Welcome, humans.

OpenAI's IPO was supposed to be the AI industry's moon landing moment. Then SpaceX went public two weeks ago, briefly hit a $2T valuation... and then promptly crashed 25%+ from its highs.

Now, OpenAI is leaning toward pushing its own IPO to 2027. Sam Altman reportedly wants a $1 trillion valuation. His CFO reportedly wants to wait until that's actually achievable. And the rest of us are watching a company burning $3.7B per quarter decide whether to bet everything on a jittery market.

The rocket company spooked the AI company. You can't write this stuff.

Today’s Top 5:

😸 Apple raised MacBook and iPad prices today, and it's AI's fault.
📰 OpenAI, Anthropic, and Amazon launched a $500M nonprofit to retrain workers for the AI economy.
📰 OpenAI is leaning toward delaying its IPO to 2027 after SpaceX's wobbly debut.
📰 Google gave Gemini 3.5 Flash the ability to see, click, and control your computer.
📰 Adobe agreed to acquire Topaz Labs, the AI image and video enhancement company.

…and a whole lot more that you can read about here.

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😺 AI Is Making Your MacBook More Expensive

You finally convinced yourself to buy a new MacBook. Then Apple quietly raised the price by $100-$400.

The culprit isn't tariffs. It isn't Tim Cook. It's AI: specifically, the thousands of data centers being built right now that are hoovering up every memory chip they can find, leaving almost nothing for consumer devices.

Apple announced sweeping price increases across Macs, iPads, and HomePods on Thursday. The company said it has "never seen a component price increase this much, this quickly."

Here's what happened:

MacBook Neo: $699 (up from $599)
13-inch MacBook Air: $1,299 (up from $1,099)
13-inch MacBook Pro 1TB: $1,999 (up from $1,699)
Base iPad: $449 (up from $349)
iPad Air (11-inch): $749 (up from $599)
Vision Pro: $3,699 (up from $3,499)
Apple shares fell 6% Thursday, their worst day in four months

Apple says demand from AI data centers has triggered "an extraordinary surge" in demand for memory and storage chips (DRAM, the stuff that lets your computer run fast). Memory prices have more than doubled since October 2025. Analysts project another 30-40% climb this year. Micron expects the shortage to last through 2027 at minimum.

Why this matters: This is the first time AI's cost has landed directly in your wallet as a consumer: not as a subscription fee or a service charge, but as a straight-up sticker shock on hardware you already rely on. Analysts expect iPhone prices to jump later this year too, potentially $200 more for Pro models.

The companies getting rich from all this? Samsung, SK Hynix, and Micron, the three firms that control global memory production. They're having their best stretch ever. Tim Cook, for his part, is stepping down as CEO September 1, leaving his successor John Ternus to inherit the memory crisis as a welcome gift.

Our take: We're entering a weird new era where your phone, laptop, and gaming console all cost more because AI companies need the same chips. The bottleneck won't clear until new chip factories come online, which takes years. If you've been on the fence about upgrading your gear, the window may have officially closed. Don't wait for a sale that isn't coming.

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🎓 AI Skill of the Day: How to Get Better Results from AI Coding Tools

Most developers use AI coding assistants the same way: type a vague prompt, get code, paste it in, hope it works.

Developer Aleksander Stensby's NDC Copenhagen talk (~40 min) walks through how to get dramatically better results from AI coding tools, and these tips apply even if you never write code yourself.

Three techniques worth stealing immediately:

1. Give the AI the full context it needs. Don't just paste a function; paste the function, the error message, the surrounding code, and a sentence about what you're trying to do. AI models (just like humans) do better work when they're not guessing.

2. Tell it what "done" looks like. Instead of "write me a function to do X," try: "Write a function to do X that handles edge cases, includes error handling, and has a comment explaining each step." Specificity in the output description dramatically improves what comes back.

3. Iterate, don't restart. When the AI gives you something close-but-wrong, describe what's wrong and ask it to fix just that. Starting over from scratch wastes context and produces more drift from your original intent.

Here's a prompt template that combines all three:

I'm working on [what you're building]. Here's my current code: [paste code].

The issue is: [specific problem or error message].

Please fix [specific thing], making sure it [requirement 1], [requirement 2], and [requirement 3]. Don't change anything else.

The most actionable tips are in the first 15 minutes; worth a watch if you use any AI coding tool regularly.

Total AI beginner? Start here (goes with this video).

