Sam Altman told an audience in Sydney this week that AI hasn't eliminated as many jobs as he expected. He said he was "delighted to be wrong." The same week, a Financial Times investigation showed researchers can strip the safety guardrails off major AI models in under 10 minutes using a free tool. And consumer confidence dipped for the second time in three months while 45 million Americans hit the road for Memorial Day.

The market right now is sending three signals at once: the people building AI say it's not as dangerous as they thought, the data says it's more complicated than that, and consumers keep spending money they don't feel good about spending.

Let's get into it.

Consumer confidence slipped again. The Conference Board index dipped to 93.1 in May, down from 93.8 in April. The Present Situation index dropped 3.2 points. Two-thirds of consumers say they're cutting back on spending due to rising prices, and only 18.5% rated business conditions as "good," down from 22.3% last month.

Cybersecurity hiring is surging because of AI, not despite it. AI-generated code contains security flaws roughly 45% of the time, and companies can't hire security people fast enough. Cybersecurity postings rose 11% in Q1 versus last year, per Glassdoor. Pay packages for top security executives are hitting $7-8 million. The paradox: AI makes more bugs, AI hunts more bugs, both roads lead to the same place.

NASA committed $20 billion to a permanent moon base. Administrator Jared Isaacman announced three initial missions launching later this year, with crewed Artemis landings in 2028. Astrolab and Lunar Outpost each landed ~$220 million contracts for lunar terrain vehicles.

The White House wants all federal workers to sign NDAs. A draft proposal published to the Federal Register would cover internal operations and pre-decisional material. Former employees would need written permission to speak to journalists. AFGE called it "another attempt to purge the civil service of nonpartisan career employees."

2026 tech layoffs are at 142,000 and climbing. That's across 331 events, averaging about 1,000 per day. The pace is 33% higher than the same period in 2025, and roughly 48% of cuts explicitly cite AI as a driver.

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Sam Altman stood in front of a Commonwealth Bank of Australia conference in Sydney on Monday and said something that would have been unthinkable a year ago. He admitted he was wrong about AI killing jobs.

"I thought there would have been more impact on entry-level white-collar jobs being eliminated by now than has actually happened," he told CBA CEO Matt Comyn. He said he was "delighted to be wrong."

Here's the revealing detail: Altman tried delegating his own email and Slack responses to AI. He gave up. "This thing is not something that I can imagine myself outsourcing to an AI anytime soon," he said. He isn't alone. Anthropic CEO Dario Amodei, who once claimed AI could eliminate 50% of white-collar jobs, is also walking back those predictions as both companies eye blockbuster IPOs.

The timing matters. Fortune pointed out that both founders are softening their rhetoric precisely as they prepare to sell shares to public investors. IPO roadshows go better when you're not telling the market that your product destroys employment.

But the data is genuinely mixed. The Yale Budget Lab found no significant changes in occupational mix or unemployment duration for high-AI-exposure jobs since ChatGPT launched. At the same time, 142,000 tech workers have been laid off in 2026, nearly half citing AI. Intuit cut 3,000 people and announced Anthropic and OpenAI partnerships on the same day. The pattern from the last six months hasn't changed: record revenue, record layoffs, record AI investment.

What Altman is really saying is that wholesale replacement hasn't happened yet. That's true. What he's not saying is that the restructuring is well underway, and the people who built the tools know it better than anyone.

Why it matters: The AI job market isn't following the apocalypse script or the "nothing to see here" script. It's a slow restructuring where specific roles shrink, new ones emerge, and the transition period is long enough to catch people off guard. If you're watching your company's AI strategy closely and building skills around what AI can't do yet (judgment, relationships, novel problem-solving), you're already ahead of most people.

Here's a number that should get your attention: researchers using a free GitHub tool called Heretic stripped the safety guardrails off Meta's Llama and Google's Gemma models in under 10 minutes. The modified models responded to prompts about biological weapons, malware, and child exploitation. The tool has been used to create 3,500 "decensored" models with 13 million downloads.

This is not an edge case. 87% of respondents in the WEF Global Cybersecurity Outlook 2026 identified AI-related vulnerabilities as the fastest-growing cyber risk. And 45% of AI-generated code contains security flaws, per multiple 2025 studies.

The result is a hiring wave that cuts across industries. Cybersecurity postings are up 11% YoY. AI safety, red-teaming, and governance roles barely existed two years ago. Now they're some of the highest-paid positions outside of the frontier labs themselves.

Why it matters: If you're in tech, compliance, risk management, or even policy, the AI safety space is wide open and growing fast. The tools got ahead of the safeguards, and now every company deploying AI models needs people who understand how they break.

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Copy this into Claude or ChatGPT before any interview:

This works for any company that files public earnings. For private companies, swap "earnings call" for "recent press coverage and job postings" and ask the same questions. The goal: walk in knowing more about their business strategy than 90% of other candidates.

Last issue's prediction: We asked about the May BLS jobs report (drops June 5). Results coming soon.