Built a Chrome extension to stop getting cut off by Claude — 70 users in 4 weeks, zero marketing budget

The company-account-vs-personal-account thing hit close to home. I've been stuck on a similar wall — every "official" channel I try (subreddits, ads) either gets rate-limited by self-promo rules or costs money before I even know if it's the right audience. Haven't tried leaning on a personal account yet, but this makes me want to.

Also, the GSC numbers you shared are basically the same thing I was staring at this week — impressions barely showing up, average position stuck way down the list. Good reminder that "it's indexed" and "anyone can actually find it" are two very different problems.

Curious how you picked which platforms to support first (Claude, ChatGPT, Gemini, etc.) — did you build for the one you personally used most, then add the rest once people asked, or did you map it out ahead of time?

Great example of solving your own pain point and shipping fast. 70 users with zero marketing is a strong start 🚀

I'd make the difference between Claude's actual limit data and outside estimates impossible to miss in the UI. For each number, show whether the platform reported it or someone estimated it. Also show when it was last updated. Estimates can still help, but people may make bad decisions if they look as reliable as the actual data.

The personal LinkedIn beating the company page isn't a fluke, it's the default state before you've earned any brand equity. People trust a name they can picture over a logo with zero history, so a founder's own account is almost always the fastest distribution channel available in the early days. I'd put the VSCode extension and timeline feature on hold and keep posting from your personal account, one good post from you will out-convert a quarter of roadmap work right now.

Your sharpest lesson isn't in the "what worked" list, it's a fault line running under the whole thing, and naming it changes what you build next. Your single differentiator, "exact Claude numbers pulled directly from Claude's internal API," is also your single biggest fragility, because they're the same fact. Every other platform is client-side estimation; only Claude gives you real data, through an undocumented internal endpoint you don't control and weren't handed. Your moat is real, but it's rented from a landlord who doesn't know you're a tenant. That endpoint can change shape or close any week, no warning, exactly like the rate limit that started this.

That's fine as a wedge, it's why you stand out at install. It's dangerous as a foundation for Pro. Picture the churn moment: someone pays for "exact Claude tracking," the endpoint shifts, and their paid feature silently degrades to the same estimate the free tools give. That's the worst possible time to break a promise, right after money changed hands.

But your own roadmap already contains the escape, you just have it sequenced behind the risk. The "AI usage timeline across every tool" is the durable product, and you said it yourself, that's the thing that stops being a rate-limit tracker and starts being AI-workflow understanding. Notice what it doesn't need: Claude's internal endpoint. A timeline of your own interactions is data you can capture client-side, equally, on every platform, with no landlord. The exact-numbers wedge gets people in the door; the cross-tool layer is what you actually own.

So the question I'd weigh before building Pro: how much of the paid tier leans on the one number Anthropic can take away, versus the workflow view nobody can? Shift the weight toward the second and the fragility becomes a feature you grew out of.

70 users in 4 weeks with zero ad spend is a pretty strong signal that you’re solving a real problem. I also liked the point about users preferring the in-page bar over the popup — a good reminder that the simplest part of a product can end up being the most valuable.

the personal-vs-company-account data point is the one I needed to read today honestly. I've been building a branded account from zero (not a personal one) for a few weeks now, which is precisely the "company account with no followers" pattern you're describing as the thing that didn't work for you. makes me wonder if I should be posting some of this from my own personal account too, borrowing whatever existing trust/audience I have, rather than assuming a clean brand account earns attention on its own from a standing start

"designing for 100 users before having 10" is also a pattern I recognize from a thread earlier this week about a much more ambitious project than yours, seems like a universal trap regardless of scope, infrastructure work feels like progress and is much easier to justify than sitting with the discomfort of not knowing if the core thing works yet

question on TokenPulse itself: does the rate-limit percentage ever create a perverse incentive, does showing someone "you're at 85%" change their actual usage behavior (rationing) versus just informing them after the fact? curious if you've noticed the visibility itself altering the thing it measures

The part about building for 100 users before having 10 really hit home for me.

