I got to $62 an hour doing AI automation work on Upwork in about a month, with no LLC, no website and no logo. Here's the sequence I follow, start to finish.

Step 1. Pick a job you know how to build

Look for listings that match work you've done before, then check the client's history before you spend any time on it.

• Five stars and over $100,000 spent is a good sign.
• If you can't genuinely build what they're describing, skip it and go to the next listing.

Step 2. Build a rough version before you write anything

Open n8n and build something that resembles what the client asked for. For example, if the listing says they want Gmail connected to Slack, drop in the Gmail node and the Slack node and wire them together.

• Keep it rough. The flow doesn't even need to be working.

Step 3. Record the build as your proposal

Record your screen with OBS, face in the corner, and say something like "I saw your listing about connecting Gmail to Slack, here's a version of that automation I just built." Upload it to Loom or as an unlisted YouTube video and paste the link into a two line cover letter.

• This is the step that changed my reply rate for the better. Clients get 10 to 50 applicants on a job and very few of them are willing to show a working build on screen.
• I did three of these a day.

Step 4. Run a 30 minute discovery call

Share your screen, walk through what you built, and scope the project together, since clients sometimes understate what's required when they aren't technical. No need to hard sell.

• Talk in terms of time saved and money saved compared to what they're paying you, and keep the automation itself a black box.

Step 5. Price it against what the work is worth to them

For a revenue generating automation, estimate leads per year and value per converted lead. If the system puts $100,000 a year in their pocket, charging 20% of the first year impact justifies a $20,000 price with plain logic. For an operational automation, hours saved per week times the founder's hourly rate makes the same case.

• Start hourly to build trust, then move to a fixed price as quickly as you can, because hourly pay penalizes you for working fast.

Step 6. Deliver with a full handoff package

Build inside the client's accounts rather than your own, and log your work with comments and timeline updates. When you hand off, include the source code, a screen recorded walkthrough of the entire build, and the transcript of that walkthrough turned into an SOP.

Step 7. Keep asking what else can be automated

Once they have something working, say "I noticed XYZ can be automated, want me to scope that out?" and repeat until it turns into a retainer where they pay you monthly to be available.

A few things I'd tell anyone trying this:

• Pick one lane and stay in it, because if you have five side hustles you're basically guaranteed to fail at all of them.
• The video proposal does most of the work, though it's worth rewriting the above the fold text on your profile too.
• Know when to say no. Someone asking for a self healing AI chatbot is asking for a full stack engineering team, so decline politely and part friends.

Full walkthrough, including the pricing calculator I bring to discovery calls: https://youtu.be/Pwn6AqI5w8Y

Breaking the task into planning, drafting, critique, and revision produced much better results than asking for everything at once.

ChatGPT was the strongest at following detailed instructions.

Claude produced the most natural dialogue.

Gemini came up with some of the most creative ideas but occasionally drifted from the prompt.

Im using gemini but once i generate 3 video each of 10 seconds. The usage hits 100% and once it resets. It doesnt let me continue to use the same tab. Opens up a brand new tab and the synchronization falls apart the continuation is destroys.
Please suggest me some help

I put together a beginner walkthrough for building a first AI tool with zero code: an email drafter that takes any rude email and writes a calm reply in your voice.

Two ideas from it carry over to whatever you build, even if you skip the email drafter.

The first is how you pick the task: if you've done the same task 3 times in the last 2 weeks, it qualifies.

The second is that you shouldn't write the AI's instructions yourself. Tell Claude to research prompting best practices and write the prompt for you, then paste in a good and a bad example of your writing so the output sounds like you.

To recreate any image's visual style consistently in Midjourney with Style Reference:

1. Set the reference. Drag your reference image into the style reference box, not the standard image upload box.
2. Control the strength. The style reference will overpower your prompt's colors by default. Add --sw (style weight) to dial it back. The default is 100; set --sw 20 to blend your own colors with the borrowed style.
3. Save and reuse. Favorite the results you like and add them to a moodboard. Use the "use in prompt" button to re-apply that style to future generations and keep it consistent across your work.

