Simon Willison — Week of 2026-05-22 to 2026-05-29#

Highlight of the Week#

This week’s most significant milestone is the release of Datasette 1.0a31, which fundamentally shifts the project’s paradigm by introducing UI support for executing write queries directly against the database. This officially bridges Datasette from a purely read-only tool to one that embraces secure data mutation, allowing developers to save and template insert, update, and delete operations.

Key Posts#

[I think Anthropic and OpenAI have found product-market fit] · Source Simon analyzes the shift in enterprise pricing to argue that AI coding agents have crossed the threshold into massive usage and real revenue generation. He points to Anthropic’s staggering $1.25 billion monthly compute spend and notes that labs are pivoting to capture enterprise value directly from heavy agent users rather than relying on middlemen.

Tech Videos — Week of 2026-05-22 to 2026-05-29#

Watch First#

The single best video this week is “Reverse engineering a Viking VOIP phone protocol with Claude Code” by Boris Starkov from Eleven Labs. It provides a stunning, high-signal demonstration of an autonomous agent sniffing traffic and rewriting persistent memory to brute-force a hardware device, proving exactly how capable models have become at executing complex, multi-step engineering tasks.

Week in Review#

This week was heavily dominated by the maturation of AI agents, moving beyond basic text chat into structured, sandboxed integrations via the Model Context Protocol (MCP) and full GUI automation. We are witnessing a fundamental shift in daily workflows, with the terminal increasingly being bypassed in favor of IDE-embedded browsers and autonomous models generating massive, risky pull requests that demand stringent human review. Underpinning this is a ruthless optimization of infrastructure, spanning from Google splitting out specialized training and inference hardware to SpaceX aggressively cutting data center build times down to 66 days.

Tech News — Week of 2026-05-22 to 2026-05-29#

Story of the Week#

Anthropic has officially unseated OpenAI as the world’s most valuable artificial intelligence startup, closing a jaw-dropping $65 billion Series H funding round that catapults its valuation to $965 billion. This historic changing of the guard arrives alongside the launch of Claude Opus 4.8 and a novel “Dynamic Workflows” tool for orchestrating swarms of AI subagents. The massive capital influx proves that explosive enterprise demand is rapidly reshaping the generative AI hierarchy, placing Anthropic squarely in the driver’s seat for the next era of frontier model development.

Chinese Tech — Week of 2026-05-22 to 2026-05-29#

Week in Review#

The maturation of Agentic AI is fundamentally shaking up both software engineering workflows and underlying computing architectures, sparking an arms race in domestic tech infrastructure. Meanwhile, geopolitical decoupling continues to drive aggressive indigenous innovation, most notably characterized by Huawei’s new semiconductor scaling laws and BYD’s unprecedented liability guarantees for autonomous driving.

Engineering & Dev#

The rapid adoption of Agentic AI is exposing cracks in traditional ecosystems and workflows. Microsoft internally banned Claude Code out of fear of Anthropic’s dominance and soaring API costs, forcing engineers back to GitHub Copilot to artificially protect its ecosystem, while a Claude-generated PR for a Node.js virtual file system sparked intense debate over the safety of committing AI code to core infrastructure. To handle the complex orchestration, memory retrieval, and tool execution demands of these agents, Huawei is pivoting back to CPUs, positioning its Kunpeng chips for Agentic workflows while utilizing Ascend for raw inference. Domestic models are also making serious strides in this arena; Alibaba’s Qwen3.7-Max excelled in “Vibe Coding” tests, successfully generating complex web apps from single prompts and beating global models like GPT-5.5, while ModelBest released ForgeTrain, the first production-grade training framework entirely written by AI without human intervention. Finally, to solve the “Babel” of fragmented enterprise agent data, Shushi Tech and others are adopting Snowflake’s OSI standard, allowing diverse AI agents to natively query unified business metrics without hallucinating logic.

YouTube — Week of 2026-05-22 to 2026-05-29#

Watch First#

The standout video this week is a fascinating, deep-dive interview with Xpeng CEO He Xiaopeng, who argues that mapping digital AI paradigms onto the physical world is a mistake, and explains why building a general-purpose humanoid robot is exponentially harder than building an EV. It is a stark, unvarnished look at the bleeding edge of “physical AI” from one of China’s top tech executives.

AI@X — Week of 2026-05-29 to 2026-06-05#

The Buzz#

The era of unconstrained “tokenmaxxing” is officially dead, violently replaced by a brutal reckoning over AI return on investment and unsustainable infrastructure costs. As enterprises recoil from the astronomical expenses of frontier models, the industry is rapidly pivoting away from sheer scale toward strict operational efficiency, dynamic model routing, and hybrid local-cloud architectures.

