You've probably noticed your favorite restaurant has been a little quieter lately. Maybe a spot you used to need a reservation for is suddenly easy to get into on a Friday. That's not just a vibe - it's in the data. The BEA dropped the Q1 2026 advance GDP estimate this morning and the headline number looks healthy: 2.0% growth, a sharp bounce from Q4 2025's sluggish 0.5%. But consumer spending on restaurants and hotels actually fell 2.8% this quarter, on top of a 1.2% drop in Q4. The growth that showed up in the number? Almost entirely AI infrastructure spending - computer investment jumped 67%. Two different economies are running at the same time right now.

Let's get into it.

Core PCE inflation for March came in at 3.2% year-over-year, per the BEA's report this morning. Headline PCE was 3.5%. Both are well above the Fed's 2% target, which means rate cuts remain firmly off the table. Futures markets aren't pricing in a cut until late 2027.

Amazon launched Connect Talent this week, an AWS product that runs structured job interviews 24/7 with no human recruiter involved. It uses voice AI to conduct interviews, score candidates, and deliver evaluation reports to hiring managers. The initial use case is high-volume hiring - Amazon ran 250K seasonal hires last year. It's now available in preview for any company.

AI agent adoption jumped from 11% to 42% of enterprises in just two quarters, according to G2 and IDC data. Nearly every executive says their company has deployed AI agents. Only 29% say they're seeing significant ROI. Deployment is moving faster than results.

Yale's Jeffrey Sonnenfeld published a sharp piece in Fortune yesterday arguing that AI won't eliminate your current job - it will eliminate the path to your first one. Entry-level positions are quietly contracting because AI handles what new hires used to do. Existing workers are largely insulated. New grads are not.

The BLS Employment Situation for April drops May 8. March showed 178K jobs added and 4.3% unemployment. With today's GDP and PCE data in hand, the April jobs report will be the next clear signal on whether this recovery is holding or softening.

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The Bureau of Economic Analysis released the Q1 2026 advance GDP estimate this morning: 2.0% annualized growth, a significant rebound from Q4 2025's 0.5%. That number will dominate financial coverage today. It deserves a closer look.

Investment was the biggest driver, adding 1.39 percentage points to total growth. But not all investment is equal. Computer equipment spending rose at a 67.4% annual rate. Software investment climbed 22.6%. These aren't small rounding errors - they're the AI buildout showing up in GDP data in real time. Companies are spending heavily on the infrastructure that runs AI systems, and that capital expenditure is now large enough to move the whole economy's top-line number.

Consumer spending told a different story. Households grew spending at just 1.6%, well below the overall GDP figure. Healthcare accounted for 47.2% of all consumer spending growth in the quarter. Durable goods were flat. Non-durable goods declined. And the category that most directly reflects whether people feel financially comfortable - hotels and restaurants - fell at a 2.8% rate, following a 1.2% drop in Q4 2025.

Government spending added 0.73 percentage points, driven largely by federal employee compensation rebounding after Q4 cuts. That's a real contribution, but it doesn't signal private-sector momentum.

The summary: two different economies are coexisting inside one GDP print. AI capital spending is running hot. Consumer discretionary spending is pulling back. The gap between those trends is where the real story lives.

Why it matters: If you're in tech, AI infrastructure, or adjacent fields, you're working in the part of the economy that's expanding fastest right now. The consumer-facing economy is softer - and that matters for hiring, comp growth, and role availability in those sectors. Understanding where the money is actually flowing gives you a clearer read on where negotiating leverage exists and where it doesn't.

The most useful version of the AI-and-jobs conversation distinguishes between two things that are often conflated: job elimination and hiring slowdowns. Yale economist Jeffrey Sonnenfeld drew that line clearly in a piece published yesterday. Existing workers are largely insulated. What's contracting is the entry-level funnel - the positions where new hires traditionally build skills before moving up.

The mechanism is straightforward. Drafting emails, basic research, data entry, scheduling - these are the tasks that filled entry-level roles for decades. AI tools handle much of that work now. Instead of hiring someone to do it, companies are using the efficiency to hold headcount flat. The job disappears before it's ever posted.

There are counter-signals worth knowing. NACE data shows overall hiring projections for the Class of 2026 up 5.6% from last year. Gusto data covering 500,000+ small businesses shows nearly 1 million new graduates on track to be hired this season. Computer science starting salaries are projected up 7% year-over-year. The openings exist - they're concentrated in roles that require demonstrated capability upfront, not just a degree and a resume.

The sharpest data point: 38% of 2026 graduates are already exploring entrepreneurship, gig work, or freelancing as primary income options. That's a rational response to a market where the traditional first-rung position has become harder to land.

Why it matters: The entry-level crunch is real but uneven. Roles requiring direct client interaction, judgment under ambiguity, or working AI fluency are holding up. The "apply and wait" approach is the one under the most pressure. The fastest path into a strong role right now runs through demonstrated skills and direct relationships, not the standard application queue.

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Most employers are trying to figure out which team members are actually using AI well. A documented record of your own AI usage is valuable in performance reviews, job applications, and any conversation about team efficiency. Here's a prompt to build one in about 10 minutes:

"I've been using AI tools in my work. Help me document the impact clearly. Ask me three things: (1) what tasks I've used AI for, (2) roughly how much time each saves per week, and (3) what I do with the saved time. Then write a 3-5 bullet summary that a hiring manager or current manager would find credible and concrete. No fluff, no hype. Just documented impact with rough numbers."

Run that in Claude or ChatGPT. Use the output as a working doc you update once a month. It takes 10 minutes now and saves significant scrambling later.

The BLS Employment Situation for April drops May 8. March showed 178K jobs added and 4.3% unemployment. Today's GDP data shows strong AI investment but soft consumer spending. What will the April jobs number show?

(Last issue's prediction: BLS Employment Situation for April. Correct answer incoming May 8.)

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