u/100TheCoolest17

Three months ago if you'd asked me where my SaaS customers came from I would have confidently said Twitter. I was active there, got good engagement, posts were landing. Felt obvious.

Turns out I was completely wrong.

The thing that bugged me was that my confidence was based on nothing. I was looking at two separate dashboards: traffic in my analytics tool, payments in Stripe. And then my brain was making up a story connecting them.

Every time a payment came through I'd glance at recent traffic and go oh this must be from that thread I posted yesterday. Zero actual evidence.

I finally decided to fix this. Tried GA4 first but setting up the Stripe side of things felt like a weekend project I didn't want. Then I found Faurya which basically does one thing: ties traffic sources to Stripe payments so you can see which channels made you money.

After running it for about a month the data was uncomfortable:

1. Twitter: biggest traffic source, almost zero paying customers
2. A tiny Facebook group I'd forgotten about: tiny traffic, disproportionate customers
3. One old blog post I wrote in 2024 and never promoted: steady conversions

The Facebook group thing was the weirdest. I'd shared my product once, months ago, and people kept coming back through that link slowly. Never would have known without the attribution.

Now I'm spending way more time in that community and way less time writing threads nobody pays for.

Anyone else had their intuition about their own product completely wrecked by actual data?

This happened to me again with the most basic question: “¿Qué hiciste ayer?” 

I understood every word. I knew the verbs. I could probably recognize the difference between pretérito and imperfecto in a grammar exercise. But out loud I went completely blank and produced something like “ehhh entonces… yo… tenía que pensar… no, tuve que pensar…” and then overused “entonces” five more times because my brain grabbed one connector and refused to let go.

The annoying thing is that I don’t think my main problem is vocabulary anymore. It’s retrieval under pressure. I can watch Spanish YouTube and understand a decent amount, Dreaming Spanish has helped my listening a lot, and Anki keeps words from disappearing. But where I live there are basically zero native Spanish speakers around, so I had built a routine with tons of input and almost no real answering.

Apparently this is common enough that people study foreign-language speaking anxiety. That made me feel slightly less ridiculous. It’s not always “you don’t know Spanish.” Sometimes it’s “you have never practiced being bad at Spanish in real time.”

What has helped me is separating the jobs of each tool instead of expecting one app to do everything. Anki is for recall. Dreaming Spanish/YouTube is for input. Pimsleur or shadowing is for making my mouth form sentences. Preply is useful when I can afford it and schedule it. For the speaking part, I’ve been using Issen some mornings because I can answer out loud without scheduling anyone or embarrassing myself in front of a real person.

I’m skeptical of “AI everything” stuff, especially when even Digg is apparently relaunching around AI news aggregation now. But for this one narrow use case, forcing myself to speak while walking around the kitchen making coffee has been more useful than adding another passive lesson.

 

The small hack that’s helping: I ask myself one boring daily question, answer for 60 seconds, then say the same answer again but cleaner. Not perfect, just less panicked. “Ayer fui al supermercado” becomes “Ayer fui al supermercado porque no tenía café.” Tiny upgrade. Repeat tomorrow. 

How are you all practicing actual speaking if you don’t have Spanish speakers nearby? Tutors, exchanges like HelloTalk/Tandem, ChatGPT voice, talking to yourself like a crazy person, something else?

Thanks i guess????

cant believe im playing the game

This came up while trying to make my morning coffee reading routine less chaotic. If you follow one fast-moving niche like AI product launches or US startup funding from outside the US, “news” is no longer just articles. It’s headlines, founder posts, demo videos, newsletter takes, Reddit threads, and then search to understand what actually changed. 

The tradeoffs seem pretty consistent. Feedly/RSS is best if you care about source control, but you still do the filtering. Google News/Apple News are convenient, but I find they repeat the same story a lot. Newsletters are usually higher-signal, but delayed and scattered. Perplexity/ChatGPT are good when you already have a question, not for passive monitoring. AI news assistants and Particle-style apps are interesting only if they dedupe well and still show sources. 

The rubric I’m using now is simple: source breadth, duplicate handling, timeline/context, follow-up Q&A, personalization narrower than “technology,” transparency back to original sources, and whether it fits a 10–15 minute habit. My practical test is to pick one story for 7 days and see if the tool catches the original announcement, at least 2 independent sources, and collapses 10 similar headlines into one useful update.

For a concrete case, think of a UK founder tracking US AI startups. I’d probably use RSS for must-read sources, 2–3 newsletters for analysis, and an AI layer for deduping/summaries/audio. If the update affects money, legal risk, or product roadmap, click through to the original source. If it’s just awareness, a summarized briefing is probably enough. 

Some useful comparison reading: Zapier’s roundup of news apps is decent for the mainstream options and Mission to Learn has a broader aggregator guide. I’ve also been testing CuriousCats.ai as one AI-news-assistant example because it combines summaries, timelines, video/audio, and follow-up Q&A in one place, but I’d still verify important claims through original sources. 

Curious what workflow people here actually trust. Do you use RSS, newsletters, AI summaries, Reddit/X, or some mix? And what failure mode do you watch for most: missing stories, duplicate noise, bias/filter bubbles, or wasting too much time?

Hey guys! I only noticed this after 100hrs of playthrough lol, not really a steam pro but I want the get the full deck, how else can i get the remaining cards??

Lately I keep getting pulled into technical screens because our engg manager is burned out from doing 6–7 interviews a week. 

What’s frustrating is how many candidates look great on paper and in conversation, then fall apart the moment they touch a real system.

Last month we tried replacing the usual HackerRank/Leetcode screen with a 30‑min debugging task on a small Node API. Bug was simple: auth failing because of a bad env variable and a dependency mismatch. 

We used a sandbox environment tool Utkrusht for this, but the tool honestly wasn’t the interesting part.

Out of 28 candidates, maybe 2 immediately checked logs and tried running the service locally. Almost nobody asked good clarifying questions. The rest just poked at code randomly. 

One guy with a very average resume fixed it in 12 minutes. Another very confident candidate never even opened the logs.

Made me realize how weak resume + interview signals can be for engg/dev candidates.

How do you recruiters here validate real hands‑on ability before sending candidates to the hiring manager? What has worked/hasn’t worked?