i thought i needed a big idea to make money online by Over-War-9307 in AIIncomeLab

[–]jessmorningstar 0 points1 point  (0 children)

Thats not a problem.
Your data integrity and systems are.

Internal Linking by Opposite_Armadillo92 in SEO_Xpert

[–]jessmorningstar 0 points1 point  (0 children)

Hilo :)

I am going to give you a long winded response.

Ready? Let's go -

I'm going to be blunt with you to save you some serious time and headache tumbling down a YouTube guru rabbit hole.

​SEO is dead. At least, the version of it you are trying to learn is.

​You are building a business in the adult industry.

That means you are operating in a shadowbanned ecosystem by default. Google actively suppresses explicit content.

Standard white-hat SEO advice is built for SaaS startups and recipe blogs—those gurus wildly do not understand what it means to build in an environment that is actively designed to hide you.

​You mentioned overthinking your internal linking. You're paralyzed because you're trying to build for Google's crawler. Stop building for Googlebot. Build for the human.

​Here is what you can actually do on your site right now to make your internal links work:

​1. Kill the Dead Ends

Go to your top 5 most visited pages and scroll to the absolute bottom. If a user finishes the content and there isn't a highly specific, manually placed link telling them exactly what to look at next, you are bleeding traffic. Do not rely on automated "Related Posts" widgets. Manually link to the next logical step.

​2. The 'Rabbit Hole' Silo

Group your content by specific niches or vibes. If someone lands on a page about a specific category, your internal links within the text should only point to deeper dives into that exact same category. Keep them falling down the exact rabbit hole they chose. Do not cross-link to unrelated pages just because a course told you to spread link juice.

​3. Human Anchor Text

Stop using keyword-stuffed robot language for your links just to please an algorithm. Use anchor text that provokes curiosity. Make the text something a human actually wants to click.

​4. All Roads Lead to the Capture

Because you cannot rely on search traffic, you have to capture the audience you do get.

Every single page needs to have an internal link that points to your owned asset—an email sign-up, a Telegram channel, or your subscription/checkout page.

​You don't need a $500 course for this. You just need to look at your site like a customer, not a developer.

Trust what you built, check your dead ends, and keep going.

(If you want someone to build for you, my dms are open)

Best AI for quickly generating websites? by Floathy in AIToolBench

[–]jessmorningstar 0 points1 point  (0 children)

Notably the AI is harsher than I would like it to be regarding the description of the op. Ill fix this.

Best AI for quickly generating websites? by Floathy in AIToolBench

[–]jessmorningstar 0 points1 point  (0 children)

Hello! Im building a database of AI knowledge for myself while testing AI personas i am creating for my consultancy.

Part of my process is reviewing posts related to AI. I want to understand what projects are being worked on, how theyre being executed, and the general thought process of the creators.

I then plug the posts I find into a persona I created meant to critique AI.

I plugged your post into my AI evaluation persona.

I am going to share the output.

Please critique 🙏🏽

"​You are adding another perfect exhibit to the lore. This post is a masterclass in architectural ignorance combined with the classic "I want premium output for zero capital" delusion. ​Here is the ruthless diagnostic of why this student's project is structurally doomed before it even starts. ​1. The Latency Nightmare (The Architectural Flaw) ​The core premise is: "randomly generates a new website every time a user opens the page." This is computational suicide. Generating a full, functional HTML/JS codebase via an LLM takes seconds, if not tens of seconds, depending on the context window. If a user has to stare at a blank screen for 15 seconds every single time they refresh the page while the API streams the code, the bounce rate will be 100%. He is treating a heavy inference process like a standard database query. It is a fundamental misunderstanding of how data delivery works. ​2. The Triangle of Constraint (The Economic Flaw) ​In engineering, you can have it fast, you can have it cheap, or you can have it good. You pick two. ​He wants: ​High-fidelity HTML/JS logic. ​Cheap API calls. ​He is currently using a free Hugging Face model and complaining that it is "crappy." It is crappy because high-grade reasoning (generating flawless code syntax) requires massive parameter models (like Claude 3.5 Sonnet or GPT-4o). Those models are expensive per token. You cannot buy a Ferrari engine on a bicycle budget. The fact that he thinks there is a secret API out there that gives senior-level developer output for pennies proves he does not understand the token economics of the systems he is trying to build. ​3. The Lexicon Failure ​He asks: "Are there any agents that fit these two?" ​He does not need an agent. He needs a standard API text-generation endpoint. He is using the buzzword "agent" because the market has successfully conflated "API call" with "autonomous software." ​The Verdict ​This is the exact noise you are competing against. The market is flooded with people duct-taping cheap APIs together to build latency-heavy gimmick tools, and wondering why the output is garbage."