Key Discussions#

• The CapEx Crisis and AI ROI: Hyperscalers are taking on record debt to fund AI infrastructure, but the anticipated financial returns are increasingly compared to the dot-com bubble. Major enterprises, including Uber, are capping generative AI spending after blowing through budgets without seeing sufficient operational savings, leading IBM’s CEO to publicly doubt if the revenue exists to pay back the trillions in necessary capex.
• Commoditization and the Rise of Model Routing: Foundational models are rapidly commoditizing as they train on the same public internet data, a reality acknowledged by Oracle’s Larry Ellison and Gary Marcus. Consequently, dynamic model routing—automatically sending high-end tasks to frontier models and simpler tasks to cheaper ones—is emerging as the definitive enterprise moat to manage surging token costs.
• Agentic Bottlenecks and Hybrid Solutions: While agent capabilities are evolving through innovations like Perplexity’s “Search-as-Code” and native Windows integrations, their enterprise adoption remains paralyzed by fragmented, undocumented institutional data. To mitigate cloud costs and latency, builders are aggressively shifting toward hybrid inference architectures that leverage local Apple Silicon alongside cloud models.
• Financial Market Turbulence and Government Entanglement: The sheer scale of AI valuations is disrupting public markets, culminating in S&P’s refusal to fast-track SpaceX’s highly hyped $1.78T IPO, which triggered a massive tech stock slide. Concurrently, proposals for the U.S. government to take a financial stake in OpenAI or grant the public 50% ownership of AI firms are sparking intense debates over bailouts and the dystopian risks of a “Central Government AI”.
• Open-Source Science vs. Structural AI Flaws: While open-weight models like ESMFold2 achieve monumental breakthroughs in mapping protein biology without massive compute, foundational consumer applications continue to expose deep reasoning vulnerabilities. These epistemic limits are starkly highlighted by ChatGPT hallucinating a global medical epidemic and physical state-tracking benchmarks like VSTAT proving that models still fail to understand basic spatial reality.

Patterns#

A clear consensus has emerged that maintaining a multi-trillion-dollar moat through closed-source, monolithic scaling is a failing business strategy. The ecosystem is fundamentally shifting its focus toward the applied application layer, recognizing that true value lies in neurosymbolic integration, intelligent workload routing, and unlocking undocumented institutional data rather than endlessly chasing the next massive parameter count.

Apple — Week of 2026-05-29 to 2026-06-05#

Week in Review#

The Apple ecosystem is intensely focused on the impending WWDC 2026, with widespread expectations of a generative AI overhaul led by a revamped Siri and critical “Snow Leopard-style” stability updates for macOS 27. On the hardware front, Apple’s budget-friendly MacBook Neo is severely disrupting the PC market with record sales, while a stream of credible leaks has painted a detailed picture of an incoming foldable “iPhone Ultra” boasting highly advanced thermal and mechanical engineering. Meanwhile, incoming leadership is reportedly enacting a massive recalibration of Apple’s spatial computing roadmap, heavily pivoting away from mixed-reality headsets toward everyday smart glasses.

Engineering Reads — Week of 2026-05-28 to 2026-06-05#

Week in Review#

This week’s reading reflects an industry furiously negotiating the boundaries of abstraction, complexity, and human attention. As the cost of generating software artifacts drops to near zero via AI, engineers are confronting the reality that our bottlenecks have shifted entirely away from writing code and squarely onto system verification, security boundaries, and organizational discipline.

Must-Read Posts#

The Last Technical Interview · Steve Yegge Yegge argues that standard tech interview loops are statistically bankrupt pseudosciences that function primarily as unconscious bias filters rather than predictors of job performance. To fix this, he proposes a “campfire” model of paid, provisional work where candidates tackle real tickets alongside the team, walking away with a portable, verified reputation stamp regardless of the final hiring outcome.

Bloomberg — Week of 2026-05-29 to 2026-06-05#

Story of the Week#

A blowout US May jobs report fundamentally rewrote the macroeconomic narrative, demolishing hopes for imminent rate cuts and driving traders to fully price in a Federal Reserve rate hike by year-end. The sudden hawkish repricing sent tech stocks and Treasuries reeling, disrupting a massive, AI-fueled liquidity frenzy that had been defined by Alphabet’s historic $84.75 billion equity raise and SpaceX’s unprecedented $75 billion initial public offering.

CNBC — Week of 2026-05-29 to 2026-06-05#

Story of the Week#

The artificial intelligence infrastructure boom reached a fever pitch before facing a swift reality check from the market. Dell Technologies and Hewlett Packard Enterprise delivered historic, server-driven earnings beats that pushed the S&P 500 above 7,600 for the first time, but Broadcom’s failure to raise its $56 billion AI chip target later in the week triggered a sharp semiconductor sell-off. Alongside Alphabet’s surprise $80 billion equity offering to fund its compute costs and an impending wave of trillion-dollar mega-IPOs, investors are beginning to weigh the staggering capital requirements of the AI buildout against current market momentum.