I’ve been building an Android music platform with an AI-assisted workflow using Codex, and I’ve noticed the same temptation: once development becomes dramatically faster, it’s very easy to keep adding features because suddenly they feel “cheap” to build.

But the hidden cost shows up later in testing, regressions and product complexity. In my case, features like persistent playback, gapless transitions, synchronized lyrics and interactive controls all work together, so a seemingly small change can affect something that was already stable.

Your point about the content-script test harness is especially interesting. AI can make implementation extremely fast, but if the testing loop is still slow, that quickly becomes the real bottleneck.

Also interesting that the in-page bar ended up being more valuable than the popup. That’s a great example of users deciding what the actual product is.

For the DOM integrations across Claude, ChatGPT, Gemini, DeepSeek and Grok: do you have any automated way of detecting when one of the platforms changes its DOM and breaks a selector, or do you currently discover those failures through users/manual testing?

The lesson about designing for 100 users before having 10 really stood out to me. It’s very easy to keep adding advanced features because they make the roadmap look impressive, even when the basic workflow has not been validated yet.

I’m currently building an early backtesting project, and this is a useful reminder to get a small number of people through the complete workflow before investing heavily in features such as multi-asset analysis or Monte Carlo simulations.

The in-page bar is also a great example of users revealing the real product. The popup contained more information, but the lightweight element shown at exactly the right moment delivered more value.

How did you collect feedback from the first users—direct conversations, Chrome Web Store reviews, or usage analytics?

Clever solve for a genuinely annoying problem — losing context mid-debug is brutal.

Since you're shipping a browser extension that touches multiple AI platforms, one thing worth keeping an eye on: manifest and content-script permissions can become security debt fast (especially MV3). If you ever want a second pair of eyes on the codebase — we built SecondRead specifically to audit AI-built projects for non-technical founders. Security holes, cost sinks, scaling bottlenecks. Happy to run a free beta audit on TokenPulse if useful — no strings attached.

Love the idea, always feel stuck when it stops midway. Claude should simply allow the last prompt to finish instead of stopping midway like Codex.

The ±8% line is the best part of this post, publishing the error band on an estimate instead of pretending it's exact. One suggestion: put that ±8% in the UI itself, not just the writeup. People trust a meter more when it admits its precision. 70 users in 4 weeks on zero budget is real traction.

The zero-marketing-budget path you took is the interesting part here - 70 users in 4 weeks from just showing up in threads like this one is a real signal. One suggestion from watching hardware-adjacent communities: the people who hit rate limits mid-session are the loudest, but the bigger audience is people who don't know a limit is coming until their workflow dies. A landing section that shows the bar working in a GIF might convert that second group better than the story does. Congrats on shipping six weekends of work - MV3 alone deserves a medal.

So I ran tokenpulse through a tool i built, the full read: https://kasspian.com/marketing/share/d4923610-707e-45fd-993b-e18ce80130a8

The blunt bit is thatit led with; you have 70 real installs and zero of them CAN pay you, there's literally nothing to buy yet. the growth question and the monetization question are different problems and the second one is now the urgent one. it also mapped where your next users already complain about rate limits in public (r/ClaudeAI is louder than you'd think)

Really smart approach with the in-page bar over popup. I had the same realization building my API platform — context-aware UX wins every time. The MV3 Service Worker lifecycle is brutal; we ended up using chrome.storage.local with a write-then-read pattern to avoid race conditions. 70 users in 4 weeks with zero marketing is solid validation that the problem is real.

Chrome extension distribution is a different beast — no app store, no search traffic. 70 users in 4 weeks with zero marketing is the real signal. The install flow (manual ZIP, chrome://extensions) filters for high intent. That's the moat: users who jump through hoops actually use it.

The strongest part is that the product came directly from a recurring workflow failure you experienced yourself. The in-page token bar also seems like a strong UX decision—showing the information where the work is happening rather than hiding it behind another popup.