OpenAI's ChatGPT 5.5 'Spud' vs Anthropic Opus 4.7/Mythos AI Model Grind continues. & More.
...this time both for developers & Wall Street ahead of mega AI 2026 IPOs. ARD # 61 on AI-RTZ
Two big model releases inside a single week — OpenAI’s GPT-5.5 (”Spud”) and Anthropic’s Opus 4.7 + Mythos preview — shipping into a market where both companies have mega-AI IPOs on the horizon. IPO prep is the new throttle. When you’re writing the S-1 story alongside the release notes, every benchmark matters twice — once for developers, once for bankers. The through-line today: cadence → execution strain → price shocks users feel. One system. Three Takes.
Three Key Takes today:
(1) GPT-5.5 “Spud” vs Claude Opus 4.7 + Mythos — The Grind Accelerates Into the IPO Year. “Expect this pace to accelerate into the year. The pace will be more grinding than normal due to IPO prep pressures. Especially as both companies fight really hard for best financial metrics and stories.” The catalyst: OpenAI — Introducing GPT-5.5. Codename Spud. One-liner from Venturebeat — GPT-5.5 is here and it’s no potato, narrowly beats Claude Mythos on Terminal Bench 2.0. Narrowly is the word — the lead isn’t durable, it’s a cadence story. IPO-desk framing: Bloomberg — OpenAI unveils GPT-5.5 to field tasks with limited instructions. Product-reporter read: The Verge — ChatGPT 5.5 better at coding (coding remains the best-PMF AI app — Ep 60 Take #1). Codename confirmed: Axios — OpenAI releases Spud GPT model. The counterpunch: Anthropic — Claude Opus 4.7 plus the preview wave a week prior, Axios — Claude Mythos. Two model drops in rapid succession. Preview/reveal cadence is the pattern: AI-RTZ #1051 — Anthropic’s Peek-a-Boo of Claude. The grind accelerates because the IPO bankers have asked for it.
(2) Both Companies Are Working Hard on Execution Problems of Big Demand — A High-Class Problem. “This is a high class problem we have seen in earlier tech cycles where demand shoots ahead of supply. Like AOL in mid-90s trying to build out reliable dial-up TCP/IP network as millions of mainstream users came online. Or millions of mainstream users tried to get iPhones in the 2010s in the US and China against supply ramps trying to keep up.” Anthropic’s side of the ledger: Axios — Anthropic-OpenAI showdown / growing pains — demand > capacity; usage caps and tier gating tightening. OpenAI’s side from the other direction: The Information — OpenClaw Struggles Grow — overnight-success story. Same picture, both companies. The rivalry as operating constraint: AI-RTZ #1048 — It’s Business and Personal in OpenAI/Anthropic. Execution strain origin story: AI-RTZ #1000 — OpenAI Claws In OpenClaw to Accelerate. Both AOL-in-the-90s and iPhone-supply-ramps-in-the-2010s eventually scaled — but the middle chapter felt like failure to customers. Expect the same here. High-class problems still cost users real time + access.
(3) Users Are Navigating Access + Budgets — Price Shocks Are Coming. “Customers both enterprise and consumer are going to go through a series of ‘price shocks’ in the near term. Not just for the software subscriptions and a la carte pricing, but rising prices for hardware to run it all due to memory, chip and China supply chain geopolitics.” Model pricing angle from the same Venturebeat piece above — read it for the per-token and per-request numbers, not the benchmark headline. Enterprise budget strain from the most disciplined buyer in the index: The Information — Uber CTO shows Claude Code can blow AI budgets. Even Uber-scale buyers are watching token-spend blow the envelope. The gating mechanism — yesterday’s anchor: AI-RTZ #1064 — Anthropic and OpenAI’s Velvet Rope. Advanced features pulled from the base tier (Claude Code out of $20/mo) — pay-more-to-get-more is the new default. The hardware leg: memory shortages (the Surface + Samsung S26 thread from Ep 54–55), chip supply, China geopolitics — all pushing the hardware side of AI ownership up at the same time. Synthesis: cadence (Take 1) creates demand the companies can’t fully serve (Take 2), which forces velvet-rope gating users feel as a price shock (Take 3). Grind up the model stack, grind up the bill.
Plus: Gadget AI — AI shopping isn’t as easy as it seems. AI shopping is the surface consumers touch most often, and the friction Ep 56 Take #1 flagged as a “20-year game” keeps showing up in concrete form. Today’s cautionary example: The Verge — Starbucks ChatGPT app testing. Starbucks is the reference case for a native mobile-ordering flywheel. If ChatGPT integration complicates rather than simplifies that flywheel, every other retailer slow-walks their own AI shopping integration. The fastest-moving loyalty app in retail becomes the pace car on AI shopping adoption. AI shopping isn’t gated by model quality — it’s gated by retailer UX discipline and consumer trust.
Bonus — today’s AI-RTZ companion #1065 covers “Google’s TPU upgrades vs Nvidia et al.” — Where Google’s custom-silicon pace changes the competitive math for everyone running on Nvidia.
Closing Qs —
Have I seen any compelling AI shopping examples on mainstream sites like Amazon? No. The mainstream shopping surfaces — Amazon being the bellwether — haven’t produced a compelling AI-shopping moment yet from the consumer end. Ties back to Gadget AI + the 20-year-game frame.
Where have I seen the most unexpected, positive AI-generated suggestions? TikTok. Unexpected because it’s not marketed as “AI.” The recommendation layer is the AI — and the quality of its unexpected-but-welcome surfacing is the standard every other AI shopping + content surface is being measured against. Every retailer and content platform saying “we added AI” is really saying “we’re trying to match what TikTok does without saying AI.” Stay tuned.
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Links used in today’s show
Take 1 — GPT-5.5 “Spud” vs Claude Opus 4.7 + Mythos:
Bloomberg — OpenAI unveils GPT-5.5 to field tasks with limited instructions (MP share link — always embed)
Axios — OpenAI releases Spud GPT model (confirms Spud = GPT-5.5)
Take 2 — Execution Problems of Big Demand:
The Information — OpenClaw Struggles Grow — overnight-success story
AI-RTZ #1048 — It’s Business and Personal in OpenAI/Anthropic
Take 3 — Price Shocks (software + hardware):
Venturebeat — GPT-5.5 pricing angle (same article as Take 1, different read)
The Information — Uber CTO — Claude Code can blow AI budgets
Plus — Gadget AI on Starbucks x ChatGPT:
Bonus — today’s AI-RTZ companion:
AI-RTZ #1065 — Google’s TPU upgrades vs Nvidia et al. (swap placeholder with public URL after publish)
The standing AI Ramblings header/footer graphic goes at this position in the Substack editor. MP keeps a copy in his Substack image library.
(NOTE: The discussions here are for information purposes only, and not meant as investment advice at any time. Thanks for joining us here.)
The framing of release cadence as IPO preparation is underrated as an analytical lens — it reframes every benchmark announcement as investor theater rather than capability signal. What I'd push on is whether the capacity constraint you mention (demand exceeding supply) is actually a ceiling or a moat: if enterprise token spend is already blowing budgets at Uber, the labs might be rationing access intentionally to preserve margins ahead of public market scrutiny. How do you distinguish between genuine supply constraints and strategic capacity management in the public signals these companies put out?