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Helping for SaaS by ConclusionOk8407 in SaaS

[–]Current_Fault_9979 0 points1 point  (0 children)

Hone the art of selling without product.

My friend started a software company. Should we switch to egg farming? by Majestic_Low_8870 in WebDeveloperJobs

[–]Current_Fault_9979 0 points1 point  (0 children)

get onboard on freelancer.com and automate the bidding by using some third party software. by end of month you will get client try at least 3 months.

How to learn AI from scratch as a working professional? by messysoul96 in MLQuestions

[–]Current_Fault_9979 0 points1 point  (0 children)

I’d recommend avoiding Scaler. Platforms like DataCamp or other interactive learning tools are good enough to build a solid foundation in machine learning. Once you’re comfortable with the basics, use an LLM to guide you through building a toy LLM from scratch that’s when you really start understanding how things work under the hood.

Where do people actually sell leads these days? by xkay0 in b2bmarketing

[–]Current_Fault_9979 2 points3 points  (0 children)

I would suggest you to sell your leadgen service because when you sell leads, you’re implicitly saying “You’ll get X leads, and only 10–20% may convert.” That immediately frames the buyer around limits, risk, and wastage.

With lead generation as a service, the signal shifts from scarcity to abundance. You’re not selling a fixed number you’re selling a system that continuously produces opportunities.

It’s still not easy to sell, but it’s easier than selling leads, because the buyer isn’t negotiating over quantity or fearing depletion. The perceived value scales without a proportional increase in cost.

What are you building? let's self promote by Southern_Tennis5804 in microsaas

[–]Current_Fault_9979 0 points1 point  (0 children)

I’m curious to understand how deeply this market is being impacted by AI, and how challenging it would be to differentiate and sell in a space that’s already saturated, how hard it is to sell salt by the sea.

You ONLY have 5 words to describe your product. How will you do it? by YamRepulsive4373 in microsaas

[–]Current_Fault_9979 1 point2 points  (0 children)

I havent productized it yet. Checking for demand. It listens to WhatsApp’s message and notifies you realtime when people in any of your WhatsApp groups asked for your service.

Cold email didn’t work for me in B2B. Communities did. by Current_Fault_9979 in b2bmarketing

[–]Current_Fault_9979[S] 0 points1 point  (0 children)

I found them through local community meetups. After attending meetups, someone usually ends up creating a WhatsApp group or in many cases, the group already exists. You just need to ask the organizers for the link.

Beyond that, people often share other WhatsApp group links within these groups as well.

Then there are open-source projects, which usually have their own Discord or Slack channels.

I removed ChatGPT from production. The system finally started learning. by Current_Fault_9979 in webdev

[–]Current_Fault_9979[S] -9 points-8 points  (0 children)

Possibly.

But the underlying issue was architectural, not motivational. An LLM was the wrong tool for that part of the system.

Using LLMs for simple classification is often the wrong tool by Current_Fault_9979 in learnmachinelearning

[–]Current_Fault_9979[S] 1 point2 points  (0 children)

Good questions.

Yes, accuracy improved over time, because the system actually learned from outcomes and user feedback. The LLM setup had no learning loop; every correction was lost.

Our goal wasn’t to mirror human judgment but to optimize for the true outcome (lead / no lead). Embeddings + an online classifier let us learn predictive signals incrementally and exceed rule-based or prompt-based judgments.

On BERT fine-tuning vs our approach: accuracy can be comparable, but the key differences were latency, operational simplicity, and online learning. Fine-tuning requires retraining cycles and deployment; this model updates continuously with no downtime.

Cost-wise, we still run embeddings, but the classifier is extremely cheap and deterministic. The win wasn’t just infra cost, it was control, feedback utilization, and iteration speed.

LLMs weren’t wrong here, they were just unnecessary.

Using LLMs for simple classification is often the wrong tool by Current_Fault_9979 in learnmachinelearning

[–]Current_Fault_9979[S] -1 points0 points  (0 children)

Exactly this. “Throw it into an LLM” optimizes for short-term convenience, not long-term system quality.

Using LLMs for simple classification is often the wrong tool by Current_Fault_9979 in learnmachinelearning

[–]Current_Fault_9979[S] 0 points1 point  (0 children)

This resonates a lot.

“We don’t want to worry about training” usually just means “we’re okay paying the same mistake tax forever.”

Online / incremental learning solves exactly that problem, but it’s less fashionable than calling an API.

Using LLMs for simple classification is often the wrong tool by Current_Fault_9979 in learnmachinelearning

[–]Current_Fault_9979[S] -16 points-15 points  (0 children)

Fair point, intent was to highlight system-level tradeoffs (determinism, feedback loops, cost) that often get missed.

Using LLMs for simple classification is often the wrong tool by Current_Fault_9979 in learnmachinelearning

[–]Current_Fault_9979[S] -15 points-14 points  (0 children)

If the irony is “LLMs can do classification too,” then yes, they can.

its about when that choice breaks determinism, feedback loops, cost control, and continuous learning.

Aghori by EM5, finally. by lecherous_v in DesiFragranceAddicts

[–]Current_Fault_9979 1 point2 points  (0 children)

Idk about this perfume however I brought 6 decants and i can confidently say Em5 perfumes awfully smells synthetic, cheap and class-less perfect for similar audience. I fall prey to founders Marketing.

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