Have a specific skill you want to learn? Request it here.

🍪 Treats to Try

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OpenArt AI lets you direct full cinematic videos using plain English: describe your story, characters, and pacing in conversation and it renders multi-scene videos up to five minutes long (most AI video tools cap at 10-15 second clips); raised $30M Series A.
Genspark is an all-in-one AI workspace that routes your prompt across 9 top models (GPT-5, Claude, Gemini, and others) and picks the best answer, with Plus and Pro users now getting unlimited AI chat and image generation across all models.
Papermark lets your AI agents run real document workflows: spin up secure data rooms, share files, and track who reads what page-by-page, all without leaving your agent stack.
BrowserAct gives your AI agent a real browser to control: it can click buttons, fill out forms, bypass CAPTCHAs, and scrape live data from any website, so your agents can do work that normally requires a human at a keyboard.
Zaro lets you build custom apps, agents, and workflows for your company just by describing what you need in plain English, using your existing data without touching code.
Oxlo gives you access to 45+ frontier models (including Kimi K2.6 and DeepSeek V4 Flash) on a single OpenAI-compatible API with per-request pricing, and it never trains on your prompts.

NEW VIDEO: How one company is building a full Anthropic AI practice from scratch

Victoria Durgin, Managing Editor at Channel Insider, sat down with the leaders at Caylent (with Grant co-hosting) to talk about what enterprise AI adoption actually looks like on the ground: how organizations are rolling out Claude, what AI governance looks like in practice, and why partner ecosystems are becoming critical to making AI transformation stick.

Worth a watch if you're thinking about how AI is being deployed at the enterprise level.

New episodes air every week on: Spotify | Apple Podcasts | YouTube

📰 Around the Horn

Someone just built an image generator powered by physics instead of a neural network. Unconventional AI's Un-0 runs on a system of coupled oscillators (think: synchronized pendulums doing math) rather than the silicon chips that power every AI model you've ever used. It's still early, but the results are real and the whole thing is open-sourced.

RAISE US launched with $500M+ raised and a goal of $1B, backed by OpenAI, Anthropic, Amazon, Microsoft, and Bank of America, to fund retraining programs for workers displaced by AI, starting in Arkansas, Connecticut, Maryland, and Utah.
OpenAI leaned toward pushing its IPO to 2027, after SpaceX's post-debut selloff spooked advisers and CEO Sam Altman's push for a $1 trillion valuation hit market headwinds.
Google baked computer use directly into Gemini 3.5 Flash, letting developers build agents that can see, click, and control browsers, mobile apps, and desktop software without a separate model call.
OpenAI's Codex grew its active user base more than 5x in the first half of 2026, with non-developer adoption rising 137x for individual users; legal, finance, and recruiting at OpenAI now use Codex as their primary work tool, not ChatGPT.
Adobe agreed to acquire Topaz Labs, an AI company known for sharpening, denoising, and upscaling videos and images, to bring its on-device enhancement models into Photoshop, Lightroom, and Premiere.
OpenAI agreed to release its upcoming GPT-5.6 model in a limited preview to select partners first, after the Trump administration asked it to stagger access while the government approves customers one by one.

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Intelligent Insights:

GenAI and Creeping Cognitive Displacement Syndrome (Starominski-Uehara, EDUCAUSE Review) — A useful framework for a problem most institutions are ignoring: how students quietly lose the ability to think independently through habitual AI use, and what universities can do before it's too late.
AI Is Degrading the Value of a University Degree (LSE Impact Blog) — The argument here is worth sitting with: when everyone graduates using AI, what does a degree actually certify? Spoiler: maybe a lot less than it used to.
A New Biology Renaissance (The Neuron) — AI's next frontier isn't another chatbot. It's programmable biology, and this explainer from our own archive breaks down why tools like Proto-JAM 2 and BioNeMo matter for the future of medicine and drug discovery.
When Does Combining Language Models Help? (Josef Chen, KAIKAKU) — A new paper studying 67 frontier models finds that mixing AI models together (voting, routing, mixture-of-agents) rarely beats just using the single best model; the gains only come when models fail on different questions, not when you add more of the same.
Language-Based Digital Twins for Elderly Cognitive Assistance (Hosseini et al.) — Researchers built an LLM-powered "digital twin" of elderly patients that mimics their conversational style to help detect early signs of cognitive decline, a non-invasive alternative to clinical screening.