What the viral Anthropic story actually means for your job
If you work on or around a growth team, you’ve probably seen this
If you work on or around a growth team, you’ve probably seen this story by now👇👇
It’s a really cool story that went mega-viral across Twitter and Linkedin.
And it split the growth community into two camps.
Camp one: this is a glimpse of the future, and AI is about to replace whole marketing and growth departments.
Camp two: cool story, but not a big deal. Early-stage teams have always run lean. This is just the next version of the tools we've always used to do the job.
After coaching 90+ growth leaders over the past 5 years (directors, VPs, heads of growth) and being a 2x head of growth myself - here's where I land.
The time and resources it takes to do world-class growth work dramatically decreased.
Stuff that used to take 30 minutes takes 30 seconds. Work that used to need an engineer doesn’t. Work that used to need a designer doesn’t. The data request that used to mean a ticket and a 2-week wait now happens in a couple of prompts.
When the cost of execution drops like that, the things that make you valuable change too. Some skills get commoditized. Others get a lot more valuable.
I see 5 shifts happening right now.
Let’s get into it.
Shift 1: Judgement over output
Growth marketers are obsessed with improving conversion rates. That’s how we measure our impact, and that’s an important outcome of the work that we do.
The way you move those conversion numbers… is by trying a lot of stuff.
Because most of the experiments we run won’t work. Maybe 1 out of every 3 is a winner, so you have to take a lot of shots to find the wins.
So we prioritize output.
The campaigns, the landing pages, the creatives, the CRO tweaks. We need a high volume of it, because volume is how you find the handful of things that actually move the needle.
And over time, that volume becomes the thing we point to.
It’s the stuff that ends up in our self-evals. How many campaigns we launched. How many landing pages we tested. How many creatives we shipped. How many pages we optimized.To push the volume even harder, many teams set goals around the number of experiments shipped.
There’s a good intention behind that.
But like many OKRs, people gamed it. They shipped a pile of tiny, low-stakes tests to hit the number. Activity went up. Business impact didn’t.
I did this too.
When I was scaling my first team, I didn’t always know the highest-impact work, so I prioritized speed and volume. Button copy. Color changes. Headline swaps. I danced around the big, scary, hard-to-execute bets, because I didn’t want to spend the political capital to fight for the resources.
Here’s what changed. Anyone getting savvy with these tools can ship hundreds of experiments a quarter now. Volume stopped being a differentiator.
So the growth marketer who still points to that volume as proof they’re valuable is the one at risk in this new world. Their resume reads like everyone else’s, a long list of stuff they tried, because everyone can do that now.
The growth marketer who pulls ahead can point to a small number of bets that actually mattered. They can tell you why they picked those bets, and what it did for the business.
The most valuable skill in growth right now is figuring out what’s worth testing, and why.
Instead of asking “could we test this,” they’re asking “should we test this.”
Shift 2: Curiosity over caution
A lot of the growth marketers I talk to spent the last 18 months keeping AI at arm’s length.
For understandable reasons.
For a while, the hype was way ahead of what the tools could actually do.
And we couldn’t keep up with the pace of new tools and still hit the goals right in front of us. And if we’re being real, a lot of our community was nervous. The rhetoric said AI was coming for our jobs, so why would you welcome it in with open arms?
That was me for a while too.
The first wave of AI marketing tools wasn’t impressive. They were fast, but lacking quality. We didn’t have the MCPs and integrations we have now. So I dabbled. But I wasn’t sold yet.
Same with most of my clients.
They had top-down OKRs to use more AI, but weren’t sure where to apply it. A lot of them used AI to get to the same place a different way, without finding any real leverage. That’s changed.
I’m watching some of my clients pull ahead of their peers, with the same budget and the same constraints as everyone else.
The difference is they’re more curious.
One client, “Alex” the head of growth at a B2C startup - had goals from his execs to use more AI. He told me AI used to feel like the boogeyman.
Something spooky he didn’t fully understand and wanted to keep at a distance.
Then a few months ago he leaned in. Hooked up all his MCPs, started playing with Claude Code. Built his first couple of agents. Here’s roughly what he told me on a recent call:
“Dude, I’m going crazy with AI. I’m having so much fun. Claude Code has been the ultimate cheat code. I’ve hooked all my disconnected tools and data into one hive mind. It feels like I have the world at my fingertips. It’s even improved my mental health, because for a long time this felt like the boogeyman, and leaning in changed my outlook on the future.”
A senior growth leader telling me his mental health at work got better because he stopped fighting AI and started building with it.
The growth marketer waiting for someone else to figure out the playbook, the right tool, the validated framework, is at risk today. Every day you wait is a day of reps you’re not getting.
The growth marketer pulling ahead is already in the lab.
They’re building. Connecting things. Learning by doing, even though it’s messy and confusing. Curiosity is becoming one of the most defensible skills you have.
Shift 3: Surface area over specialty
The real story here is how much one growth marketer can do on their own now. (This is basically the Anthropic story.)
Another client, “Francis”, the head of growth at a big, popular consumer AI startup. He lost his dedicated growth engineer, who got pulled back to core product work.
So Francis leaned in and figured out if he could do it himself.
