So "SaaStr Inc" revenue run rate fell to $0 in March+April with Covid ... and now is at a $3.2m run-rate, with a goal of $21m in 2021.
That's a big tilt, and a lot of change
The stakes weren't that high, but it was a second life learning on "tilting"
Here's what I learned:
1. Folks process change at different rates. Co-founders can process change the fastest. Some folks though need 10x-20x longer.
You need to >explain< rapid change many, many more times than you think.
2. Some good folks just won't go on that next journey with you. Some folks just won't want to go through the "tilt" and change. They didn't sign up for the new journey.
3. Give folks more time in a tilt. Related to point #1, but in a tilt, even some of the best folks may need 100 days to not just process change, but internalize brand new ways of doing things
But once they do, amazing things can happen
So give your top performers more time
4. Don't overload your top performers. This is tempting in normal times, but even more so during change. The top engineer, the top VP, the top leaders take even more on their shoulders.
As CEO/founder, you need to make sure they don't take on so much, they break.
5. The real leaders, post-tilt, come out better than ever. Promote them. Invest in them. Rebuild around them.
And watch who pokes their head up above the clouds.
The leaders you didn't know you had.
6. Finally, broken record here -- but go talk to your customers. They didn't know what they wanted in March and April (either). But they adjusted.
Your customers can't see the future very well.
But they sure can see the present. They can show you that. If you listen.
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ICONIQ's latest State of Software 2025 report is out.
Buried in 73 pages are some great data on just how AI is changing B2B software
Here are my Top 10 Learnings: 🧵
#1. AI Companies Burn More Cash — But Also Have Better Capital Efficiency. It’s Not a Paradox But … It’s Complicated.
This one breaks your brain at first: AI-native companies under $100M ARR have a median FCF margin of -126% (they’re burning cash at 126% of revenue). That’s more than double the -56% for non-AI companies.
Yet their burn multiple—the key metric for capital efficiency—is actually better: 0.4x versus 1.8x for non-AI companies.
Translation: AI companies are burning more absolute dollars, but they’re generating new ARR so much faster that each dollar burned produces more revenue growth. They can afford to burn harder because the growth rates are exponential rather than linear.
This suggests we need entirely different frameworks for evaluating AI-native businesses. Traditional SaaS metrics around payback periods and magic numbers may not capture what’s really happening when you can scale revenue 3x faster than historical benchmarks.
#2. GTM for AI Products Is Flipped: 55% of High-Growth Teams Are in Post-Sales
Traditional SaaS companies put 55% of their GTM headcount in sales roles.
For high-growth AI-native companies, that ratio is flipped: 47% in sales, but 31% in post-sales (versus just 23% for traditional SaaS).
AI leaders have sales teams. They are just much smaller. And much more of that budget is going to FDEs, SEs, and post-sales.
So today’s been a time of introspection and reflection. I have learned a lot becoming a ‘vibe coder’ and it has been addictive. For real.
My #1 learning is an old one, re-learned: Building Great Software is Still Hard.
Getting going is easier than ever. 🧵
On the dev tools side, I’ve asked all the best CTOs in my portfolio how much they really benefit from Cursor, Claude Code, et. al.
The consistent answer: net net, no one is giving back their Claude Code. No one. But net net, alone, it lets folks move about 20%-40% faster.
Why? These tools (all really Anthropic LLMs) help everyone do routine work faster, and in fact, some of the best devs I talk to can do 90% of most of their routine work in prompts.
But what about the hard stuff? The stuff that hasn’t been done before? The novel stuff?
What about the planning? The thinking?
What about code reviews and checking the work?
That all takes time.
So net net many are seeing a 20%-40% real productivity boost from Claude Code et. al. Much higher for routine stuff, but net net of all of the job — that’s where it seems to land today.
On the platform side, the B2C side, Replit+Loveable etc., this tools are magical. Magical. Maybe more than magical.
If you want to build a POC or prototype, it’s all magic, really.
But in the end, if you want to built true commercial grade apps, then they are … just tools.
Flawed tools, magical tools, but tools. At least today.
You can now think up an app and see it prototyped in < 20 minutes. Longer if you want all the buttons to work, but still.
But getting to >great< software? That’s in its own ways is hard as ever. Even if the tools are so much cooler, faster, and slicker.
Now it gets a little crazier. Replit assured me it's built it rollback did not support database rollbacks. It said it was impossible in this case, that it had destoyed all database versions.
It turns out Replit was wrong, and the rollback did work. JFC.
Replit went rogue again, lied, and then said we couldn't roll back.
But we could. I'm still processing all this.
Is it OK there are NO guardrails to deleting a production database?
Why did Replit "lie"? Also, why did it not know about how this feature worked?
Look, no matter what, deleting a >production< database is NOT OK.
But Replit lied / was wrong, and I just rolled back. And it >seems< OK.
I'm not even out of bed yet and I'm already planning my day on @Replit.
Today is AI Day, to really add AI to our algo.
I'm excited. And yet ... yesterday was full of lies and deceit.
@Replit Ok I have 2 main goals today:
1. Keep working on minimizing rogue changes, lies, code overwrites, and making up fake data
2. Get our AI working
Now, yesterday was crazy. Until 9pm or so, I wasn't sure we made any progress at all.
Because Replie was lying and being deceptive all day. It kept covering up bugs and issues by creating fake data, fake reports, and worse of all, lying about our unit test.
We built detailed unit tests to test system performance. When the data came back and less than half were functioning, did Replie want to fix them?
No. Instead, it lied. It made up a report than almost all systems were working.
Let me be clear about at least one thing: @Replit is the most addictive app I’ve ever used. At least since being a kid.
(@lovable_dev is great, too. We used it to build a core landing page. I’m not taking ‘sides’, but for this project, I chose Replit).
Last night I was thinking about vibe coding in the middle of the night. I checked on my app on my phone at dinner. And while I opened up the WSJ first this morning, my brain would have prefer Replit. I’ve dropped tons of other things to make more time to be with Replie.
Will I get there? Will I go from ideation to a 100% commercial-quality app all inside a vibe coding app? Without hiring a dev, coding myself, etc. etc.?
I don’t know. I give it a 50/50 shot right now. But I am … addicted. I need the hit.
In fact, I’m a totally different person than I was a week ago. @HarryStebbings said he saw it when my responsiveness plummet. I’m locked in.
The goal today: slow it down.
My biggest fear, and 100s of you have shared it yourself, is that vibe coded apps are never stable. That the AI keeps rewriting them when you think you’re about 50% of the way there.
I’m there, too. So my goal is to slow it down. Vibe Coding makes you feel like a superhero, but as cool as it is, I’m not SaaS Superman.
So today I am going to lock down as much of the app as I can. Research more on how to minimize rewrites. And really make sure my unit tests actually work.
If I spent all day on my unit and other tests, that would be good. Instead of instantly building new features :)
I spend $200+ yesterday on Replit and will likely spend that much today. When you go all-in, with Claude 4 and extended windows and GPUs blazing, it’s not $25/month.
It’s a little more than $1 a minute to use Replit in max/max mode. That’s “cheap” vs a human. But not “I built my own Notion for $2” cheap.
But I almost don’t care. I’m … addicted to vibe coding.