In the post-Claw era, the agent landscape is already being rewritten. The bigger question is: when will the "Aha moment" arrive for personal AI? 1:04:18 no <p><em>Silicon Valley 101 premieres on <a href="https://www.youtube.com/watch?v=MTqNYdv" rel="nofollow noopener">YouTube</a> on July 22, 2026.</em></p> <p>The OpenClaw hype may have cooled, but we JUST stepped into AI's Agentic era. </p> <p>At WAIC 2026 in Shanghai, we sat down with Vincent Koc, Chief Architect of the OpenClaw Foundation, to revisit the open-source AI agent framework that took the global AI community by storm, drove Mac minis to sell out in China, and triggered intense debate over AI safety, security, and control.</p> <p>Vincent reveals what happened after the viral frenzy and the so-called “uninstall wave”: OpenClaw’s weekly NPM downloads actually climbed from 2.5 million to a record 4.2 million. Behind that growth are two very different forces—Chinese companies pushing employees to adopt AI agents through automation-driven KPIs, and Western users quietly bringing agent tools into the workplace from the bottom up.</p> <p>Our conversation also explores what happened after OpenClaw founder Peter Steinberger joined OpenAI. Rather than being absorbed into a single company, OpenClaw moved into an independent nonprofit foundation intended to preserve the project’s open-source identity. Peter continues to provide technical stewardship, while the Foundation has taken on the work of keeping the project alive.</p> <p>In the post-Claw era, the agent landscape is already being rewritten. The bigger question is: when will the "Aha moment" arrive for personal AI? </p> <p>Timeline: <br> 00:00 Conversation with Vincent Koc, Chief Architect of the OpenClaw Foundation<br> 02:15 The OpenClaw Craze<br> 03:41 Working with Peter Steinberger<br> 04:26 Dealing with 13,000 PRs<br> 07:44 The China Sensation <br> 10:56 The Cooldown and the “Post-Claw Era”<br> 14:28 Big Tech’s Claw Experiments<br> 20:47 The Biggest Challenges Today<br> 23:23 The Gateway Architecture<br> 24:45 Defining Security Boundaries<br> 28:33 The Models and Frameworks Behind AI Agents<br> 32:09 The Memory Problem<br> 34:34 Multi-Agent Coordination<br> 35:41 Conway’s Law<br> 40:09 Why the Agent “Aha Moment” Hasn’t Arrived<br> 41:37 Lessons from the Cooldown<br> 43:09 The Enterprise–Personal Agent Growth Flywheel<br> 44:28 OpenClaw’s App Strategy<br> 48:04 Hermes Agent<br> 51:00 OpenClaw Foundation<br> 55:08 Hiring <br> 55:52 Decision Making<br> 57:40 Peter Joined OpenAI<br> 01:00:55 Staying Open Source: The Only Way to “Give It to the World”</p> tech, AI, OpenClaw, Agent, VincentKoc Silicon Valley 101 premieres on YouTube on July 22, 2026.

The OpenClaw hype may have cooled, but we JUST stepped into AI's Agentic era.

At WAIC 2026 in Shanghai, we sat down with Vincent Koc, Chief Architect of the OpenClaw Foundation, to revisit the open-source AI agent framework that took the global AI community by storm, drove Mac minis to sell out in China, and triggered intense debate over AI safety, security, and control.

Vincent reveals what happened after the viral frenzy and the so-called “uninstall wave”: OpenClaw’s weekly NPM downloads actually climbed from 2.5 million to a record 4.2 million. Behind that growth are two very different forces—Chinese companies pushing employees to adopt AI agents through automation-driven KPIs, and Western users quietly bringing agent tools into the workplace from the bottom up.

Our conversation also explores what happened after OpenClaw founder Peter Steinberger joined OpenAI. Rather than being absorbed into a single company, OpenClaw moved into an independent nonprofit foundation intended to preserve the project’s open-source identity. Peter continues to provide technical stewardship, while the Foundation has taken on the work of keeping the project alive.

In the post-Claw era, the agent landscape is already being rewritten. The bigger question is: when will the "Aha moment" arrive for personal AI?

