OpenAI just revised its cash burn forecast and the numbers are huge! They're adding $111 billion to projections through 2030, bringing total expected burn to $665 billion. The company will torch through $25 billion in 2026 alone. Revenue more than tripled to $13.1 billion, beating their own forecast, but it still can't keep pace. Training models alone will hit $440 billion through 2030. This is the most expensive bet in tech history.

Today in AI:
→ Claude found 500 security bugs humans missed for decades
→ Google and Meta are banning OpenClaw users with no refunds
→ Prompt of the Week: Get different perspectives instead of single answers

Let's dive in..

Anthropic just launched Claude Code Security, and the results from internal testing are wild. Using Claude Opus 4.6, their team found over 500 vulnerabilities in production open-source codebases. Bugs that had gone undetected for decades despite years of expert review. We're not talking about theoretical edge cases. These are real vulnerabilities in code that millions of developers rely on.

How it works differently:

→ Reasons like a security researcher - Doesn't just pattern-match. Understands how components interact and traces data flows
→ Multi-stage verification - Re-analyzes each finding to filter out false positives
→ Severity ratings - Helps teams prioritize what to tackle first
→ Human-in-the-loop - Nothing gets applied without developer approval. You review, you decide

Anthropic spent over a year stress-testing this. Internal red teams, cybersecurity Capture the Flag contests. One side effect nobody expected: cybersecurity stocks took a hit when this launched. Cloudflare and CrowdStrike both slid on the news. The market is pricing in what automated security review might do to traditional tooling.

For your team: If you're still doing manual security reviews for every release, this is worth evaluating. The false positive rate will make or break adoption, but finding bugs that humans consistently miss? That changes the ROI math on code review workflows.

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I've been watching the OpenClaw ban wave unfold, and it's revealing something important about where platform control and open-source AI agents collide.

Google permanently banned paid AI Ultra subscribers, people paying $250 per month. For routing Gemini through OpenClaw via Antigravity OAuth. No appeals. No refunds. Mass suspensions swept through hundreds of accounts. Anthropic followed with similar bans for Claude users connecting to OpenClaw. Meta issued warnings that using OpenClaw on work devices is strictly prohibited.

Why platforms are banning it:

→ Token consumption - Agentic capabilities burn through millions of tokens in a single afternoon. Flat-rate pricing breaks when agents run autonomously for hours
→ Security vulnerabilities - January audit found 512 vulnerabilities, eight critical. Includes one-click remote code execution and two command injection flaws
→ Platform economics - When users can spin up 24/7 autonomous agents consuming tokens at scale, the business model doesn't work

The contradictory part is OpenAI isn't banning ChatGPT users for OpenClaw usage. They hired Peter Steinberger, OpenClaw's creator, and he's joining them while the project moves to an open-source foundation. So we've got Google and Anthropic cracking down hard, Meta restricting it on corporate devices, and OpenAI welcoming it with open arms.

What this tells me: the platforms are realizing that agentic AI on flat-rate pricing doesn't work. When a user can spin up an autonomous agent that runs 24/7, consuming tokens at scale, the business model breaks. The response so far has been bans and account suspensions. The smarter response will be rethinking how AI agents get priced and metered.

For your team: If you're building on top of Claude, Gemini, or ChatGPT with automation or agentic workflows, understand the terms of service around API usage and rate limits. What worked on a Pro plan might get you banned when scaled to production. And if you're evaluating OpenClaw or similar tools, know that major platforms see this as a violation worth permanent account termination.

Instead of asking a question, get different perspectives:

This forces the AI to reason from multiple angles instead of jumping to a single answer. Works well for technical decisions, strategy, or evaluating trade-offs.

🤖 Grok 4.2 vs Sonnet 4.6: early testing shows different strengths. Sonnet 4.6 leads (real expert-level office work) beating Opus 4.6 and Gemini 3.1 Pro. 70% of developers preferred it. Grok 4.2 is weak on coding but hit 12.11% profit in stock-trading simulation. Grok 4.20 runs four AI agents in parallel that debate before producing answers.

🔊 OpenAI built a 200-person team for AI hardware devices. First product: smart speaker with camera, $200-$300, ships early 2027. Camera learns who's using it and what's around them, includes Face ID-style recognition.

✍️ WordPress.com added a built-in AI Assistant. Works in three places: Site Editor for layout and design, Media Library for image generation and editing, and Block Notes for team collaboration. You can ask questions about your content without leaving the editor.

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