Something I heard recently on some podcast which really resonated was (paraphrasing): "Inertia is the biggest issue for a startup. The world doesn't like you, doesn't think it needs you... and you've got to invert that. You have to create momentum by scratch and the most important thing a founder does, by an order of magnitude, is invert inertia. Literally, in a physical sense. Like the world stays at rest and you've got to create momentum." With that in mind, it makes sense to do things that don't scale... because in the beginning, you're not trying to optimize a machine that's already running. You're trying to get the engine to turn over at all. PG's point is that scalable growth comes later; first, you have to manually crank the thing into motion. You do manual stuff not because it's efficient, but because it's the only way to get traction when no one's looking for you in the first place. And that's how you learn what actually works, how you build momentum one user at a time, and how you prove there's something worth scaling at all.
I also think that the biggest value in doing things manually is that you actually learn.
One of my clients used to make a nice curated list of the important financial and stock market news of the week, it was a niche part of a niche product but people loved it.
At some point he thought about automating everything, it became less curated, more spammy, it lost any value and in the end so did the product. Sure there was more news, but it was less curated, edited and the signal to noise ratio got worse.
In fact what they did manually was more valuable even if the scope was smaller.
Many companies don't understand that and rush into premature optimization.
I'll have another example: one of my clients wanted a scraper to automate something his company needed to do manually: check competitors prices on their ecommerces.
I built it, way simpler than they wanted (they thought they wanted an app with a proper front end, turns out it was better for both to produce an excel spreadsheet with the data) and they were happy.
Then after some time they understood that they were missing part of the experience: navigating their competitors manually allowed them to see new approaches to show the catalogue, new trends and products, they were actually learning from the competition.
Eventually they realized and got back to doing it, and left my scraper just for price analysis.
But the overwhelming majority of my clients keep putting automation before the product and problem and misses important learning opportunities.
People focus on the primary function they want to automate and forget about all the ancillary functions and effects, which, in aggregate, can be as important as the core function.
That's a really good point, doing things manually is an important part of being connected to a job and its outcomes. I will also say, sometimes you need a few hours of little manual tasks to break up the day between brain-heavy tasks.
Similar thing happens in sales. A gen-AI driven sales tool might write perfect copy and reach 1000 people. But when you go by each person and write a hand-written email to them, the ancillary thing is that you learn about that person. You develop intuition about what sort of people would be right people and develop a perspective about why you can solve their problem or not. This completely gets lost when you automate and play numbers game. This is especially important in zero to one phase.
“Inverting inertia” is a great framing, but it mostly applies to one type of startup. Sequoia’s Arc framework shows there are three paths: Hair on Fire (urgent pain, momentum matters), Hard Fact (people live with the pain, you have to change habits), and Future Vision (people don’t even believe it’s possible, you need to build credibility). Doing unscalable things is vital in Hair on Fire, but in the other two paths the playbook is more about reframing reality or creating belief before momentum even starts.