Timeline:
00:00 Conversation with Vincent Koc, Chief Architect of the OpenClaw Foundation
02:15 The OpenClaw Craze
03:41 Working with Peter Steinberger
04:26 Dealing with 13,000 PRs
07:44 The China Sensation
10:56 The Cooldown and the “Post-Claw Era”
14:28 Big Tech’s Claw Experiments
20:47 The Biggest Challenges Today
23:23 The Gateway Architecture
24:45 Defining Security Boundaries
28:33 The Models and Frameworks Behind AI Agents
32:09 The Memory Problem
34:34 Multi-Agent Coordination
35:41 Conway’s Law
40:09 Why the Agent “Aha Moment” Hasn’t Arrived
41:37 Lessons from the Cooldown
43:09 The Enterprise–Personal Agent Growth Flywheel
44:28 OpenClaw’s App Strategy
48:04 Hermes Agent
51:00 OpenClaw Foundation
55:08 Hiring
55:52 Decision Making
57:40 Peter Joined OpenAI
01:00:55 Staying Open Source: The Only Way to “Give It to the World”

]]> Silicon Valley 101 premieres on YouTube on July 22, 2026.

The OpenClaw hype may have cooled, but we JUST stepped into AI's Agentic era.

At WAIC 2026 in Shanghai, we sat down with Vincent Koc, Chief Architect of the OpenClaw Foundation, to revisit the open-source AI agent framework that took the global AI community by storm, drove Mac minis to sell out in China, and triggered intense debate over AI safety, security, and control.

Vincent reveals what happened after the viral frenzy and the so-called “uninstall wave”: OpenClaw’s weekly NPM downloads actually climbed from 2.5 million to a record 4.2 million. Behind that growth are two very different forces—Chinese companies pushing employees to adopt AI agents through automation-driven KPIs, and Western users quietly bringing agent tools into the workplace from the bottom up.

Our conversation also explores what happened after OpenClaw founder Peter Steinberger joined OpenAI. Rather than being absorbed into a single company, OpenClaw moved into an independent nonprofit foundation intended to preserve the project’s open-source identity. Peter continues to provide technical stewardship, while the Foundation has taken on the work of keeping the project alive.

In the post-Claw era, the agent landscape is already being rewritten. The bigger question is: when will the "Aha moment" arrive for personal AI?

Timeline:
00:00 Conversation with Vincent Koc, Chief Architect of the OpenClaw Foundation
02:15 The OpenClaw Craze
03:41 Working with Peter Steinberger
04:26 Dealing with 13,000 PRs
07:44 The China Sensation
10:56 The Cooldown and the “Post-Claw Era”
14:28 Big Tech’s Claw Experiments
20:47 The Biggest Challenges Today
23:23 The Gateway Architecture
24:45 Defining Security Boundaries
28:33 The Models and Frameworks Behind AI Agents
32:09 The Memory Problem
34:34 Multi-Agent Coordination
35:41 Conway’s Law
40:09 Why the Agent “Aha Moment” Hasn’t Arrived
41:37 Lessons from the Cooldown
43:09 The Enterprise–Personal Agent Growth Flywheel
44:28 OpenClaw’s App Strategy
48:04 Hermes Agent
51:00 OpenClaw Foundation
55:08 Hiring
55:52 Decision Making
57:40 Peter Joined OpenAI
01:00:55 Staying Open Source: The Only Way to “Give It to the World”

