Today is April 1st. Which means I could open this with something about how we're shutting down the agency, pivoting to artisanal hot sauce, or announcing a proprietary algorithm we're calling "LevelIQ."
I thought about it. Then I remembered how hard it is to get people to open email in the first place.
So: no pranks. Everything in this issue is real, but I've been thinking about what makes today different from every other day.
April 1st is the one day most people actually slow down before they share something. You see a headline, something that sounds a little too surprising or convenient, and before you forward it or post it or repeat it in a meeting, you stop. You check. You ask someone. You Google it. You think: is this actually true?
I wish that happened more on April 2nd through March 31st.
The instinct you have today, the one that makes you read twice and ask "wait, is this real?", is a useful one. The growth leaders I respect have gotten better at applying it outside of April. They ask harder questions of their own data. They push back on platform reporting. They want to know how they know what they think they know.
That's not slower. That's actually how you get to strategy you can defend.
No pranks today. Just the news.
Patrick Patterson
CEO at Level Agency
New episode: Good Enough Isn't
From Behaviors to Exits: The Business Psychology Behind Every Great Transition
Laurie Barkman has lived a lot of careers in one. One of the first professional digital marketers at American Eagle Outfitters. CEO of a 125-year-old logistics firm. Private equity veteran. Now she helps founders build businesses that don't collapse without them.
What ties all of it together is something she's believed since the beginning: business is psychology. The tools change. How people decide and trust doesn't.
In this episode, Myles and I sit down with Laurie to talk about exit readiness, anti-fragility, the entrepreneurial gene, and why hope is not a strategy. There's a lot in here for anyone who's building something and thinking about what it actually takes to make it transferable, valuable, and worth owning.
Level POV: Google's March 2026 core update Google's March core update is still rolling out, and the early signals are meaningful, particularly for sites in YMYL categories and content that leans on thin AI-generated pages. Our team broke down what we know, what we're watching, and what to do if you're seeing volatility. Read more
The ultimate campaign QA checklist for 2026 QA checklists don't make the highlight reel, but they're often the difference between campaigns that work and spend that disappears. This one from PPC Hero is worth bookmarking before your next major launch. If your team doesn't have a documented pre-flight process, this is a solid starting point. Read more
What Meta's and YouTube's legal losses mean for media buyers When major platforms take hits in court, the downstream effects on media buying aren't always obvious, but they matter. This Digiday briefing breaks down what the legal exposure could mean for ad pricing, inventory access, and where the leverage sits in the buyer-platform relationship going forward. Read more
Google adds scenario planner, PMax updates, and Veo Scenario planning inside Google Ads is a meaningful shift from reactive reporting to proactive budget modeling. The new Scenario Planner lets you simulate outcomes before committing spend, which is the kind of tool that changes how media conversations happen with clients. The Veo integration is worth watching on the creative side as well. Read more
Claude's paying user base is skyrocketing The AI consumer adoption curve isn't slowing. This TechCrunch piece on Anthropic's growth is a signal worth paying attention to, not just because of what it says about Claude, but because of what it says about where people are going to research, make decisions, and interact with content. The audience is moving. Read more
OpenAI's ad pilot hits $100 million in annualized revenue in six weeks Six weeks. That number is hard to sit with. The inventory in AI platforms is real, it's growing fast, and brands that are testing now are building a head start the rest of the market will spend the next two years chasing. This Reuters piece is a quick read but the stat is the story. Read more
Deep dive: AI
The experimental budget is no longer an experiment
The 80-20 rule, 80% to core channels, 20% to testing, has been a reliable budget framework for years. It's starting to bend.
According to Digiday's reporting, agencies are seeing clients push that test budget closer to 25%, and in some cases, they're not adding line items at all. They're just shifting existing dollars out of Meta and Google and into places like CTV, retail media, out-of-home, and now, AI ad placements. For Pawco, that meant a 10% increase to their marketing budget in Q1 specifically to account for AI and AEO tactics. Brands like The Knot are funding ChatGPT ad pilots directly from test-and-learn dollars.
Performance channels like Google and Meta are more saturated, reach is eroding, and AI is forcing businesses to find audiences in new places before competitors do. As one agency leader in the piece put it: there's no other option but to lean into new things.
What matters for growth leaders isn't which new channel to test. It's how to structure the testing so you're actually learning something. The brands getting the most out of expanded experimental budgets are the ones that shifted their KPIs and attribution expectations before they shifted the dollars. The spend is the easy part.
When something goes wrong with ad spend, who actually owns it?
MarTech's framing on this one is sharp: small mistakes in paid media can lead to massive losses, and ownership determines who absorbs the impact.
That word, ownership, is doing a lot of work. Most paid media teams have accountability in theory. Someone manages the campaign. Someone reviews the reports. But when spend goes sideways, the question of who actually had decision-making authority, and who was responsible for catching the error before it compounded, often doesn't have a clean answer.
The piece also surfaces something that's true at a lot of organizations right now: marketing budgets are increasingly driven by what teams can defend, not just what performs. That sounds like a small distinction, but it changes behavior. When defensibility is the standard, spend concentrates in a small set of trusted channels because those are the ones with familiar reporting, familiar benchmarks, and familiar excuses when things go sideways. It's a kind of risk aversion that looks like strategy.
The fix is clearer ownership at the campaign level, documented decision points, and escalation paths that exist before something breaks rather than after. Accountability structures built before the mistake are the ones that actually prevent them.
Google Stitch is a free AI design tool from Google Labs that generates high-fidelity user interface designs from natural language prompts. Describe what you want and it produces complete, multi-screen UI layouts with HTML and CSS you can actually hand to a developer.
Stitch can generate up to five interconnected screens at once, supports voice commands for real-time edits, and exports to Figma or developer tools via MCP.
For marketing teams, this means faster first drafts. Landing pages, campaign microsites, email layouts. Anything where design capacity is the bottleneck, Stitch cuts the time between brief and visual considerably.
What does ChatGPT actually say about you?
When a potential buyer asks an AI agent for a Top 5 list in your category, do you make the cut? More importantly: Why or why not?
Don't leave your brand’s reputation to an algorithm you haven't audited. Our scorecard pulls back the curtain on how AI platforms frame your brand sentiment and which sources they use to vet your authority.
Inside your custom report:
Sentiment analysis: Is the AI's summary of your brand accurate or outdated?
Citation audit: Discover which third-party sites are feeding the AI your info.
AEO roadmap: Immediate steps to improve your "AI discoverability."
