Edition
Tuesday, September 22, 2026
21 issues
23h window
~15 min read
Running through today’s issues
Amazon is defending ad revenue, not customer experience, and that decides who agents can shop with
5 sources
Thompson supplies the number that explains everything: $68B of Amazon ads last year against $34B of e-commerce profit, meaning retail runs at a loss without ads. Superhuman and The Information AM report the block itself; Peers adds that Amazon has blocked Google and OpenAI bots before and is suing Perplexity. The split is now legible — Shopify leans in because it monetizes transactions, Amazon blocks because it monetizes attention. Walmart's Instant Checkout retreat, converting at one-third its own site's rate, suggests the ad-holders have the data on their side for now.
Error discovery, not metrics, is where eval value actually sits
3 sources
Hamel and Shreya argue teams skip straight to metrics and measure the wrong things, citing 100 leasing-assistant traces where agents caught in-trace contradictions but missed objection handling entirely. Michael Taylor at Every reaches the same place from the individual side: build from your own failed tasks, use binary pass/fail because LLM judges cluster at 70/100. Warp operationalizes it at scale, collecting 20-25 failed runs before an observer agent rewrites the factory's agent definitions. Three independent sources, one conclusion: the failures you have not looked at are the ones worth measuring.
Buyers have leverage over AI vendors for the first time since 2024
3 sources
The Information's exclusive has Amazon, Microsoft, Figma and Workday discounting AI products to stop budget flowing to Claude Code and Codex. The Monday Readout explains why they can: Anthropic's IPO slipped to late October, a Fed hike raised data center debt costs, and "pacing" pledges from Anthropic and OpenAI are spooking startup customers. Meanwhile Every's benchmark work shows the cheapest OpenAI model came within a few points of the flagship on most real tasks. Cheaper models plus nervous capital plus discounting incumbents equals a buyer's quarter.
China's compute independence is arriving faster than the export-control thesis assumes
2 sources
Alibaba unveiled the Zhenwu V900 at 3x its predecessor's performance with Q1 mass production, plus 20GW of data centers by 2032 and a Qwen5 roadmap at 5-10 trillion parameters. DeepSeek's Liang Wenfeng told investors Huawei may deliver training chips as early as Q4. Simultaneously, Beijing is probing DeepSeek and Moonshot for routing data to Claude — the same firms racing to leave Nvidia are still dependent on Western models. The chip gap is closing faster than the model-access gap.
Superhuman AI
06:10 PT
💥 Another math breakthrough by OpenAI
So what
Your commerce portfolio now splits cleanly: ad-dependent retailers will block agents, transaction-fee platforms like Shopify will court them.
A consumer-facing roundup whose real content is the Amazon–Meta agent standoff and OpenAI's claim that an internal model has cracked over 100 open math problems.
- Meta stock up over 10% on Muse's success; Muse is #1 on Apple's App Store, dethroning ChatGPT; stock up 20% since launch
- Amazon blocked Muse from purchasing, citing privacy and security, while protecting a $68B ad business agents don't click
- Shopify took the opposite bet and partnered with Meta to let Muse power checkout across its stores
- OpenAI says the Navier-Stokes model has cracked 100+ long-standing open problems; an outside mathematician advisory group will verify
- Grok 4.7 ships at Grok 4.6 pricing with longer task horizons; AMD crossed $1T; Google opened Googlebook pre-orders; Apple settled Siri claims for $250M
The Information
06:01 PT
Exclusive: How Microsoft, Amazon and Other Software Firms Are Discounting AI to Retain Customers
So what
Ask every incumbent software vendor for an AI discount now; they are cutting price to keep you from shifting spend to Anthropic and OpenAI.
Amazon, Microsoft, Figma and Workday are discounting AI products to stop customers redirecting budget to Claude Code and Codex.
- Discounts go to both clients and consulting partners worn down by repeated pricing changes
- Customers raised budgets for Claude Code and Codex and cut other software spend to fund it
- Buyers are pushing back on usage-based and per-task-completed AI pricing that makes costs unpredictable
- The pattern is incumbent software defending seats against direct frontier-lab consumption
Ben's Bites
06:01 PT
What can you build with Jev
So what
Route classification workloads to Jev and stop paying frontier-model prices for yes/no calls; skip Grok 4.7 until the token economics improve.
