- jaypeters.dev
- Posts
- Video Processing, Micro-SaaS and Bubbles
Wave payments on hold this week to focus on video uploads instead.
Plus it looks like n8n doesn’t want workflows to be paid services.
And are we in a bubble?
Topics for this week:
Rebuilding TikTok
I have new respect for video-based apps.
Trying to replicate TikTok’s multi-billion dollar video platform is not easy to do.
I was happy to get an initial version working in Wave that looked like TikTok-style video swiping, and even managed to setup a cheap way to make it work with real videos, but that cheap approach may already be reaching it’s limit.
AWS App Runner is handling all the video processing on the backend at the moment.
Users upload their video to the virtual machine and it strips metadata and compresses it down so it can be quickly loaded during swiping.
But it seems that basic system may already be reaching it’s limits with a few users.
I’m trying to balance decent user experience with cost effectiveness while Wave isn’t making a ton of money to fund its infrastructure, but it could prove challenging.
The lone App Runner instance probably won’t cut it.
I upgraded the App Runner VM itself, from .5 vCPU with 1 GB of RAM to 1 vCPU with 2 GB of RAM, but concurrency is still going to be an issue.
A few video uploads at the same time or back to back and that will start to cap out again.
Probably going to need implement a queuing system first and foremost.
Chatting with a few AI models, it sounds like App Runner can lead the processing but also offload to Lambda if things get a little busy.
And users will have to wait a little.
The next biggest performance improvement would most likely be chunking video data so it can process immediately.
Lots to look into but I’m looking forward to building something that can reliably manage a burst of upload traffic on a busy Saturday night.
More to come on Wave’s slow replacement of TikTok and Instagram.
Reading Handwritten Documents
I made a video about this process a little while ago, where I was demonstrating how to use n8n to read the contents of a PDF and fill out other data columns within Monday.com using the content, saving the effort of having to manually enter customer data.
But I managed to completely forget to try that system with handwritten documents.
If the doc is nicely printed, n8n can turn the PDF to text with no problems.
If it’s handwritten, n8n completely gives up and returns no text from the document.
So rather than having to install another community node to convert the PDF to an image, I finally found a way to have gpt-5-mini read the document instead.
I knew GPT could handle it because I took the handwritten document and uploaded into the ChatGPT app on my MacBook, and GPT read the text back to me right away.
Unfortunately it’s not as straightforward to do in n8n.
Took a couple different HTTP Request node attempts to finally figure out how to have n8n call OpenAI to read the contents of a document.
But this video covers the full process.
This could be a really handy one even for things outside Monday.com.
The Dead Internet Discussion
We managed to not wait another year for Episode 12 of the Dev Sync after our triumphant return with Episode 11 last month.
Jim, Eric and I recorded a new episode last night about the “dead internet” theory.
It’s a theory that came about around 2016 that all of the internet is just bots talking to bots.
Surprisingly though, last year may have been the first year that bot traffic overtook human activity on the internet, leading by 51%, so bot activity is certainly on the rise thanks to LLMs.
We dive deeper into that, and try not to get too distracted with AI related topics like it’s impact on the future of the internet and how work is changing in general.
It was another quick 50+ minutes, and the full episode should be up on Monday.
Stay tuned!
And here’s Episode 11 in the meantime:
n8n to Micro-SaaS
I’ve been circling around the micro-saas idea for a long time and I may have a reason to dive into it soon.
I accidentally essentially built a SaaS using n8n when I was working on the course generation system during livestream sessions.
With the completion of version 1 of that project, I got curious about turning it into a full platform that people could pay to use.
My first thought was I could just vibe-code a front-end for users to sign up and pay to access the app, then the backend would kickoff the workflow to generate the course.
I’m not sure at this point, but this approach may fall into a bit of a gray-area.
According to their sustainable use policy, you can’t use n8n for commercial purposes if the value of the service derives entirely or substantially from n8n functionality.
Turning a workflow into a SaaS could potentially violate that policy since a substantial amount of value would be operating through n8n.
At it’s core, I think they are trying to prevent people from reselling access to the n8n platform, like vibe-coding a new website that just uses n8n nodes underneath and charges for access to a custom no-code platform.
And arguably, it would still take a substantial custom web app to turn an n8n workflow into a SaaS.
It would require a full website for users to signup and login, a backend like Supabase to manage the session and store user and transaction data, and a Stripe integration to handle payments for the service before ever kicking off the n8n workflow from a webhook.
But most of the value of the app would derive from the n8n workflow creating the resulting deliverable.
So to be safe, I don’t know that I’ll be connecting an n8n workflow to a website and charging for access unfortunately.
The alternative will probably look something like Go microservices hosted in Lambda, replacing the n8n workflow.
Kicking around a few candidates for this approach so more to come on that, but I know for sure n8n will remain just an automation platform for now.
The Bubble
The hot debate right now in tech and the markets is if AI is a bubble.
A few weeks ago, Sam Altman himself admitted we may be in an AI bubble.
And the common comparison is to the “dot com” bubble of 2000.
But I heard an interesting point the other day about why this AI bubble is different from the dot com bubble.
According to Gavin Baker, Managing Partner and CIO of Atreides Management (nice Dune reference), during the 2000 bubble, there was a metric of something called “dark fiber.”
Fiber optic cables are laid down in the ground for internet traffic, but if the cables aren’t lit up for use, it’s just dark fiber.
At the time, 100s of thousands of miles of dark fiber was laid for the expected internet boom, but at the peak, 97% of the fiber in America was still dark.
Only 3% was in use for the internet.
AI, right now, has the opposite problem.
No company can get enough GPU’s to run their AI models.
GPUs are melting from use instead.
There’s no shortage of traffic.
The AI bubble could be a different kind of bubble, though.
NVIDIA has positioned itself nicely at the center of the AI race as the primary manufacturer of the GPUs needed for AI models to run in the cloud, so if NVIDIA makes a mistake or runs into trouble, it could have massive consequences.
But at the same time, all the other AI companies are scrambling to come up with alternatives so that not everyone is reliant on one primary source of GPUs.
AMD and a number of other chip manufactures are stepping-up for sure, even new ideas for chip architecture and processing concepts are entering the market with all of this pressure, so new options are showing up to spread the stress.
So right now we might be in an NVIDIA bubble.
But only time will tell.
It was really interesting to hear the dot com bubble described with a single metric like dark fiber after looking back 25 years.
I’ll be curious to see if there’s one defining metric for the current AI bubble when looking back 25 years from 2050.
And that’s it for this week. Video uploads, micro-saas infrastructure and bubbles, what more could you ask for.
If you want to start a newsletter like this on beehiiv and support me in the process, here’s my referral link: https://www.beehiiv.com/?via=jay-peters.
I also have a Free Skool community if you want to join for n8n workflows and more AI talk: https://www.skool.com/learn-automation-ai/about?ref=1c7ba6137dfc45878406f6f6fcf2c316
Let me know what else I missed! I’d love to hear your feedback at @jaypetersdotdev or email [email protected].
Thanks for reading!