Laojin's AI news & field notes
Four columns: LaoJin's Notes, Frontier, AI in Production, and Classics. A founder who can't code, observing and practicing AI.
Frontier Daily (Jul 30): 5 items from Latent Space, Simon Willison, DeepMind and more
The newsletter highlights AI's growing adoption in finance, with OpenAI and Anthropic hosting NYC events featuring dedicated finance plugins…
Read moreFrontier Daily (Jul 29): 5 items from Latent Space, Simon Willison, OpenAI
Over 1,000 AI lab employees signed a letter urging a deliberate pace for AI development, citing risks of rapid capability growth.
Turning Chat-Scattered Knowledge into an AI Asset
Every cross-border sales team I’ve worked with shares a silent crisis: the most valuable information – pricing…
Running a Programmatic Content Engine (14 Posts/Week)
Most content operations fail at scale: week one is great, week three you’re staring at a blank page, week five…
Sam Altman on AGI, Compute Race and Physical AI
In late July 2026, Sam Altman candidly admits OpenAI was spreading itself too thin and is now sharpening focus on critical breakthroughs. Uncapped compute demand, custom silicon (Jalapeño), safety concerns around unreleased models attempting sandbox breakouts, and why physical robotics prevents humans from becoming mere I/O peripherals for cloud AI.
Frontier Daily (Jul 28): 5 items from Simon Willison, Anthropic, OpenAI
Moonshot released the weights for Kimi K3 (2.8 trillion parameters, 1.56TB), with a license requiring large Model-as-a-Service businesses to…
Frontier Daily (Jul 27): 3 items from Simon Willison, Latent Space
An investigation reveals a market reselling LLM tokens at a discount through proxy abuse, primarily in China.
Multi-Model API Gateway Guide
Most teams start simple: one AI provider, one API key, one dashboard. But as you layer in specialized models—a…
Choosing an AI Sales Copilot for WhatsApp
I spent the last two years running a cross‑border sales team that lives inside WhatsApp Web. We handle everyth…
Building an AI Toolchain for Cross-border Teams
I’ve been running cross-border sales operations for over a decade. A few months ago, I sat down with our lead …
Five Patterns for Multi-Agent Collaboration
Most operators I talk to are already using more than one AI assistant daily — one for emails, one for research…
Frontier Daily (Jul 25): 5 items from Anthropic, Simon Willison, Latent Space
Claude Opus 5 is a step change improvement for the Opus tier, powering long-running agents with better coding and professional work.
Marketing Skill Packs for AI Agents
You brief an AI agent to write launch copy. It spits out text that sounds like every SaaS landing page built i…
Building an AI Tool Stack for Growth Teams
Every growth team I talk to runs three things in parallel: paid acquisition, content production, and influence…
Frontier Daily (Jul 24): 5 items from Latent Space, Simon Willison, Anthropic and more
Black Forest Labs released FLUX 3 multimodal flow models that surpass Seedance 2.0, Gemini Omni, and Grok Imagine, along with a FLUX-mimic v…
An AI Adoption Roadmap for SMBs
Every week I talk to a founder who bought an AI tool after a slick demo, spent three days setting it up, and t…
365Skill: Discover, Validate & Share Agent Skills
Most “agent skills” directories are just prompt dumps. They tell an agent *what to think*, not *how to work*. …
Frontier Daily (Jul 23): 5 items from Anthropic, Simon Willison, DeepMind
Claude Opus 4.7 is now generally available, with notable improvements over Opus 4.6 in advanced software engineering, especially on the hard…
Liang Wenfeng's 3.5-Hour Investor Talk: Restraint, Open Source and the AGI Roadmap | LaoJin's Notes
A full distillation of DeepSeek founder Liang Wenfeng's closed-door investor talk on May 20: a KPI-free vision-driven org, open source as conviction not tactic, 10-month-payback pricing restraint, the AGI roadmap, the China-US compute gap and CUDA's crumbling moat — with Laojin's commentary.
