hey X π
I'm Aditya, doing growth at an AI startup @beanchors_
also building something in stealth for marketers tired of guessing which tool to buy π€«
here for growth, AI & startup convos
what are you building? let's connect π€
Founders who do their own marketing π
Growth folks at AI startups.
B2B marketers testing AI tools.
I want to meet you.
What's one growth experiment you're running this month? π
@OjasSharma276 Five straight days over βΉ2k is where it starts to look like a pattern, not luck π₯ What changed right before the streak, a new channel or something in the product itself?
@ZidaneZ08902030@X Dev tools + building in public is a fun mix π οΈ For your job platform, what's been the harder part so far: getting candidates in, or getting them to come back after their first application?
Hot take π₯
Most early startups don't have a growth problem.
They have a positioning problem.
If people can't repeat what you do in one line, they won't share it.
Agree or disagree?
@Artie_Martello@X Curious what you hear on the podcast side, Artie: are guests more excited about AI for building the product, or for distribution? Feels like the second one is where most founders still get stuck π€
Find your customers' language before writing landing page copy:
Read 20-30 reviews of the tools your users already pay for.
The exact phrases in their complaints usually beat any headline you brainstorm, and show which feature to lead with.
@sajithpai Good reminder that ads quietly decide the price customers see. Same pattern as free SaaS tiers funded by a few big accounts.
Do you think Indian papers can hold that subsidy as ad money keeps moving to digital?
@tonyaibuilds #2 feels like the most underrated one. Asking for ways it could be wrong surfaces assumptions a plain "double-check this" never does.
Do you run these in one prompt or as a second pass?
The hidden cost of AI features: success raises your costs.
Old SaaS got cheaper per user as it grew. AI products can get more expensive.
Founders, are you pricing AI usage separately yet? https://t.co/gIHA84qZMS
Canva's new AI got so popular this year that it forced the company to cut its growth forecast by a third.
The more people used it, the bigger the bill got, because too many of those requests ran on models Canva rented from the big AI labs. Growth guidance fell from 30% to 20%, and its biggest backers marked it down from $42 billion to $34.9 billion. Melanie Perkins, the CEO, told shareholders, "We were relying too heavily on frontier models."
This week Canva shipped its way out, a model called Brush.
Canva's 160-person research lab built it on top of an open-weights model, then trained it on Canva's own templates, editing data from users who opted in, and grades from the company's staff designers. It edits a deck about the way you would. Writes a little code, nudges the layout, checks how it looks, goes again. Canva says it's 46% cheaper per task than the agent it replaces, and up to 69% faster.
At Canva's size, 46% is the whole ballgame.
265 million people use Canva every month. Even a dime per user per month in AI costs would add up to $318 million a year. Cliff Obrecht, the co-founder, said the cost to serve a user went "from cents per month to now many, many more cents per month."
So Canva has been swapping rented models for its own, one job at a time. It says its in-house style-transfer model runs 23x cheaper than the frontier version, its image model 30x cheaper and its video model 17x. Cost per AI task is down nearly 90% since April. Brush brings that same play to editing, the part where you fiddle with a design until it finally looks right.
Renting the big labs' models is how Canva found out what 265 million people actually wanted, and Brush is how it plans to afford giving it to them.
@soham_nayak04 That gap is wild π€― Are the verified impressions coming more from your replies on big accounts or from your own posts? Feels like those two reach very different crowds.