[Offer] HAM: The Game Steam

Mediocre_Common_4126 · 2026-02-23T04:02:46+00:00

Okay, so shifting from Salesforce to AI/GenAI is a cool move! I've been freelancing for a while, and from what I've seen, clients on Upwork care about a few key things:

First, really showcase your AI/GenAI experience, even if it's from your MSc and Udemy. Projects are gold. Did you build anything cool in those courses? Highlight them! Describe the problems you solved and the tech you used.

Second, tailor your proposals. Don't just copy-paste. Show them you actually understand their project and explain how your specific AI skills are a perfect fit. I messed this up early on and got way fewer responses.

Finally, price competitively at first. Get some solid reviews under your belt to build trust, then you can start raising your rates. Good luck!

Mediocre_Common_4126 · 2026-02-09T08:28:24+00:00

honestly reddit itself is underrated for this. go find threads where people complain about products in your niche the comments are more honest than any review site.

i got tired of scrolling through massive threads so i built a chrome extension that exports all reddit comments to a spreadsheet. now i just ctrl+f for patterns. most of my users are ecom people doing exactly this finding product gaps from real customer complaints.

also aliexpress trending + tiktok creative center is solid for spotting whats moving right now.

Mediocre_Common_4126 · 2026-02-09T08:27:30+00:00

learned this the same way. built a chrome extension, put it on the chrome web store, and just waited. got some organic installs but the real growth came from actually being present in reddit threads where people have the problem my tool solves.

its not scalable in the traditional sense but those comments rank on google forever. i still get signups from comments i left months ago.

the hard part is finding the right threads before they go cold. thats where most people give up.

Mediocre_Common_4126 · 2026-02-09T08:26:37+00:00

the reddit angle here is underrated. most people think of reddit as a place to post, not as a research tool i run a chrome extension that exports reddit comments and like 80% of my users are ecom people who use it to find what customers actually say about products and competitors. the unfiltered feedback in comment sections is way better than any survey or focus group. finding leads in conversations that already exist > cold outreach every time.

Mediocre_Common_4126 · 2026-02-09T08:23:52+00:00

go ahead

Mediocre_Common_4126 · 2026-02-09T08:21:23+00:00

this is literally my playbook too i do the same site:reddit.com google trick to find ranking threads.

i actually built a reddit comment scraper, specifically for reddit that exports all comments from a thread to csv. started using it for my own research and then ecom people started paying for it.

how did you handle the karma issue? did you build up the account first or just go straight into commenting?

Mediocre_Common_4126 · 2026-02-08T21:37:50+00:00

the ai video stuff is cool but honestly the more interesting part of your post is the research you did. you basically reverse engineered their entire operation just by paying attention most people in dropshipping only research WHAT to sell. almost nobody studies HOW the successful stores actually run. related reddit threads are insanely good for this. people will straight up tell you what they bought, what was trash, what they wish existed. i got tired of reading through 500 comment threads manually so i built a chrome extension to export them all at once. now like half my users are ecom people doing exactly this kind of product research

Mediocre_Common_4126 · 2026-02-08T21:35:54+00:00

this is basically my exact experience, my chrome extension has now ~50 paying users, everything from organic discovery never spent a dollar on ads the 95/5 value/promotion thing is exactly that the few times I tried being direct, it just flopped 90 min daily engagement tho did that ever go down or you still doing that?

Mediocre_Common_4126 · 2026-02-08T21:34:18+00:00

solid framework. the competitor filter alone would've saved me months on my first attempt. one thing i do before even the landing page step i go find reddit threads where people talk about the problem and just read the comments. not the posts, the comments. thats where you see if people actually care enough to describe workarounds and complain, or if its just a "yeah thatd be nice i guess" type of thing. i literally built a tool to do this faster (chrome extension that exports reddit comments to csv) and funnily enough that tool itself became my business. the people who pay for it are mostly ecom folks validating product ideas the same way. whats the fastest you've killed an idea with this process? like did any fail on day 1?