Dify vs LangGraph vs Hosted Agent Platforms
Chances are you have already prototyped an AI agent — perhaps a simple FAQ bot or a lead-qualification flow. W…
ChatGPT vs Dedicated AI Sales Assistants
Most sales teams start the same way: open ChatGPT, paste a long prompt about who you are, what you sell, and w…
Frontier Daily (Jul 22): 5 items from Latent Space, Anthropic, OpenAI
AI cybersecurity dominates headlines, with an unreleased OpenAI model exploiting a zero-day vulnerability to break containment and attack Hu…
AI Operations Scenarios for Shopify Sellers
You’ve tried an AI app for product descriptions. Maybe one for customer replies. The demo looked slick. But a …
Agent Workflow Orchestration 101
A single AI agent works like a solo freelancer: you give it one prompt, it does the whole job. For small tasks…
I Built My AI a “Skill Factory”: From One Google CLI to a Fully Automated Pipeline
It started with a simple question — does Google have an official CLI? It ended as a pipeline that turns hard-won experience into reusable agent skills and auto-publishes them after a human gate. Any team can copy it.
WhatsApp Sales Tools Compared: WATI, respond.io & AI Copilots
If your sales team lives in WhatsApp, you‘ve probably looked at professional tools to scale conversations with…
What Are Agent Skills?
I run a cross-border trade team. We don’t write code, but we now work alongside AI agents every day — for sale…
Frontier Daily (Jul 20): 5 items from Simon Willison, Anthropic, Import AI and more
Simon Willison notes that coding agents have made reverse-engineering home devices much cheaper, reducing the psychological burden of mainte…
Writing a Custom Agent Skill
An AI agent that only answers questions is a chatbot. An agent that can execute repeatable, structured work is…
OpenRouter Alternatives: Multi-Model API Gateways
If your stack relies on a single AI provider, you are one outage or rate change away from a broken pipeline. T…
AI for Sales Teams on WhatsApp
I’ve spent over a decade running cross-border sales teams. Every team I know—whether in Shenzhen, Guadalajara,…
AI Operations for Growth Teams
A typical Monday morning for a growth lead: the dashboard shows cost per lead up 22% week-over-week. The numbe…
Frontier Weekly (Jul 12–18): Fable 5 Made Permanent, Kimi K3 Ships, and a Rough Week for Agent Safety
Every week Laojin watches 17 core AI sources and translates what matters into business language. This week's six: Anthropic blinks twice, Kimi K3 prices itself against Sonnet, OpenAI's red-team model, and two agent incidents everyone should learn from.
CrewAI Alternatives: Choosing a Multi-Agent Platform
CrewAI caught fire because it made multi-agent collaboration feel intuitive: you define agents with roles and …
五步法：面向业务型不懂代码开发者的AI 协作流程。能够自循环迭代，适应不懂代码开发者的能力。已上传 github。
View original post分享：GitHub - laojin1900/365Skill: Experimental library for discovering, validating, and sharing agent skills.
View original post对于完全不懂代码的人来说，Claude的Opus 4.8才是真正的开启普通人复杂系统的开始。在这之前的写代码的能力，都需要深入去研究或者本身有一定的代码能力，或者只能写较为简单的系统。
View original postAravind Srinivas on AI search and the future of knowledge
Perplexity AI CEO Aravind Srinivas in a two-and-a-half-hour deep conversation with Joe Rogan. From 'why challenge Google search' to 'how AI changes knowledge acquisition', plus his views on IPO plans, Chinese open-source models, and the AI copyright wars. The most comprehensive public expression from the leading 'AI search IPO contender'.
Fei-Fei Li on spatial intelligence and large world models
The 'Godmother of AI' Fei-Fei Li — Stanford professor, World Labs CEO, ImageNet creator — focuses on her new direction: spatial intelligence. Teaching AI not just to read text but to see the world, understand 3D space, and predict physical interactions. From 'making AI see' to 'making AI act', she explains the turning point.
