George Cheng

OpenAI Just Hired Its Second Sales Chief in Nine Months. Watch the Org Chart, Not the Benchmarks.

On Wednesday OpenAI replaced its chief revenue officer, Denise Dresser, after nine months on the job and handed the role to Dali Rajic, the president and chief operating officer of Wiz. The press release language was the usual polish about helping businesses realize the full value of AI. Founders should

The Vendor Lock-In Clock Is Ticking: Run One Self-Hosted Open Model Workflow Before Year End

Here is a gap that should bother you. 81 percent of enterprises say AI vendor lock-in is a real risk. 6 percent have done anything about it. Analysts are calling lock-in the most underestimated operational risk in enterprise AI in 2026, and the survey data says they are

The Frontier Premium Is Collapsing. Here Is What to Build When a $0.10 Open Model Matches a $10 Closed One.

Look at the price sheet for August 2026. DeepSeek V4 Flash serves input tokens at $0.14 a million. DeepSeek V4 Pro sits at $0.435 in and $0.87 out after a 75 percent cut. Kimi K3, a 2.8 trillion parameter model that tops the coding leaderboards, is

Meta Open-Weighting Its Best Model Is Not Generosity. It Is the Smartest Scorched-Earth Strategy in AI.

On August 10, Meta released Muse Glimmer, an open version of Muse Spark, the most powerful model it has ever built. Spark debuted in July as a closed model, and a lot of people took that as the end of Meta's open-weights era. Five weeks later, here

The Agent Framework Gold Rush Looks Exactly Like the JS Framework Wars. Most of It Will Be Dead in 18 Months.

There is a Reddit thread making the rounds that compares agent frameworks. It covers more than twenty of them. LangChain, LangGraph, LlamaIndex, Haystack, Semantic Kernel, Pydantic AI, DSPy, Mastra, AutoGen, CrewAI, MetaGPT, the OpenAI Agents SDK, Google ADK, Strands Agents, CAMEL, AutoGPT, AgentScope, DeerFlow, and the list keeps scrolling. Every

'AI-First Founder' Is Already a Meaningless Label. Here Is What Actually Differentiates Founders in 2026.

Somewhere in the last eighteen months, 'AI-first' completed the full hype-word life cycle. Fresh, then fashionable, then mandatory, then meaningless. Record time. An investor at Sopra Steria's venture arm put it plainly: they now have to differentiate between 'a SaaS company augmented by

Speed of Iteration Beats Quality of First Draft. Nvidia's One-Week Industry Group Just Proved It.

In late July, Nvidia launched the Open Secure AI Alliance with Microsoft, SpaceX, IBM, and Palantir as founding members. Within days the group swelled past 30 companies, pulling in Adobe, BlackRock, Cisco, Intel, and Visa. One week later, TechCrunch ran this headline: 'Nvidia doesn't mess around: A

AI Captured Half of All Startup Funding. That Makes This the Worst Time to Pitch AI and the Best Time to Pitch a Boring Problem.

AI took nearly half of all global startup funding in 2025. That is $202.3 billion out of roughly $425 billion, up from 34 percent in 2024. Q1 2026 pushed the AI share to something like 80 percent of new capital. The OECD, being the OECD, framed 2025 more conservatively

Nine Open-Weight Releases in Twelve Days: Western Labs Finally Learned What Chinese Labs Knew. Open Weights Are a Go-to-Market Strategy, Not Charity.

Nine open-weight models shipped in twelve days this July. The headliner was Thinking Machines' Inkling, a 975 billion parameter model released with weights on day one, from a lab that could have charged rent on a closed API and chose not to. Five different vendors put frontier or

The Best Contrarian Founder Bet in 2026 Is Boring: Build on Open Weights and Let the Frontier Labs Subsidize Your R&D

Every founder I meet wants the glamorous bet. Build the next lab. Raise the megaround. Chase the frontier. I want to make the case for the opposite, the bet nobody brags about at dinner: build your product on open weights and let the richest companies in history pay for your

Open Weights With a License Attached Is Not Open Source. Kimi K3 Just Proved the Point.

On July 27, Moonshot released the full weights for Kimi K3. All 2.8 trillion parameters, 104 billion active. The benchmarks are real, the model is a monster, and the download is free. What it is not, despite what half the coverage says, is open source. K3 shipped under a

'Open Weights' Is Not 'Open Source.' Founders Betting Their Stack on the Difference Will Get Burned.

Let me be clear about where I stand before I say anything else. I build on open models. I want them to win. The strongest argument for open AI is that it lets people like us build companies without asking a lab for permission. This piece is not against open