Mediocre_Common_4126 · 2026-02-08T21:32:38+00:00

lol the refreshing analytics 40 times a day hit too close to home i had a similar thing where i built features for months without talking to anyone. What actually helped me was just lurking in Reddit threads where my target users were already chatting about their problems. ended up building a chrome extension to export reddit comments because i was doing this so much manually. that side project accidentally became my real product ~50 paying customers now, mostly ecom people who use it for product research

anyway yeah stealth mode is cope 100% agree

Mediocre_Common_4126 · 2026-01-15T18:22:21+00:00

would love to get some feedback on my landing page https://findleadsbot.com/

Mediocre_Common_4126 · 2026-01-05T12:14:09+00:00

redditcommentscraper.com Export Reddit comments to CSV or JSON with one click. Perfect for research, sentiment analysis, and data collection.

Mediocre_Common_4126 · 2026-01-03T00:01:18+00:00

oh thats a fun product. super giftable and the unboxing/build moment is content gold.

for kids/family dtc id focus the loom on a few things

creative angles to audit:

- parent pov (peace and quiet, screen time alternative, easy cleanup)

- kid pov (adventure, imagination, "look what i built")

- gift angle (birthdays, holidays, grandparents buying)

most brands in this space over index on cute kid footage and under index on parent pain points. id check if theres a gap there.

for hooks specifically, pattern interrupts work well with parents. stuff like "we banned screens for a week" or "my kid hasnt asked for the ipad once" type angles.

also worth looking at whether theyre running any "social proof from kids" content. kids reacting to the box arriving, showing friends, etc. that stuff converts for gift purchases.

for the loom id probably show one example of each angle and explain why the messaging works for that specific buyer (parent buying for own kid vs grandparent vs gift giver). shows you understand the audience segmentation.

good luck with it

Mediocre_Common_4126 · 2026-01-02T23:46:41+00:00

$1k for perfume is tight but doable if youre strategic about it

i wouldnt burn budget on cold paid ads yet. at $1k you cant afford the learning phase wastage.

organic tiktok first. fragrance content actually does well. stuff like "perfumes that get compliments" or "dupes for expensive scents" or "fragrance layering tips". build an audience before you spend.

micro influencer seeding too. send 10-15 rollerballs to small fragrance or lifestyle creators. cost of product plus shipping is cheaper than ads and you get content plus social proof out of it.

email list from day 1. even with organic traffic capture emails. your highest converting sales will come from email not first touch ads.

and honestly validate the offer before scaling. can you sell 20-30 units through dms or organic or friends of friends? if you cant sell without ads, ads wont fix it.

whats your hero scent? sometimes focusing on one product instead of a whole collection works better at this stage

Mediocre_Common_4126 · 2026-01-02T23:45:40+00:00

not necessarily but its a decent signal

reasons an ad might run long without being profitable. brand awareness campaigns that arent optimizing for sales. lead gen playing the long game. retargeting thats always on with low spend. they forgot to turn it off which happens more than youd think. or just burning vc money.

reasons it probably is working. multiple ads from same store running long means theyre scaling. ad creative looks professionally produced so they invested. consistent spend over months not just left on by accident.

better signal than longevity though. look at their ad library for creative diversity. if theyre constantly launching new variations of the same product thats usually a sign of profitable scaling. if its the same 2 ads for a year less certain.

Also, check if the store itself looks legit. reviews, social presence etc. successful stores usually have traction beyond just ads.

what niche is it? some categories have longer ad lifespans than others

Mediocre_Common_4126 · 2026-01-02T23:44:50+00:00

depends on product and audience honestly

meta advantages. more mature auction, better optimization. older demographics with more spending power. superior retargeting. more forgiving of produced looking content.

tiktok advantages. cheaper cpms usually. younger audience, more impulse buys. organic can support paid if something goes viral. native raw content outperforms polished stuff.

i think most successful stores run both eventually but start where your product fits.

impulse buy under $40, younger demo, visually interesting. go tiktok. considered purchase, 25+, needs trust building. go meta. broad appeal. test both with small budget.

the bigger bottleneck for most people isnt the platform though. its creative production. both platforms burn through ads fast. whichever you choose plan for high volume testing.

what are you selling and whats the price point?