He connected his MCPs to Snowflake and the company’s codebase, all wired into Claude Code. Now when he wants to test something, Claude knows which data to pull, runs the analysis, calculates significance, and writes the code to ship the experiment live.
Last month he ran a test that drove a 17% lift in revenue from the test cohort. He shipped it solo. Claude did what used to be 3 people’s jobs.
And the part worth highlighting: the hypothesis, the design, the read on the data, all of that came from Francis. Claude helped him ship it.
I see the same thing in my own work.
A few years ago, a custom dashboard meant a ticket to the data analyst, a 2-week wait, and a couple of meetings about formatting. Now it’s 3 minutes and a couple of prompts. I’ve got 10x more dashboards than I did 2 years ago, because I can do it myself.
The growth marketer who was valuable because they specialized in one thing (the Google Ads person, the lifecycle email person, the CRO person, etc) is in a tougher spot now.
The growth marketer getting more valuable can absorb the adjacent work, because the surface area one person can cover just expanded. One person owns the experiment design, the data pull, the code, and the read.
I’m even seeing a few directors and VPs with no direct reports who set the strategy and own most of the execution.
Strategy is the real work. Execution is the part AI helps with.
(I’ve watched a few people flip this and hand the strategy to the AI while they go do the execution. In my experience that hasn’t worked nearly as well, yet.)
Shift 4: Business problem first
This is the question I’m getting from heads of growth on almost every call right now: who on my team is actually safe, and who isn’t?
I’m seeing a pattern. The people most at risk walk into every room with a tactic instead of a business problem. Their starting point is “what should we ship?” or “I can do more with AI now, so what should we do?” The better starting point is “what does the business actually need here?”
When execution was the hard part, you could be a tactical, campaign-first thinker and still look productive, because everything took forever to build and the slow execution cycle covered for the missing strategy.
Now anyone can ship in 20 minutes.
Back to Alex. His team executes like crazy, thinking in sprint cycles and feature releases, rarely stepping back to ask what the most important work even is and how it ties to the company’s goals. That’s the muscle to build.
The growth marketer who fully understands the business problems, then works backward into the projects is worth a lot more than they were a year ago.
The growth marketer who walks in with a tactic looking for a reason to ship it is now competing with a $20-a-month subscription.
The value is knowing which campaign to run to move the business.
Shift 5: Learning over shipping
The first 4 shifts are about you as an individual. This one’s about how you run the team. And it’s what separates the growth leaders the rest of the org can’t live without from the ones who could be replaced tomorrow.
AI changed how we ship, and in the process it exposed what a growth team actually produces.
We care about wins and growth rate, obviously. But the way we get there is by learning what works and what doesn’t.
The learning is the real product.
Here’s why that matters. A growth team usually works at optimization. The company already went 0 to 1. There’s a working growth model and a few channels that convert. Your job is breaking through the conversion plateaus to get to the next level.
Most of the time we don’t actually know what’ll work.
We have hunches. Segmentation, maybe. Or the copy. Or a friction point in the UX. We call them hypotheses, but a lot of time, we won’t know until we try.
If you’re at huge volume, you can spray and pray. The rest of us can’t.
So the job gets specific. What are we testing? Why? What do we expect to learn? And who else in the company benefits from that learning?
That last question is the one most teams skip. I skipped it. I was so locked onto my team’s number that I treated everything else as someone else’s problem. Product shipped things that contradicted what we’d learned in activation. Sales used copy on calls that we’d already proven didn’t convert on landing pages and paid ads.
We left a pile of free wins on the table, because I ran the team like a shipping factory instead of a learning and enablement function.
Done well, it’s a process with 4 steps:
Ideation. Build a backlog of strong ideas that could move the KPI.
Prioritization. Use a framework to pick the right bet, not the loudest or most senior person’s pick.
Experiment design. Write down what you hope to learn, how you’ll know if it worked, when you’ll move on if it doesn’t, and who else should see the result.
Wins/losses tracker. Capture what worked, what didn’t, and why, so it compounds over time and doesn’t walk out the door when someone leaves.
We used to do all of this by hand. Now AI does most of it. The hard part is the discipline to actually follow the process once it’s in place.
And once you learn something valuable, every team that touches the customer needs to know too.
Product needs to know what’s working in activation. Sales needs to know which messaging converts. CS needs to know which signals point to expansion or churn risk.
If you keep your learnings inside your team’s four walls you’ll waste most of their value.
The growth leader who runs their team like an execution factory, head down, clawing toward the number, hoarding the learnings, gets stuck. They look productive. They are productive. But the rest of the org doesn’t actually need them there.
The growth leader who runs the team like a learning and enablement function is the one the org can’t live without. Product depends on them. Sales gets better because of them. CS improves. Execs prioritize their work, because it makes everyone smarter.
The learnings, and how you spread them, are the product. Campaigns and wins are the byproduct.
I broke the whole thing down on YouTube where I post stuff like this every week for people who work on and around growth teams.
And if you’re looking for some more support, there are 2 ways I can help:
The Head of Growth Guide. The full system I implement with my coaching clients. It’s the playbook I wish I’d had when I was head of growth myself. [LINK]
1:1 coaching. If you’re working through something specific and want a thinking partner who’s been in the seat, I take on a small number of clients at a time.