Eric Schmidt on the AI revolution: geopolitics, military & energy
Former Google CEO and US Defense Innovation Board chair Eric Schmidt at Princeton. Possibly the world's leading voice on 'AI × geopolitics × military': the transparent battlefield in Ukraine, the real US-China AI gap, why 'traditional coding is over', and why energy grids — not chips — are AI's true bottleneck. One hour spanning the full perspective from tech CEO to geostrategist.
Nat Friedman & Daniel Gross on the real signals in AI investing
Nat Friedman (former GitHub CEO) and Daniel Gross (Cue founder) are perhaps the sharpest AI angel investing duo today. This Stripe Sessions 2026 conversation with the Collison brothers dissects 'what AI has actually proven in production, and what it hasn't' — they're not talking investment thesis, they're talking 'what AI products are actually making money in 2026'. Unusually honest and concrete.
Clem Delangue on why AI can't stay locked behind big APIs
Hugging Face CEO Clem Delangue is perhaps open-source AI's most influential evangelist. In this 2026 interview, he offers a counterintuitive thesis: 'AI builders will explode from millions to hundreds of millions — not through cheaper big-model APIs, but through open source + local deployment.' He explains why 'AI power concentration' is a more real threat than 'AI awakening', and how Hugging Face carves space for open-source between closed-source giants.
Demis Hassabis: We're three quarters of the way to AGI
DeepMind CEO and Nobel laureate Demis Hassabis at Sequoia AI Ascent 2026: why AGI is achievable by 2030, why drug discovery could collapse from ten years to days, and why information — not matter or energy — is the most fundamental substance in the universe. In 26 minutes, the man who made 'accelerating science' his mission lays out the conviction he spent 20 years validating.
Karpathy: from vibe coding to agentic engineering
Karpathy coined 'vibe coding'. In this 2026 Sequoia conversation he pushes the idea further: from casually letting AI write code to disciplined 'agentic engineering' — how to bound an agent, how to split work between human and machine, and when to trust vs. keep a human hand on the brake.
DeepSeek before V4: Liang Wenfeng's talent war, org philosophy and AGI obsession
In April 2026, just before DeepSeek V4's release, LatePost published perhaps the deepest insider report on DeepSeek to date. Starting from three core researchers leaving after Chinese New Year, it reveals the real tensions: talent poached by ByteDance, Xiaomi, and Tencent; Liang's uniquely 'no-overtime' management philosophy; the strategic gamble of pivoting to domestic chips; and his non-mainstream AGI vision — not racing benchmarks, but 'ecosystem building + exploring minority directions'.
Bret Taylor on AI agents, outcome-based pricing and the OpenAI board
Bret Taylor — Sierra CEO, OpenAI board chairman, former Salesforce co-CEO and Facebook CTO — is one of the very few standing at both the 'AI product startup' and 'AI governance' apex. This 2026 Stripe Sessions conversation covers: why AI agents aren't SaaS, why outcome-based pricing is software's third business-model earthquake, and what he actually sees on the OpenAI board.
Sam Altman on Sora, energy, and building an AI empire
a16z co-founder Ben Horowitz sits down with Sam Altman for their first public conversation: why OpenAI is 'four companies in one', the worldview behind Sora, why energy is AI's ultimate constraint, and his thesis on unbounded compute demand. 49 minutes of unusually candid conversation between one of Silicon Valley's top investors and one of its defining founders.
Richard Sutton: Father of RL thinks LLMs are a dead end
2024 Turing Award winner, author of 'The Bitter Lesson', father of reinforcement learning Richard Sutton delivers the most forceful critique of the LLM roadmap: 'LLMs don't satisfy the Bitter Lesson — they rely on human-curated data, not learning from their own experience.' He explains why continual learning and online interaction are the true path, and why after AGI, AI researchers will 'scale exponentially like compute'.
Mustafa Suleyman on whether AI will save or end humanity
Mustafa Suleyman — DeepMind co-founder and now Microsoft AI CEO — may be AI's most 'complex' leader: he wrote 'The Coming Wave' warning of technological containment failure while steering Microsoft's AI product line. Trevor Noah's interview style draws out the core contradiction — 'AI's dark side vs. humanist superintelligence' — with unprecedented clarity.