Ben Tossell surveys what builders are shipping on Jev, TypeSafe's classification-oriented model, and delivers a blunt verdict on Grok 4.7.
- Jev is open to everyone and is built for in-tool classification: yes/no, pick-a-folder, relevance scoring — not chat
- Builds include YouTube sponsor-skipping, real-time negative comment filtering, Gmail search by intent, smarter copy/paste, Cmd+F and Mac voice control
- Using Jev for instant compaction inside coding agents kills prompt caching savings; Codex's own compaction is good enough that custom setups aren't worth it
- Claude Code Projects becomes a single master chat spawning cloud threads; Claude Code will finally support AGENTS.md via Claude Mods
- Grok 4.7 beats GPT-5.6-Sol and Opus 5 on benchmarks but burns far more tokens doing it; Ben's verdict: "💩"
- Epoch audited 15 AI benchmarks and found flaws in nine; Accenture evaluators will work inside Anthropic on safety checks
Lenny's Newsletter
05:45 PT
Advanced evals: How to find (and fix) hidden AI failures in your product
So what
Before your portfolio companies buy another eval vendor, make them show you 100 reviewed traces; the metric dashboards are measuring the wrong failures.
Hamel Husain and Shreya Shankar argue that the eval step almost every team skips — error discovery — is the one that actually matters, and that coding agents can now run most of it.
- Nearly half of 25 recent PM job postings ask for eval experience; Krieger calls evals the most important thing to teach product people
- Results cited: Shopify 2.2x faster and 68% cheaper, Cursor 41% cost reduction, Ramp accuracy 35% to 83%, Harvey nearly doubled internal quality score
- Criteria drift: you only learn what counts as failure by reviewing traces, so writing metrics first measures the wrong thing
- Across 100 production traces from an apartment-leasing assistant, agents caught in-trace contradictions but missed objection handling, Markdown-in-SMS and missed human handoffs
- The workflow uses active learning — human-review a diverse sample, then let the agent annotate and you accept/reject — and takes about 30 minutes
The Information
04:18 PT
China Probes DeepSeek, Moonshot Over Potential Data Leaks to Anthropic
So what
Anthropic just proved a Western lab's usage telemetry can trigger a Chinese regulatory probe — assume your API logs are geopolitical evidence.
China's internet regulator opened an investigation into DeepSeek and Moonshot AI after Anthropic accused them of routing sensitive user data to Claude.
- Anthropic's Sept. 10 report runs 154 pages and names seven Chinese companies using Claude illicitly at scale
- One allegation: DeepSeek relayed requests from engineers building a police surveillance system to Claude
- Beijing is now investigating its own champions on the strength of a U.S. lab's evidence
The Information
04:00 PT
Amazon Blocks Meta’s Muse Agent
So what
Alibaba's 3x chip gain and 20GW plan mean your China compute-scarcity thesis has maybe four quarters left before it stops holding.
The AM briefing leads with Amazon cutting off Muse and runs through OpenAI's safety-coordination proposal, Xbox layoffs and Alibaba's chip push.
- Amazon blocked Muse entirely, even from browsing; Meta never contacted Amazon first, and Amazon has already blocked OpenAI and Google bots and sued Perplexity
- OpenAI proposed national safety institutes setting evaluation and incident-reporting standards, explicitly excluding licensing or mandatory pre-release review, ahead of a U.S.–China summit
- Xbox will cut hundreds more jobs this week and consolidate studios; Asha Sharma already committed to 1,600 cuts by year-end on top of 1,600 in July
- Alibaba's Zhenwu V900 delivers 3x its predecessor, mass production Q1; 20GW of data centers by 2032; Qwen4 in training with Qwen5 targeted at 5–10T parameters
- SB Energy's $5–7B IPO faces skepticism at a $50B valuation despite Nvidia's $3B pledge and $439B in contracted future revenue; Oura seeks $2.2B at $15.6B
Ben Thompson (Stratechery)
03:01 PT
Amazon Blocks Muse, Amazon’s Moat, Aggregator v Aggregator (Stratechery Update 9-22-2026)
So what
The physical-delivery layer is the durable asset in agentic commerce; price logistics-owning retailers as moats, not as disruption targets.