]]> Episode 6: Flash Models, Bullish on SaaS, and the RSI Reality Check | Richard Bian, Ant Group https://valley101.fireside.fm/6 c936afcc-4194-4b54-8d16-cc3c8c8e2b42 Wed, 21 Oct 2026 07:45:00 -0700 Valley101,Inc full 1 Valley101,Inc Why build specialized models when general AI keeps improving? 1:05:52 no <p>Richard Sikang Bian is the Head of Product and Operations for Ant Ling, the foundational LLM at Ant Group's InclusionAI lab. He leads the “Model as a Product” team, helping turn AI research into tools developers and businesses can use. <br> In this conversation, Richard explains Ant Ling’s investment in Flash models and specialized capabilities for finance and health, and why he thinks many general models are “intelligent at everything, but they specialize in nothing.”<br> We discuss:<br> • Why build specialized models when general AI keeps improving?<br> • What Flash means and how capability, speed, and cost fit together.<br> • Why Richard remains bullish on SaaS in the age of AI agents.<br> • What benchmarks reveal—and miss—about real-world performance.<br> • AI safety and the missing pieces behind recursive self-improvement.<br> This podcast was recorded in mid-September, after the release of Ling-3.0-flash-Fin, an open-weight model trained on specialized financial data. Since the recording, Ant Group has released the model weights for Ling-3.1-flash.</p> <p>Timestamps:<br> 00:00 China’s Proposed AI Export Controls<br> 02:54 Richard Bian, Ant Ling<br> 03:35 From Trillion-Parameter Models to Domain Enhancement<br> 07:49 Why Build Flash Models?<br> 15:53 Bullish on SaaS<br> 23:50 Turning AI Into an Enterprise Product<br> 27:00 Coding and Cowork Agents<br> 32:24 Finance, Healthcare, and Real-World Benchmarks<br> 37:23 Can We Trust AI Benchmarks?<br> 43:48 US and China data market and brokers<br> 50:13 AI Safety and Open Models<br> 59:38 What’s Missing From Self-Improving AI?</p> <p><em>Watch the video edition of this episode on our YouTube channel <a href="https://www.youtube.com/watch?v=wxSjg9Cd18A" rel="nofollow noopener">Silicon Valley 101.</a></em></p> <p>About Valley101:<br> Valley101 is an independent media that tells deeply reported stories about the people, companies, and technologies shaping the future. We cover AI, semiconductors, startups, and the global technology industry through documentaries, explainers, and conversations with the people building it.</p> <p>Subscribe for more stories from Silicon Valley and beyond.</p> <p>Contact: <a href="mailto:video@sv101.net" rel="nofollow noopener">video@sv101.net</a></p> SiliconValley, tech, AI, business Richard Sikang Bian is the Head of Product and Operations for Ant Ling, the foundational LLM at Ant Group's InclusionAI lab. He leads the “Model as a Product” team, helping turn AI research into tools developers and businesses can use.
In this conversation, Richard explains Ant Ling’s investment in Flash models and specialized capabilities for finance and health, and why he thinks many general models are “intelligent at everything, but they specialize in nothing.”
We discuss:
• Why build specialized models when general AI keeps improving?
• What Flash means and how capability, speed, and cost fit together.
• Why Richard remains bullish on SaaS in the age of AI agents.
• What benchmarks reveal—and miss—about real-world performance.
• AI safety and the missing pieces behind recursive self-improvement.
This podcast was recorded in mid-September, after the release of Ling-3.0-flash-Fin, an open-weight model trained on specialized financial data. Since the recording, Ant Group has released the model weights for Ling-3.1-flash.

Timestamps:
00:00 China’s Proposed AI Export Controls
02:54 Richard Bian, Ant Ling
03:35 From Trillion-Parameter Models to Domain Enhancement
07:49 Why Build Flash Models?
15:53 Bullish on SaaS
23:50 Turning AI Into an Enterprise Product
27:00 Coding and Cowork Agents
32:24 Finance, Healthcare, and Real-World Benchmarks
37:23 Can We Trust AI Benchmarks?
43:48 US and China data market and brokers
50:13 AI Safety and Open Models
59:38 What’s Missing From Self-Improving AI?

Watch the video edition of this episode on our YouTube channel Silicon Valley 101.

About Valley101:
Valley101 is an independent media that tells deeply reported stories about the people, companies, and technologies shaping the future. We cover AI, semiconductors, startups, and the global technology industry through documentaries, explainers, and conversations with the people building it.

Subscribe for more stories from Silicon Valley and beyond.

Contact: video@sv101.net

]]> Richard Sikang Bian is the Head of Product and Operations for Ant Ling, the foundational LLM at Ant Group's InclusionAI lab. He leads the “Model as a Product” team, helping turn AI research into tools developers and businesses can use.
In this conversation, Richard explains Ant Ling’s investment in Flash models and specialized capabilities for finance and health, and why he thinks many general models are “intelligent at everything, but they specialize in nothing.”
We discuss:
• Why build specialized models when general AI keeps improving?
• What Flash means and how capability, speed, and cost fit together.
• Why Richard remains bullish on SaaS in the age of AI agents.
• What benchmarks reveal—and miss—about real-world performance.
• AI safety and the missing pieces behind recursive self-improvement.
This podcast was recorded in mid-September, after the release of Ling-3.0-flash-Fin, an open-weight model trained on specialized financial data. Since the recording, Ant Group has released the model weights for Ling-3.1-flash.

Timestamps:
00:00 China’s Proposed AI Export Controls
02:54 Richard Bian, Ant Ling
03:35 From Trillion-Parameter Models to Domain Enhancement
07:49 Why Build Flash Models?
15:53 Bullish on SaaS
23:50 Turning AI Into an Enterprise Product
27:00 Coding and Cowork Agents
32:24 Finance, Healthcare, and Real-World Benchmarks
37:23 Can We Trust AI Benchmarks?
43:48 US and China data market and brokers
50:13 AI Safety and Open Models
59:38 What’s Missing From Self-Improving AI?

Watch the video edition of this episode on our YouTube channel Silicon Valley 101.

About Valley101:
Valley101 is an independent media that tells deeply reported stories about the people, companies, and technologies shaping the future. We cover AI, semiconductors, startups, and the global technology industry through documentaries, explainers, and conversations with the people building it.

Subscribe for more stories from Silicon Valley and beyond.

Contact: video@sv101.net

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