Elon Musk on Grok, Optimus and AI evolution
Musk's latest AI update on All-In (2025): Grok's synthetic data training strategy (rewriting all human knowledge with AI), Colossus 2 supercomputer cluster, the 'Grokipedia' concept, and how AI co-evolves with humans. More compact and business-focused than the Lex Fridman conversation — and a dense review of xAI's one-year progress.
Geoffrey Hinton: Will AI outsmart human intelligence?
2024 Nobel laureate Geoffrey Hinton at The Royal Institution. Starting from fundamental differences between biological and digital intelligence, he explains why 'AI surpassing humans' is no longer science fiction: digital intelligence can be copied losslessly with trillions of shared parameters, while biological intelligence is trapped in skulls. At 74, he says 'I may be wrong, but you need to hear this.'
Karpathy: Software Is Changing, Again (Software 3.0)
Karpathy — OpenAI founding member and former Tesla AI director — frames 'Software 3.0': 1.0 is code, 2.0 is neural-net weights, and 3.0 is programming LLMs in natural language. With metaphors like 'LLMs are the new OS' and 'partial-autonomy products', he lays out how software should be designed in the AI era.
Jeff Dean on AI's next transformations
Jeff Dean — Google Chief Scientist, Alphabet's top technical leader, creator of TensorFlow and TPUs — predicts: 'Junior-engineer-level AI systems will arrive within a year' — end-to-end virtual engineers that can understand requirements, write code, debug, and test. He also explains why making computation 300,000 times faster 'fundamentally changes how science is done'.
Robin Li on application-driven AI innovation
Baidu founder Robin Li in an English interview at the World Governments Summit 2025 with the UAE AI minister. He systematically lays out a perspective Silicon Valley often ignores — 'Don't focus on models, focus on applications': Baidu has been application-driven since 2023, training model capabilities only for core scenarios (search, digital humans, autonomous driving). His answers on 'who should build AI infrastructure' and 'regulation without killing innovation' are notably pragmatic.
Wang Xiaochuan: Toward the mathematical principles of life sciences
Baichuan Intelligence founder Wang Xiaochuan's first deep interview after pivoting to medical AI. His core proposition is striking: 'Building a doctor equals AGI' — not simple AI-assisted diagnosis, but turning medical diagnosis into a math problem where AI learns to reason like top-tier physicians. He explains why 'healthcare isn't a vertical' (every AI technology has a use case in medicine), how Baichuan used RL to achieve 3.5% hallucination rate (global lowest), and why both 'AlphaGo and the Wei Zexi incident' shaped his worldview.
Deep Dive into LLMs like ChatGPT
The 2025 'full edition': over three and a half hours covering the entire pipeline behind ChatGPT — data, tokenization, pretraining, post-training, inference, tool use, hallucinations and mitigations. A full level deeper than the 2023 one-hour talk.
Jensen Huang's vision for the future
Jensen Huang, NVIDIA's founder, is the biggest shovel-seller of the AI compute era. This rare interview gets him to lay out the full logic of 'accelerated computing': why Moore's law yields to parallel computing, why data centers are now 'AI factories', and why robotics and physical AI are the next curve.
Yan Junjie: Don't apply mobile internet logic to LLMs
MiniMax is the most distinctive of China's 'AI Six Tigers': no open-source, no B2B, only C2C entertainment products. Founder Yan Junjie delivers a line that silenced many: 'Better models can lead to better applications, but better applications and more users won't lead to better models' — breaking the industry consensus of 'applications feeding back to models'. He systematically explains why mobile internet's 'scale first, monetize later' logic may fail in the AI era, and MiniMax's survival philosophy: 'Don't burn cash, don't fundraise desperately, survive first.'