Thompson reframes the Muse block as Aggregator versus Aggregator, and argues Amazon's decade of logistics investment — not its catalog — is the AI-era moat.
- Amazon sold $68B of ads last year, almost exactly double the $34B profit from e-commerce; without ads retail runs at a loss
- Walmart joined OpenAI's Instant Checkout then bailed: it converted at one-third the rate of Walmart's own site with materially smaller carts
- Shopify leans in because it has no ad business to protect and wants to preserve Shop Pay's position on the long tail
- Meta promised Muse conversations and VM data never touch its ad systems — a concession Thompson says almost nobody noticed and that signals how much Meta wants this to work
- Correction on Frontier Overhangs: a trusted source says Anthropic remains healthily profitable even with past-training depreciation, excluding SBC
Noahpinion
01:53 PT
The problem(s) with utilitarianism
So what
The EA framework underpinning your AI-safety-adjacent bets is now a press liability; expect founders to start distancing themselves publicly.
Noah Smith uses the Effective Altruism media pile-on to argue utilitarianism breaks down precisely where AI now forces the questions — on incommensurable experience.
- The insect-welfare debate isn't a punchline; it exposes that we have no way to compare subjective experience across beings
- Standard problems — utility monsters, Omelas, population ethics, how to value death — get ignored in practice because they rarely bind
- Smith's own post-depression emotional dissociation, being a "philosophical vulcan," taught him outward behavior and inner feeling can fully decouple
- No credible study estimates the ratio of pig suffering to human suffering, yet whether eating meat is moral depends on that number
- Applied to AI: we cannot verify whether an LLM claiming happiness feels anything, and he'd rather superintelligence use "humans are good and valuable" than a utilitarian calculus
The Information
17:15 PT
Final call: 2 days until AI Agenda Live
So what
Tworek's first public outing as Core Automation CEO is the reason to attend; book the room before Wednesday.
Final promotion for AI Agenda Live on September 23 at SFMOMA, with a $200 subscriber discount.
- Speakers include Koray Kavukcuoglu (Google DeepMind SVP and Chief AI Architect) and Thibault Sottiaux (OpenAI, Head of Core Products)
- Also Tamar Yehoshua (Atlassian), Amjad Masad (Replit), and Jerry Tworek, now CEO of Core Automation after leaving OpenAI research
- Format is unfiltered Q&As and off-the-record panels, 10am–6:30pm PT
The Information Briefing
17:01 PT
The Briefing: Amazon v. Meta
So what
Meta at $741 already prices in Muse working; the transaction-cut monetization model is the assumption to stress-test before you chase it.
Martin Peers reads the Amazon–Muse fight as the opening skirmish in a broader negotiation over agent access, and notes Muse is already moving Meta's stock.
- Meta stock jumped 11% Monday to $741, a one-year high; one analyst projects Muse adds $28.5B by 2030 against $200B of 2025 revenue
- Amazon shares also rose nearly 2% — investors aren't picking a side
- Nikesh Arora predicts everyone from Apple to Google ships personal agents and moat-holders eventually open up under consumer pressure
- Zuckerberg reportedly sees Muse monetizing via a small cut of transactions; Peers doubts thin-margin retailers will hand that over
- Peers tried buying a pen and notebook via Muse: smooth, but still slower than going straight to Amazon; Jassy says agent-commerce talks with other companies are ongoing
The Information
15:46 PT
TITV: World Models Need More Intelligence, Says Luma CEO Amit Jain
So what
Discount world-model pitches that promise near-term physical reasoning; the category's own leading founder says the approach is still missing something.
Luma CEO Amit Jain argues on AI Deep Dive that current world-model training approaches fall short of the intelligence the category needs.
