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I stopped doing my weekly competitor research manually. I gave Qoder one recurring task: → Track Cursor, Windsurf & GitHub Copilot → Check official updates, X, Reddit & Product Hunt → Find the week’s important releases, news & partnerships → Turn it all into a structured report and save... show more

Kalsoom (ghotai )

51,049 subscribers

118,728 Aufrufe • vor 10 Tagen •via X (Twitter)

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18 Kommentare

Profilbild von Kalsoom (ghotai )

Kalsoom (ghotai )vor 10 Tagen

Try Qoder free with 600 Credits 👇 300 from the Pro trial + 300 with my code 9797YB.

Profilbild von Patrick's AIBuzzNews

Patrick's AIBuzzNewsvor 10 Tagen

That's the smarter and more efficent way.

Profilbild von Shah

Shahvor 10 Tagen

This a really smart setup

Profilbild von Fakhr

Fakhrvor 10 Tagen

600 credits plus Qwen 3.8 Flash at 0.0x Credits makes this worth testing.

Profilbild von NOVA

NOVAvor 10 Tagen

This is the kind of repetitive research task AI should take off your plate

Profilbild von AIMATRIX

AIMATRIXvor 10 Tagen

The research → analysis → report workflow is the part that really caught my attention. Huge time saver.

Profilbild von Hussain Hashim | Building SundayBack

Hussain Hashim | Building SundayBackvor 10 Tagen

@AIwithGhotai nice! Make sure to set an alert for industry events too. Sometimes that's where the big news drops.

Profilbild von Jimmy

Jimmyvor 10 Tagen

Research → analysis → report, all handled by one workflow. That’s the goal

Profilbild von Abdul Sarfraj

Abdul Sarfrajvor 10 Tagen

This is a great example of using AI for actual workflow automation, not just content generation

Profilbild von Ujala Pandey

Ujala Pandeyvor 10 Tagen

The structured report at the end is what makes this workflow really practical

Profilbild von David Marco

David Marcovor 10 Tagen

The combination of X, Reddit, Product Hunt, and official sources makes this much more useful than basic web search

Profilbild von Vikas gupta

Vikas guptavor 10 Tagen

The weekly competitor research alone can eat up so much time. Automating the whole loop makes a lot of sense

Profilbild von Sachin Malik

Sachin Malikvor 10 Tagen

Competitor monitoring is perfect for this kind of recurring AI workflow

Profilbild von Rohit

Rohitvor 10 Tagen

Recurring research tasks are one of the most underrated AI automation use cases

Profilbild von Rachel Woods

Rachel Woodsvor 10 Tagen

I like that this goes beyond just collecting links. It researches, analyzes, and turns everything into a report

Profilbild von EDDY VU

EDDY VUvor 10 Tagen

Tracking Reddit and X usually pulls in tons of noise, how clean is the signal you get back?

Profilbild von Lily

Lilyvor 10 Tagen

The “set it once” part is exactly what makes workflows like this valuable

Profilbild von JOYA

JOYAvor 10 Tagen

Tracking official updates + X + Reddit + Product Hunt in one workflow is seriously useful

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30,072 Aufrufe • vor 1 Monat

I'm excited to introduce my FREE AI Pandas Data Analyst Copilot which created a data analysis report with dozens of charts from my questions in under 30 seconds. Today, I'll share with you how to automate data analysis with my Pandas AI Agent + Copilot, which is available on GitHub. I'll guide you through setting up the Copilot app, creating dozens of data analysis charts from any CSV or Excel file, and interacting with your data live. This AI is a BIG help! Table of Contents: 00:00 Introduction to the App 02:24 Setting Up the App 04:25 Using the App 08:58 Understanding the Python Code Github to AI Data Science Team (app is in the apps folder): Get the Code and Future Updates by Joining my Python AI/ML Tips Newsletter: === Want to learn how to build AI projects companies actually want? (live Python Code) On Wednesday, April 9th, I'm sharing one of my best AI Projects: Time Series Forecasting with AI Register here (500 Seats):

I'm excited to introduce my FREE AI Pandas Data Analyst Copilot which created a data analysis report with dozens of charts from my questions in under 30 seconds. Today, I'll share with you how to automate data analysis with my Pandas AI Agent + Copilot, which is available on GitHub. I'll guide you through setting up the Copilot app, creating dozens of data analysis charts from any CSV or Excel file, and interacting with your data live. This AI is a BIG help! Table of Contents: 00:00 Introduction to the App 02:24 Setting Up the App 04:25 Using the App 08:58 Understanding the Python Code Github to AI Data Science Team (app is in the apps folder): Get the Code and Future Updates by Joining my Python AI/ML Tips Newsletter: === Want to learn how to build AI projects companies actually want? (live Python Code) On Wednesday, April 9th, I'm sharing one of my best AI Projects: Time Series Forecasting with AI Register here (500 Seats):