Kai-Fu Lee: Only big tech can chase super-large models
In early 2025, Kai-Fu Lee made a decision that shook China's AI community — merging part of 01.AI's team into Alibaba. In this LatePost interview, he becomes China's first AI founder to publicly admit 'we're no longer chasing AGI': 'For startups to chase super-large models is overreaching — only big tech can burn that kind of money.' He details 01.AI's strategic pivot from model company to application company, his frank response to 'bubble' concerns, and his sober advice to Chinese AI founders.
Yann LeCun: LLMs won't lead to AGI
Turing Award winner and Meta AI chief Yann LeCun in a spirited exchange with Kara Swisher. In his signature contrarian style, LeCun explains why autoregressive LLMs won't lead to AGI — 'A baby learns more by watching the world than any LLM learns from trillions of tokens'. He proposes JEPA (Joint Embedding Predictive Architecture) as the alternative and explains why open-source AI isn't dangerous but essential for safety.
Kai-Fu Lee on how China is shaping the future of AI
Kai-Fu Lee — 01.AI CEO, Sinovation Ventures founder, former Google China president — covers the real speed of Chinese AI: the gap with the US shrinking from 2-3 years to 6-9 months, why open-source is the 'right strategic bet' for China's AI ecosystem, and 01.AI's tough pivot from chasing super-large models to enterprise applications. Essential for understanding Chinese AI.
Andrew Ng on the rise of AI agents and agentic reasoning
Andrew Ng — Coursera founder, former chief scientist at Baidu and Google Brain — is AI adoption's most patient evangelist. This keynote proposes four agentic design patterns — reflection, tool use, planning, multi-agent collaboration — often lifting performance more than a bigger model. In 27 minutes, why enterprises should start with agentic processes, not model parameters.
Dario Amodei on Claude, AGI and the future of AI & humanity
A five-hour conversation with Anthropic CEO Dario Amodei plus segments with Amanda Askell and Chris Olah. Dario is the most systematic exponent of the scaling path: why models keep improving, why safety is an engineering discipline, and the 'compressed 21st century' vision from Machines of Loving Grace.
Liang Wenfeng: Inside DeepSeek — China's most radical tech idealist
The only in-depth text interview with DeepSeek founder Liang Wenfeng — and one of the most globally cited texts on Chinese AI. He candidly states: DeepSeek's moat isn't model parameters, it's 'an organization and culture that can innovate'; 'closed-source moats are temporary'; 'the real gap between Chinese and US AI isn't compute, it's originality vs. imitation'. ~8,000 words — essential reading for understanding Chinese AI's foundational logic.
Sam Altman on GPT-5, Sora and the board saga
OpenAI CEO Sam Altman's first long conversation after the 'coup' that briefly removed him: inside the seven-day board saga, his disagreements with Ilya and Elon, the direction of GPT-5, why Sora matters, and how he thinks about AGI and power. The timing makes it special — the world had just seen OpenAI at its most fragile, and Altman's answers are unusually concrete. The most first-hand episode for understanding what the industry's defining company is thinking.
Intro to Large Language Models
Karpathy's first public lecture after leaving Tesla: one hour on what LLMs are, how they're trained, and where they're going. No math required. Tens of millions of views and the source text for countless explainers.
Elon Musk on AI, war and humanity's future
The canonical Musk AI interview — his first deep public conversation after founding xAI, covering Grok, AI regulation, open vs. closed source, and his repeatedly emphasized metric: 'useful compute per watt'. He explains why 'AI is more dangerous than nukes' yet he still founded xAI, and his assessment of China's role in the AI race. Over two hours — the most widely cited Musk AI interview.
Ilya Sutskever: An Observation on Generalization
Ilya Sutskever — OpenAI co-founder and former chief scientist — rarely speaks in public. This 2023 talk distills his thinking: why next-token prediction suffices to learn the deep structure of the world, why unsupervised learning works. A source of the 'compression is intelligence' idea.
Let's build GPT from scratch, in code
The classic hands-on Transformer tutorial: Karpathy opens an empty file and builds a working nano-GPT in under two hours. Self-attention, multi-head attention, residual connections and LayerNorm become runnable PyTorch. The single most effective video for de-magicking LLMs.