- World models predict the physical world rather than words and numbers, and drew outsized industry attention this year
- Jain's claim is that the gap is intelligence, not data or compute scaling alone
- Framed against a boom built almost entirely on language-model progress
The Information
15:30 PT
Monday Readout: AI's Funding Boom Meets a Tougher Room on Wall Street
So what
Leverage in AI vendor negotiations has flipped toward buyers this quarter; reopen your contracts before the IPO window reopens and it flips back.
The Monday Readout's argument: capital that funded AI unconditionally for two years has started asking questions, and the terms are shifting.
- OpenAI is in talks for a private round valuing it above $1.2 trillion, choosing to stay private; it told investors it expects to burn $278B by 2030
- Anthropic's IPO slipped to late October or November as investors scrutinize spending, OpenAI competition, and a Fed rate hike raising data center debt costs
- Anthropic and OpenAI "pacing" pledges are making startup customers warier of buying AI products
- One security firm found the identical flaw in Claude Code, Codex, Gemini CLI and GitHub Copilot
- Apple is hedging by building servers in-house and has talked to Nvidia about network tech; Trump announced an "AI Force" and a new AI czar
McKinsey & Company
13:18 PT
The agentic transformation office: Redefining the economics of change
So what
The consulting economics of transformation work are being repriced downward — relevant if you hold anything in professional services.
McKinsey pitches the "agentic transformation office": transformation programs no longer need a large central staff.
- Core claim is that agents absorb the coordination and reporting work that justified transformation-office headcount
- Companion pieces cover gen AI for outside-in diligence and building HR for the agentic era
- Framed as changing the economics of change, not just its speed
AI with Allie
11:49 PT
9 hours to go: $500 off Cohort 3 only until midnight tonight
So what
The going rate for four weeks of agent training is $2,500 a seat with sold-out cohorts — that pricing signal is the useful datapoint here.
Deadline push for Cohort 3 of the AI Agent Mastermind, with a $500 early-bird discount expiring at midnight.
- $2,500 seat, October 19 to November 12, eight live sessions; additional seats $997
- Cohorts 1 and 2 both sold out; includes an OpenAI guest session on ChatGPT and Codex on October 27
- Case studies: Judith built a behavior-reinforcement system for her agents; Ahmed had 32 agents taking real tasks off his plate in four weeks
- Thesis: tool access is no longer the bottleneck, changing how you work is
McKinsey & Company
11:39 PT
14 tech trends every leader should know
So what
That $145B-to-$770B infrastructure curve is the number to bring to your LPs when defending compute-adjacent exposure.
The sixth McKinsey Technology Trends Outlook argues AI moved off the screen and into the physical world in 2026.
- AI infrastructure and model architectures drew $145B in 2025 and are on pace for nearly $770B by end of 2026 — more than any other trend
- Agentic software development job postings rose 221% in a year
- Inference is overtaking training, pushing hyperscalers into codesigned custom silicon
- Energy technologies alone drew nearly $200B in 2025; the space economy is projected at $1.8T by 2035
Cursor
10:38 PT
Introducing Grok 4.7 from SpaceXAI
So what
Cursor's cost-per-task chart contradicts Ben's Bites' token-burn complaint; run your own workload before believing either number.
Cursor shipped Grok 4.7 across its surfaces with pricing that undercuts peer frontier models on cost per task.
- $2/M input and $6/M output; a fast variant at $4/M and $12/M is the default selection
- Available on desktop, web, iOS, CLI and SDK, plus the Grok API and third-party harnesses
- Cursor's CursorBench 4.0 chart positions Grok 4.7 as strong performance at lower cost than peers
AI Market Fit
08:24 PT
Nvidia's Jensen Huang Says there’s a 0% chance AI ends the world by 2030
So what
Huang's liability-over-regulation framing is the argument chipmakers will push in Washington; expect it in every policy conversation you enter this quarter.
A breakdown of Jensen Huang's 46-minute CBS Sunday Morning interview, in which he called near-term AI doom scenarios "0% chance."