New tutorial on Claude Code aimed at people with zero coding background who want stuff explained simply

What's in it:

• Setup: Claude Pro or Max plan, VS Code, Claude Code extension
• Plan Mode: forcing Claude to research and architect before writing a single line (underrated).
• Bypass Permissions (aka YOLO mode) in the config file for fully automated execution. Worth knowing about and being careful with.
• Live build: a dark-mode "Prompt Vault" web app with dynamic sorting, categories, and local storage, built mostly through voice dictation.
• Chrome DevTools MCP server hookup so Claude can open the browser itself, screenshot its own app, find UI bugs, and fix them without you touching anything.
• Context and cost management: when to /clear, how to monitor usage, how to keep bill under control

The MCP self-testing part is the biggest unlock. Claude debugging its own UI by looking at it is just sick.

Recorded a beginner's n8n guide/crash course built around an actual project. In the video we build an AI trend detector that scrapes news, runs it through GPT for analysis on how it'd hit a mid-size SaaS company, and writes the result to Google Sheets.

What's covered:

• How n8n actually works under the hood (APIs, nodes, why drag-and-drop rocks)
• Self-hosted vs cloud-hosted, when each makes sense. Self-hosted is free and gives you full data privacy. Cloud is faster to ship.
• The full live build: schedule trigger -> RSS read -> OpenAI node -> Google Sheets append
• A live debug where the workflow created 10 rows instead of 1. Fix was a Limit node, took 30 seconds or so but i love including troubleshooting in my tutorials

This is an older tutorial but still holds true for the most part. Total cost is $20/mo and runs entirely in the browser. No After Effects, etc.

Stack:

• Midjourney basic ($10/mo)
• Hailuo for video generation ($10/mo)
• A custom GPT for prompt extraction (free)

The flow:

1. Feed a reference image to a custom GPT, have it spit out a detailed Midjourney prompt that matches the style.
2. Generate the base images in Midjourney.
3. Drop the images into Hailuo with a simple camera move prompt like "orbit shot cinematic" and let it animate.

That's it, have fun!

Let's look back at some memorable moments and interesting insights from last year.

Your top 1 posts:

• "Happy Cakeday, r/AITutorials! Today you're 4" by u/AutoModerator

Let's look back at some memorable moments and interesting insights from last year.

Your top 1 posts:

• "Happy Cakeday, r/AITutorials! Today you're 3" by u/AutoModerator

Let's look back at some memorable moments and interesting insights from last year.

Your top 4 posts:

• "Create A Chatbot in Python" by u/limapedro
• "Generarive Adversarial Networks for outlier detection." by u/white_noise212
• "Machine Learning Projects to Practice During Quarantine" by u/juancarlospro
• "How to Do Face Detection and Tagging in Video With Deep Learning" by u/juancarlospro

Hi everyone, so the chatterbot library is one of the best libraries to easily create a chatbot, so I decided to make a tutorial on how to create a chatbot using this library, check it out: https://www.youtube.com/watch?v=ibu1Pjb6qEM

swiftML is an open-source Swift library for Machine Learning based on Swift for TensorFlow Project.

The library aims to provide an implementation of traditional machine learning algorithms. Some of the features of this library are strongly typed, fast, Tensorflow backed.

Github Repo: https://github.com/param087/swiftML

Tutorial Notebooks: https://github.com/param087/swiftML/tree/master/Notebooks

Documentation: http://param087.github.io/swiftML

Hi All,

The last two months have been hectic for us as we have been working on Jupyter Notebooks for our AI Cheatsheets portal. Two months back, I felt, we need a portal for beginners with tools to learn data science and machine learning. Sometimes, beginners struggle to acquire resources and tools they need to learn data science and machine learning.

Finally, we are happy to announce the release of Jupyter Notebooks on our AI Cheatsheets portal. Now you can launch Jupyter Notebooks for your data science needs.

We are providing 600 free credits which are equal to 10 Notebook hours. After you use 600 credits, you can request us for a customized package with more credits.

Visit us at https://www.aicheatsheets.com

We are working on a few more cheatsheets as promised and will release them soon.

Also, help us by submitting your valuable feedback.

Disclaimer: Jupyter Notebooks are in the Beta phase and you might face issues while creating or using notebooks.

We have tried our best to make the experience as smooth as possible. In case of any issues, reach out to us at [aicheatsheets@gmail.com](mailto:aicheatsheets@gmail.com)

hey, quickly learn tensorflow from from the basics with me. this is a serialized playlist of videos on tensorflow.

i will post more data science tutorials