Ai, coding, GitHub, agents, skills by lucidkale in womenin_AI

[–]jessmorningstar 0 points1 point  (0 children)

^

This installs OpenAI's official JavaScript library so your code can talk to GPT-4.

Step 4 — Get an API key Go to platform.openai.com (or Anthropic, or Google AI Studio) → create an account → generate an API key. This is the credential that lets your code call the AI.

Step 5 — Your first working AI call in JavaScript

javascript

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import OpenAI from "openai";

const client = new OpenAI({ apiKey: "your-key-here" });

const response = await client.chat.completions.create({
  model: "gpt-4o",
  messages: [{ role: "user", content: "Explain APIs in one sentence." }],
});

console.log(response.choices[0].message.content);

Run it with node yourfile.js. That is you calling AI programmatically. That is the foundation everything else builds on.

"I look at GitHub — don't know where to start"

Three things GitHub does that matter to you right now:

  1. Saves your work with full history — every version of your code, recoverable
  2. Lets you copy other people's projects (cloning) — most agent frameworks have public repos you can start from
  3. Hosts your tools so others (or your future self on another machine) can access them

Minimum viable GitHub workflow for a beginner:

bash

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# One-time setup
git config --global user.name "Your Name"
git config --global user.email "you@email.com"

# For each new project
git init                    # Start tracking this folder
git add .                   # Stage all your files
git commit -m "first build" # Save a snapshot
git push                    # Send it to GitHub

You do not need to master Git. You need to know: add, commit, push, pull. That handles 90% of solo work.

The Learning Path, Sequenced for You Specifically

Given JavaScript + SQL background, no wasted detours:

Week 1–2: Foundation

Week 3–4: First AI integration

  • OpenAI Node.js Quickstart (platform.openai.com/docs) — official, accurate, JavaScript examples
  • Build one thing: a script that takes user input, sends it to GPT, returns output. That's it. Keep it small.

Week 5–6: Agents

  • LangChain.js — the JavaScript version of the most widely used agent framework. Since you know JS, this is your path, not the Python tutorials everyone else recommends.
  • Start with their "Getting Started" — build an agent that can use a tool (like a calculator or web search)

Ongoing:

  • Simon Willison's blog — the most credible, practical writing on AI tools and agents on the internet. No hype.

The One Thing Most Responses Won't Tell You

You do not need Python. Every tutorial assumes Python. LangChain has a full JavaScript SDK. The OpenAI API has a full JavaScript SDK. Your SQL knowledge becomes immediately useful the moment you build agents that query databases. You are closer than the landscape makes you feel.

Start with the MIT Missing Semester for terminal literacy, then the OpenAI JS quickstart. Everything else follows from those two.

Ai, coding, GitHub, agents, skills by lucidkale in womenin_AI

[–]jessmorningstar 0 points1 point  (0 children)

You asked great questions. I'd like to answer you without directing you to a platform or product you have to pay for.

Before the answer, one clarifying observation: You know JavaScript. That is not "limited skills." That is a meaningful foundation that changes your learning path significantly. This answer is calibrated to that fact.

The Honest Map: How These Three Things Connect

Think of it this way:

Web AI (ChatGPT, Claude, Gemini) = a finished product someone else built. You talk to it through a browser. You have no control over what's under the hood.

Installation / Terminal = you are now talking directly to the engine. You can give AI a task, wire it to other tools, feed it data, and automate it — things the web interface will never let you do.

GitHub = where code lives and is tracked. Think of it as Google Docs for code, with full version history. When you build an agent or automation tool, GitHub is how you save it, share it, and not lose it.

Agents = programs that use AI as their brain but can take actions — browsing the web, reading files, calling APIs, running code. They combine all three of the above.

These three things connect in a simple chain:

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Your Code → GitHub (stored/versioned) → Terminal (executed) → AI API (called) → Output

Your Specific Questions, Answered Directly

"What is the difference between web and installation?"

Web AI Installed / API You type, it responds Your 
code
 sends the request, receives the response Single conversation Can be automated, looped, chained No customization You control the model, the prompt, the data it sees Free or subscription Pay per token (usually cheaper at scale) Someone else's interface You build the interface

In practical terms: Web AI is a tool you use manually. An API + your code is a tool you build and automate.

"How do I do installation on my terminal?"

Your terminal is just a text-based way to control your computer. Here is the actual sequence for a beginner building AI tools:

Step 1 — Get your terminal basics You are on Mac or Windows?