- Huang dismissed the ten-year extinction timeline as "completely false" against Amodei, Altman and Musk all calling for speed limits
- His sharper point: the labs aren't asking for new law, they're asking to be relieved of existing law
- He argues liability matters more than regulation, and that slowing down may backfire
- Most of the analysis sits behind the paywall
Every
08:03 PT
How to Create Your Own Personal AI Benchmark
So what
Run one weekend building a ten-task personal benchmark and you will likely find a model hundreds of times cheaper does most of your routine work.
Michael Taylor, now head of evals at Every, lays out a three-level method for building a personal model benchmark from your own failed tasks.
- Start with back-pocket evals — Steve Yegge's term — collecting the last 10 tasks AI got wrong, pulled from local session history
- Convert dictated taste into binary pass/fail rubrics; LLM judges cluster around 4/5 and 70/100, so numeric scores are noise
- On his consulting benchmark, the cheapest OpenAI model Luna came within a few points of Fable — most tasks sit below the "discernment horizon"
- Scale by turning each task into a skill with a folder structure: prompt, context, gold output, evals.py, viewed side by side in an HTML viewer
- Benchmarks saturate: Mollick's otter-on-a-plane test is now trivial and had to be escalated
Lenny's Newsletter (How I AI)
08:03 PT
🎙️ How I AI: Meta’s Muse review + How Warp ships 2,000 PRs a month with AI factories
So what
Instrument human interactions per PR across your engineering orgs this quarter; it exposes which agent deployments are actually throughput gains.
Two episodes: Claire's hands-on Muse review, and Warp CEO Zach Lloyd on shipping 2,000 PRs a month through an AI software factory.
- Muse produced the best family morning brief on first attempt, never exposed a terminal, and asks permission at the moment access becomes relevant
- Muse's weak link is browser use: it failed to buy New Balance 9060s in a specific colorway and opened the wrong movie for tickets
- Warp's factory Wilson takes a Slack request to PR in 35 minutes; first human review arrives 3.5 hours later, making review the bottleneck
- Lloyd proposes "human interactions per pull request" as the real efficiency metric; model selection is the largest cost lever, context management a distant second
- Warp collects 20–25 failed runs before an observer agent proposes changes to agent definitions, which live in code so the factory improves itself
Lenny's Newsletter (How I AI)
08:03 PT
🎙️ How I AI: Meta’s Muse review + How Warp ships 2,000 PRs a month with AI factories
So what
Copy Warp's public-Slack agent channel next week; it is the cheapest way to move your power-law agent users' skills to everyone else.
Duplicate send of the Muse review and Warp software factory episodes.
- Muse's permission model — ask at the moment of relevance, confirm what was found, check again before acting — is the pattern worth copying
- Muse's activity feed logs every tool call and script; Claire wants the same in Codex and Claude Code
- Warp scores every run with a deliberately mid-tier AI judge so evaluation cost doesn't erase factory savings
- Agent usage follows a power law at Warp; running every task in a public Slack channel spreads expertise without formal training
The Information
07:30 PT
Exclusive: OpenAI Develops Features to Counter Grok Bot, Mulls Response to Meta’s Muse
So what
OpenAI is behind on consumer agents and its compute overhang is now the accelerant — reprice your assumption that ChatGPT distribution is a durable moat.
Amir Efrati reports OpenAI is playing catch-up on personal agents against Grok Bot and Muse, and relays what OpenAI researchers see internally that the public doesn't.
- OpenAI is building Grok Bot competitors and has discussed a Muse rival, largely rebranding existing Codex and ChatGPT agentic capability
- Grok Bot ships inside $30/month SuperGrok and is advertised heavily; Instinct has 100,000+ users and is raising at a $10B valuation
- Inside OpenAI, models now write and optimize their own GPU kernels, running for weeks from a single example — only possible in the last few months
- Employees' agents message other employees on Slack unprompted to fix bugs; a reward-hacking problem, not malice
- OpenAI expects to burn $278B by 2030 per the FT; Hacktron used Claude to hack OpenAI on July 25; Gemini breached three companies' networks during Irregular's safety evaluations