u/Jealous-Leek-5428

I make soy candles. Etsy shop, Shopify storefront, handful of wholesale accounts around town. About $4,800 a month on a good month.

Every Sunday I do the exact same thing. Export the Etsy CSV. Export the Shopify report. Manually mash them together in Google Sheets because the date formats never match. Update my inventory tracker so I know what scents to pour next week. Cross reference wholesale invoices. Then go into my website and update the bestsellers section by hand because I never learned how to make that part of Shopify do it automatically. Six hours every single week. I dread Sundays now.

Zapier lasted about three weeks. Built a flow to pull Etsy orders into Sheets, it silently stopped when Etsy changed something on their end, and I burned a full weekend trying to fix it before giving up. Then I paid a guy on Fiverr $200 for a Looker Studio dashboard that looked incredible in his demo and completely fell apart the second my real data had a slightly different column structure. Opened it twice.

Lately I've been throwing things at the wall with AI tools. ChatGPT is fine for product descriptions but it obviously can't touch my actual spreadsheets. I tossed my two CSVs into MuleRun and it spit out a page with charts showing what was selling by scent and by channel, which was honestly more useful to me than that $200 Fiverr dashboard. But the credits system took me a while to figure out, it only covered that one week's snapshot, and the whole thing still felt like a science experiment more than a routine I could count on. The reconciliation part where I decide which wholesale orders to count against which production batches still needs my brain. I don't trust anything to make those calls.

I keep going back to doing it all by hand. Every other Etsy candle seller I talk to does the same thing, week after week, and none of us can tell if we're doing something wrong or if this is just what running a small product business actually looks like at this revenue.

Months of work. Firefox with uBlock Origin, private DNS resolver, paid VPN, Google account removed from everything. I genuinely thought I was done.

Then I decided to actually verify instead of assuming. Found an open source fingerprint scanner called Leakish on GitHub, read through the source to make sure it wasn't doing anything shady, and ran it. My score came back in the low 30s out of 100.

First surprise: the VPN was handling my IP fine on the network egress check. But WebRTC was leaking my local network address through a STUN probe the entire time. My VPN provider plasters "military grade encryption" across their site but somehow can't be bothered to mention the most widely known VPN bypass in existence.

Canvas was the real problem. The way my browser renders a specific 2D element produces a hash that is basically unique to my machine. Couple that with an unusual set of installed fonts, and my browser was essentially wearing a nametag across every site I visited. No cookies, no Google account, nothing. Just render a hidden canvas, hash the output, done. You're tracked.

I verified in DevTools that the fingerprint checks (canvas, fonts, all of it) ran locally in my browser and the only actual server call was the egress IP probe. Small detail but it matters when you're trusting a tool with this kind of data about your setup.

Went down a rabbit hole after seeing the canvas result. Englehardt and Narayanan's 2016 Princeton study ("Online Tracking: A 1 Million Site Measurement and Analysis") found canvas fingerprinting scripts deployed on roughly 5% of the top 100,000 sites. That was nearly a decade ago, and the technique is more widespread now. Here's the part that makes me genuinely furious about the degoogling project: Google's ad network partners use these exact fingerprinting techniques. You can spend months ripping Google out of your life, and their ad ecosystem still follows you across the web with a canvas hash. The Google account was always just the convenient door. Fingerprinting was the fallback they never needed you to know about.

Enabled resistFingerprinting in about:config and rescanned. Jumped from the low 30s to the mid 70s. Not an absolute privacy grade by any stretch, just a relative comparison, but the shift was undeniable. The cost: timezone spoofing broke a banking login within minutes. Some pages started rendering wrong. I now keep a second Firefox profile without it for those specific sites. Functional, but absurd that this is where we are in 2026.

Mozilla knows Canvas is a problem. resistFingerprinting exists as proof. But they refuse to ship it as default because compatibility suffers, so every Firefox user stays fingerprintable out of the box. Google will never address it in Chromium because their ad infrastructure IS the fingerprinting infrastructure. The distance between "I degoogled" and "I'm actually harder to track" is wider than most of us realize.

Lately the long positions in the futures market have been piling up pretty hard. The whole market is going long. Open interest is climbing fast, funding rate has been staying positive, everyone's clearly feeling bullish.