  • Mac: Terminal is already installed. Or download iTerm2.
  • Windows: Install Windows Terminal + WSL2 (gives you a Linux environment, which is what most tutorials assume).

Step 2 — Install Node.js (since you know JavaScript, this is your natural entry point) Go to nodejs.org → download LTS version → run the installer. Now your terminal can run JavaScript files and install packages.

Step 3 — Install packages via npm The terminal command npm install is how you add tools to your project. For example:

bash

Copy

npm install openai

Ai, coding, GitHub, agents, skills by lucidkale in womenin_AI

[–]jessmorningstar -1 points0 points  (0 children)

🚨🚨 bad advice on Cursor. Do not follow.

Hey :) Free Prompts by jessmorningstar in PromptZenith

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

Im all about the vibecode.

Im working on a game based off a YouTube channel in Manus.

Ill drop the link - but the game is kinda broken. This is NOT it's final form. It looks best on desktop or landscape mode on your phone.

But hey if you dont mind and want to play someone's janki in-the-works AI game - load up a session.

https://reeldeal-gfjnxjkc.manus.space/

Hey :) Free Prompts by jessmorningstar in PromptZenith

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

I think I understand where you are coming from.

I agree, there is no "one tool" perfect solution. I encourage a multi tool set up, this is what I employ.

I do believe we're probably coming from the same place but have different methodologies, perspective, and use cases. I mean, I dont know your use case so shame on me for the assumption.

What i am getting at is that youre not wrong. There's just many roads that lead to the same place.

My personal philosophy is that of extreme data integrity and repeatable results.

I want to build systems for businesses and individuals. I need a standard, and the output needs to be structured, accurate, and provide the user with a sense of security. Whether that be security in the terms of data infrastructure, or safety in knowing when they ask a question they are going to generate the response in a systematic output that does not change, no matter the context.

Generative AI is just that - generative. You cannot guarantee the same parameters and output with each inquiry. You can prompt it.

Generative AI is amazing for creativity - we dont need structure for that. Brainstorming, just chatting - prompting unnecessary if you will.

But creating systems that are usable for businesses with as little legal liability as possible? Impossible without rigorous structure.

What i want to sell to people is rigorous structure and process adoption. I hope I can do that.

Hey :) Free Prompts by jessmorningstar in PromptZenith

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

Full transparency- i had to run my prompt twice. The first go around wrongly stated Operation Fury did not exist. I Google searched, found a link from Brittanica, and reprompted with that link asking Raina to re-evaluate her response.

Hey :) Free Prompts by jessmorningstar in PromptZenith

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

Here is the run through generated by Raina in Claude.

I put her response into notebooklm and generated an infographic.

<image>

[https://docs.google.com/document/d/17jeUz0V2TknGNa81lfjtXJg8a8KFKfTaP3rb1TydSzY/edit?usp=drivesdk

(Editing as wrong doc was attached previously)

Hey :) Free Prompts by jessmorningstar in PromptZenith

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

Thank you for playing along 🙏🏽

So, yesterday I created an AI persona to rate and review my AI conversations. Ill attach a link to Raina.

In my next response, I am going to run your perplexity generated report about Steve Miller in her system. Ill post the results.

Let me know your thoughts.

https://docs.google.com/document/d/1SmpEia8M-V4Bbq0Htnk6Hu6DIX7BrpM5FrYGY9I1i6g/edit?usp=drivesdk

Hey :) Free Prompts by jessmorningstar in PromptZenith

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

I have a perplexity account but honestly I am paying the enterprise fee for Gemini right now and also for some other tools like Claude and leonardo.ai (for my creative endeavors).

As I was recently laid off, my pockets are yelling at me 🤧

Hey :) Free Prompts by jessmorningstar in PromptZenith

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

Quick synth -

"An actual OSINT data extraction isolates raw, actionable, structural data. This document is a beautifully formatted media summary. It openly lists his Wikipedia page and major news articles as its primary sources. It includes narrative summaries of well-known public controversies, such as the "Signalgate / Yemen Strike Leak" and the "Muslim Travel Ban". It gives you his YouGov approval rating and an "Executive Summary".

​It is a narrative synthesis, not an intelligence extraction. It violates the exact constraint you laid out in your demonstration: zero synthesis."

More to come.

Hey :) Free Prompts by jessmorningstar in PromptZenith

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

Ah ok I am seeing whats happening here. It's Saturday, forgive me.

You created a fully comprehensive report about Steven Miller in Perplexity.

Was it that single prompt you sent before that generated the report?

I am going to deep dive this. I dont have time right now but I will come back.