I solo founded a business and it just crossed 100K MRR (still solo). The trick is:
1. Don't give up after the first month of no traction, if you can get at least 1 customer at this stage that is a good sign.
2. Make contact with every customer you acquire, find out why they installed your product and what they want from it. Build any feature that they say is missing and offer the best customer support possible
3. Repeat this for a period of time. Once you have more customers the circumstances will change but this how you go from 0 -> 1 and get some runway IMO
Good advice. Do you think the part of point two about building every feature request might be a bit risky for some solo folks?
It’s easy to get carried away building every request, especially with early adopters who likely aren’t actually invested yet but may be excited about their own vision for it.
My personal experience is that too much of it leads to the product becoming a sort of shapeless, unwieldy ooze. Or perfect for one customer and few others. Some things can be tough to undo later too, so you might end up supporting them a lot longer than you’d like.
You've to go into founder mode - solve problems that exist for customers you've already discovered, rather than build something and expect magical "marketing" to find customers. The latter was previously a weak strategy, and is completely gone with the AI era. No alternative to working very closely with customers.
Honestly, I'm still not quite seeing how this fits into marketing. I get that we're focusing on our current customers, but how do we actually bring in new ones?
No magic pill: you can't work backwards. Pivot away from current idea if it's not getting word of mouth or any other traction, and for the next idea start with finding problems for people in your network that they will pay for.
Go looking for them wherever you think they might gather or hang out (online or in person). Reach out to those who seem like a good fit and ask them about the problem(s) they’re having that your product solves. Once you know if your product would actually solve it well for them, tell them about it in earnest.
If you’re doing that honestly, where they really have that problem and you actually have a good solution, you’d be a jerk not to lightly pitch it at that point.
You could probably do that up to 100 or so customers reasonably easily.
I’m working on Zigpoll[https://www.zigpoll.com], a lightweight survey/feedback tool for ecommerce (mostly Shopify).
Built it because most survey tools felt overgrown for what I needed. It focuses on post-purchase and on-site surveys, attribution questions, and getting clean data out.
Lately I’ve been working on:
Simpler targeting + survey logic
Exposing survey data to AI tools
Improving response rates without nagging users
It’s bootstrapped, profitable, and built by one person (me).
My one-person project Zigpoll [https://www.zigpoll.com] I've cracked the eCommerce market (1M ARR as of a couple days ago) but want to spread out more broadly into other verticals (SaaS, Hotels, Restaurants, Home Services, etc...) to reduce sector risk. If anyone is cooking something up please reach out and I'll be happy to hook you up with the service for free. [jason@zigpoll.com]
It’s literally all just context engineering. Just different ways of attempting to give the model the information it needs to complete your task. This is not a significant change to your interaction model with Claude
A lot of our customers use post purchase surveys and on-site surveys to help with this sort of thing. For example a really common use-case is an attribution survey which appears after a sale is made. The survey will ask something like "how did you hear about us?" which helps determine what actually drove the sale so they can get some clear insights outside of Google and Meta. It's not perfectly reliable but it's an additional data point that helps with the mess out there...
On-site surveys for eCommerce and SaaS. It's been an amazing ride leveling up back and forth between product, design, and marketing. Marketing is way more involved than most people on this site realize...
48 months solo is impressive. That marketing line is 100% true.
I'm building a tool that auto-generates ad creatives from a url (img-pt.com). Happy to run it on zigpoll.com and show you what it comes up with, if you think it can help you out.
I've seen people post this same advice and I agree with you that it works but you would think they would absorb this common strategy and integrate it as part of the underlying product at this point...
The people who build the models don't understand how to use the models. It's like asking people who design CPUs to build data-centers.
I've interviewed with three tier one AI labs and _no-one_ I talked to had any idea where the business value of their models came in.
Meanwhile Chinese labs are releasing open source models that do what you need. At this point I've build local agentic tools that are better than anything Claude and OAI have as paid offerings, including the $2,000 tier.
Of course they cost between a few dollars to a few hundred dollars per query so until hardware gets better they will stay happily behind corporate moats and be used by the people blessed to burn money like paper.
> The people who build the models don't understand how to use the models. It's like asking people who design CPUs to build data-centers.
This doesn't match the sentiment on hackernews and elsewhere that claude code is the superior agentic coding tool, as it's developed by one of the AI labs, instead of a developer tool company.
You don't see better ones from code tooling companies because the economics don't work out. No one is going to pay $1,000 for a two line change on a 500,000k line code base after waiting four hours.
LLMs today the equivalent of a 4bit ALU without memory being sold as a fully functional personal computer. And like ALUs today, you will need _thousands_ of LLMs to get anything useful done, also like ALUs in 1950 we're a long way off from a personal computer being possible.
That's $500k/yr, and I guarantee there's a non-zero amount of humans out there doing exactly that and getting paid that much, because of course we know that lines of code is a dumbass metric and the problem with large mature codebases is that because they're so large and mature, making changes is very difficult, especially when trying to fix hairy customer bugs in code that has a lot of interactions.
Doesn't specifically seem to jive with the claim Anthropic made where they were worried about Claude Code being their secret sauce, leaving them unsure whether to publicly release it. (I know some skeptical about that claim.)
A lot of it is integrated into the product at this point. If you have a particularly tricky bug, you can just tell Claude "I have this bug. I expected output 'foo' and got output 'bar'. What went wrong?" It will inspect the code and sometimes suggest a fix. If you run it and it still doesn't work, you can say "Nope, still not working", and Claude will add debug output to the whole program, tell you to run it again, and paste the debug output back into the console. Then it will use your example to write tests, and run against them.
I learned about JQBX and similar platforms through people that reached out as I've been sharing Jukebox around and they seem like they were beautiful corners of the internet.
We're building Zigpoll (https://www.zigpoll.com), a survey platform focused on zero-party data collection — think post-purchase attribution, customer feedback, and segmentation — all done directly on your site without relying on third-party cookies or offsite links.
We initially built it for Shopify, but now it’s fully embeddable, supports headless implementations, and integrates with tools like Klaviyo, Zapier, n8n, and Snowflake. One thing we’re especially proud of is how fast and unobtrusive it is: polls load async, don’t block rendering, and are optimized for mobile and low-latency responses.
From a tech angle:
Frontend is all React, optionally SSR-safe.
Backend is Node.js + Postgres, with a heavy focus on queueing + caching for real-time response pipelines.
API-first design (public API just launched: apidocs.zigpoll.com).
We recently open-sourced our n8n integration too.
If you're a dev working on ecom, SaaS, or even internal tooling and need a non-annoying way to collect structured feedback, happy to chat or get you set up. Feedback welcome — especially critical stuff. Always looking to improve.
1. Don't give up after the first month of no traction, if you can get at least 1 customer at this stage that is a good sign.
2. Make contact with every customer you acquire, find out why they installed your product and what they want from it. Build any feature that they say is missing and offer the best customer support possible
3. Repeat this for a period of time. Once you have more customers the circumstances will change but this how you go from 0 -> 1 and get some runway IMO
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