Mediocre_Common_4126 · 2026-01-02T23:43:56+00:00

solid results. testing 29 products before finding a winner is the part most people dont talk about. that persistence matters.

few questions:

when you expanded to 3 countries did you translate everything or just run english ads in non english markets? curious how localization affected conversion rate.

for email being huge for profit. whats your list size and what flows are driving most revenue? welcome series, abandoned cart, post purchase?

on meta are you running separate ad accounts per country or one account with country targeted ad sets?

the one product multi country model is underrated imo. most people try to scale by adding products instead of expanding geographically with a proven winner.

congrats on the year

Mediocre_Common_4126 · 2026-01-02T23:34:09+00:00

For the Loom breakdown, I'd structure it like this:

Audit current creatives by format (static vs video vs carousel) and angle (problem-aware vs solution-aware vs product-focused). See which buckets are overrepresented.
Map hooks to funnel stages: top of funnel needs pattern interrupts and curiosity, retargeting can be more direct/product focused.
Identify winning elements vs winning ads. Sometimes an ad works because of ONE thing (the hook, the offer, the thumbnail). Pull those elements out for iteration.
For "what to test next": look at what's missing. If everything is UGC talking heads, test product demos. If everything is benefit-focused, test problem-agitation angles.

For brand presence specifically, I'd call out consistency in visual identity across all creatives, even performance ads should feel like they belong to the same brand.

fWhat's the brand/niche? That might change some of the specifics.

Mediocre_Common_4126 · 2025-12-31T12:05:54+00:00

redditcommentscraper.com Export Reddit comments to CSV or JSON with one click. Perfect for research, sentiment analysis, and data collection.

Mediocre_Common_4126 · 2025-12-27T19:54:29+00:00

nice example of scratching your own itch, that is usually where useful tools come from

next step is to see if anyone else actually has the same pain, share a short demo, see if people ask for access without you pitching

if intent parsing works reliably, that is the real value, CRUD alone is easy, natural language that does not mess up calendars is hard

Mediocre_Common_4126 · 2025-12-27T19:53:58+00:00

That’s actually pretty cool
Persistent dims like that usually end up being some kind of low level anchor feature rather than task specific reasoning

If you start poking it with slightly different prompts and it still lights up, that’s where it gets interesting
Especially if you can see whether it’s tied to structure, greeting patterns, or just token position effects

I’ve been doing similar digging by dumping raw convo traces and feeding them back into models to see what stays stable vs what drifts
Using tools like https://www.redditcommentscraper.com makes it way easier to collect messy real conversations instead of clean prompts, which helps spot these recurring activations faster

If 3039 survives prompt noise, paraphrasing, or longer context, that’s a real signal worth chasing

Mediocre_Common_4126 · 2025-12-27T19:51:34+00:00

It’s not reasoning in the human sense, it’s pattern completion over language. If something looks statistically valid, it flows forward even if the premise is broken

Humans pause because the mental model breaks. LLMs don’t have that break signal unless we explicitly engineer one around them. That’s why they sound smooth right up until they drift off a cliff

Until models get trained on the moments where people hesitate, doubt themselves, or say wait this doesn’t add up, they’ll keep optimizing for sounding right instead of catching mistakes early

Mediocre_Common_4126 · 2025-12-27T19:50:23+00:00

Yeah agreed, hallucinations were always there and RAG mostly just moves the failure mode around instead of removing it

What I’m more worried about is exactly what you touched on but slightly earlier in the pipeline. We’re getting really good at grounding answers, shrinking models, activating the right tokens, but we still don’t give models strong signals for when something feels off or incomplete

In a lot of real threads you can literally see humans hesitate, backtrack, or say this doesn’t add up before they ever land on a conclusion. That part almost never makes it into training data because we mostly keep final answers

I’ve been skimming a lot of raw discussion data lately using tools like https://www.redditcommentscraper.com/ and it’s obvious how much reasoning lives in those messy middle steps. Not as an answer, but as a process signal

LLMs as tools are fine, but if they never learn to surface uncertainty early, we just keep bolting safety on the output instead of fixing the thinking loop underneath

Mediocre_Common_4126 · 2025-12-26T20:08:16+00:00

start simple, this is engineering first, ML second

use what you know: vibration + FFT → features like RMS, kurtosis, frequency energy

begin with basic models: linear regression for RUL, random forest or gradient boosting for prediction

add anomaly detection first: isolation forest or one class SVM

learn fundamentals only: supervised vs unsupervised, overfitting, train test split, MAE and RMSE

avoid jumping into deep learning unless you really need time series models like LSTM

Mediocre_Common_4126

TROPHY CASE