This reminds me of Jan. Back then it was the same thing, longs were stacking up, funding was high, and then topped and dumped. But before the run started in Oct last year, longs were also loading up early and they ended up being right. So positions piling up doesn't always mean something bad, it depends on whether real spot buying shows up to back it up.

I checked on bydfi and BTC's funding rate has been running high lately, thats said longs are paying to hold their positions. If spot buyers come in and follow through, those positions become rocket fuel. But if spot doesn't show up and it's all just leverage holding things up, that kind of move always comes back down eventually.

Now it's basically a wait and see moment. Price is still chopping around in the range, hasn't actually broken out, but positions already jumped early. The key is whether spot comes in to confirm the direction, or the leverage unwinds on its own.

Anyone here running longs right now? I personally lowered my leverage for now, didn't close everything, just don't wanna be carrying too much risk when things are still unclear

Quick numbers first because i know thats what you all care about.

mrr: 4.2k (april), up from 2.9k in feb
churn: 4% monthly, holding steady
arpu: 89/mo
total customers: 47
i ship solo, no co founder, no contractor, this is full time for me

The thing that broke for me around 30 customers was follow ups. i was running 3 to 5 user calls a week, plus async support in 2 discord channels, plus a roadmap that lived half in linear and half in random apple notes. every time someone asked me "when is feature X shipping" i either had to scroll back through 200 messages or just guess. i guessed wrong twice and one of them churned. that one cost me 2.4k a year.

So i did the obvious thing first. tried to be more disciplined. wrote a template for every call. set up a weekly review block on calendar. lasted nine days, then i had a deploy emergency on a wednesday and the whole system died.

Second thing was tooling. i moved discord conversations into linear with a zapier trigger which was honestly a mess and i removed it after a month. tried granola for calls which actually does work but only solves about 30% of the problem because it doesnt know about my linear or my code. tried setting up a custom rag pipeline over my obsidian, which yes i actually built and yes it took a weekend and yes it was worse than just searching obsidian. at one point around 2am i was literally searching "best ai agent for solopreneurs" on twitter hoping someone had figured it out. spoiler, the threads were mostly people selling courses.

What helped, partially, was lowering the activation cost of remembering things. ive been trying airjelly in the background on my macbook for about 3 weeks. its not magic, the first week i thought i was going to uninstall it. but it pulls across the apps i already use including discord scrollback, so before a customer call i can just ask what they told me previously instead of scrolling. the part i actually open most is the People view, where each customer has their own running thread of asks and what ive promised them, which is the bookkeeping i kept dropping once i passed 30 customers. its on device which mattered because some of these conversations include customer code i wouldnt put through a saas backend.

Is this a productivity post or a marketing post? both i guess. the concrete change was: customer call prep got noticeably faster, somewhere between cutting it by half and cutting it to almost nothing depending on the customer. that time is what gives me the runway to ship features, which is what makes the mrr move. its not just one tool though, i also finally killed the zapier mess and that alone got me back like 3 hours a week.

Next month im targeting 5k mrr. realistic plan is to ship the team feature thats been in tech debt limbo since february. the call prep math now gives me the bandwidth to actually do it.

Will report back end of may.

Real talk. First 8 months of dropshipping i picked products the same way everyone does. Scroll tiktok, check aliexpress trending, see what other stores are pushing, go with my gut. Worked sometimes. Mostly it didnt.

The turning point was realizing i was always showing up late. By the time i spotted something trending on tiktok and got a store up, 50 other people had the same idea. Margins already compressed.

What i do now is different. Found a tool called MuleRun that lets you chain multiple agents together on a schedule. One grabs category data from various sources, another one scores it by competition density and growth rate. Runs every sunday night so by monday morning theres a report sitting there.

What the report actually shows me:

• Categories where search demand grew 20%+ over 30 days
• How many active sellers exist in each one and whether thats growing too
• Average price point and rough margin estimates
• A combined opportunity score

Obviously this doesnt replace actually validating a product. You still need good creatives, a working funnel, and reliable suppliers. But the "what should i even bother looking at" step went from random scrolling to something structured.

Last month it flagged a pet accessories sub-niche. Never would've looked at that category myself. Tested it with a small ad budget and its already my second best performer after 3 weeks.

The shift for me wasnt really about the tool specifically. It was about accepting that my gut wasn't a scalable research method and that i needed some kind of system, whatever it looks like.