Matt Dancho (Business Science)

12,736 Aufrufe • vor 1 Jahr

$I just realized I've been scheduling my biggest AI jobs at the worst possible time, and it was costing me up to 80% more than it needed to. Qoder now runs Qwen3.7-Max and Qwen3.7-Plus with off-peak rates, which means the same models cost significantly less during the off-peak window. here's what changed: • Qwen3.7-Max: 0.5x → 0.1x (up to 80% off) • Qwen3.7-Plus: 0.1x → 0.04x (60% off) the model doesn't change. the reasoning doesn't change. the context length doesn't change. only the credit multiplier does. and the best part? the off-peak rates are applied automatically. no configuration needed. so instead of launching long refactors, migrations, agent runs, or large code generation whenever I think about them... I simply queue them during my off-peak window ( to local time) and let the same flagship Qwen model do the work for a fraction of the usual cost. that's probably the easiest productivity upgrade I've made this month. switch to Qwen3.7-Max or Qwen3.7-Plus in Qoder during your local off-peak hours and compare the credits before and after. search "Google Qoder" or download it here:$

I just realized I've been scheduling my biggest AI jobs at the worst possible time, and it was costing me up to 80% more than it needed to. Qoder now runs Qwen3.7-Max and Qwen3.7-Plus with off-peak rates, which means the same models cost significantly less during the off-peak window. here's what changed: • Qwen3.7-Max: 0.5x → 0.1x (up to 80% off) • Qwen3.7-Plus: 0.1x → 0.04x (60% off) the model doesn't change. the reasoning doesn't change. the context length doesn't change. only the credit multiplier does. and the best part? the off-peak rates are applied automatically. no configuration needed. so instead of launching long refactors, migrations, agent runs, or large code generation whenever I think about them... I simply queue them during my off-peak window ( to local time) and let the same flagship Qwen model do the work for a fraction of the usual cost. that's probably the easiest productivity upgrade I've made this month. switch to Qwen3.7-Max or Qwen3.7-Plus in Qoder during your local off-peak hours and compare the credits before and after. search "Google Qoder" or download it here:

marcus

24,620 Aufrufe • vor 3 Monaten

Is Windsurf better than Cursor? impossible to say, but... it does one thing better: soooo... I spent an hour testing windsurf... and this is what i created... and app called "boop-boop" lol... one thing windsurf does is it searches the internet. If you've been watching my videos you know that i go to perplexity all the time to get code examples and docs. but with windsurf you can just say, "search the replicate top image gen models and add them to the chat we just created" It will search the internet, find the right model then write the code. This is great for replicate and openrouter. You can have one api key in your .env file then just tell windsurf to search for docs for [insert ai model] and it will just add it to your app. Impressed tbh.

Is Windsurf better than Cursor? impossible to say, but... it does one thing better: soooo... I spent an hour testing windsurf... and this is what i created... and app called "boop-boop" lol... one thing windsurf does is it searches the internet. If you've been watching my videos you know that i go to perplexity all the time to get code examples and docs. but with windsurf you can just say, "search the replicate top image gen models and add them to the chat we just created" It will search the internet, find the right model then write the code. This is great for replicate and openrouter. You can have one api key in your .env file then just tell windsurf to search for docs for [insert ai model] and it will just add it to your app. Impressed tbh.

Riley Brown

31,043 Aufrufe • vor 1 Jahr

This is how Opus 5.5 in Claude Code built a WoW-style game in 36h. There's a lot more to it than one prompt. I wrote a detailed spec, gave it access to Unity, Blender and Higgsfield, and packed my own workflow into skills. I go through all of it in the video:

This is how Opus 5.5 in Claude Code built a WoW-style game in 36h. There's a lot more to it than one prompt. I wrote a detailed spec, gave it access to Unity, Blender and Higgsfield, and packed my own workflow into skills. I go through all of it in the video:

Stefan 3D AI

28,628 Aufrufe • vor 7 Tagen

Better Cursor alternative? I've been playing with the new AI IDE Windsurf launched by Codeium past few days, and the result was impressive, particularly: 1. Code base understanding: One thing Windsurf did really well is its understanding of the whole code base & dependencies; This led to a big difference in terms of final code quality 2. Context aware: It actually knows everything I did in the editor, e.g. it automatically knows code edits I made without me prompt it; 3. Reflection: I noticed Windsurf has been finetuned to reflect and try to iterate/improve code it generated autonomously; This was a magic moment for me .... I shared key highlights i had and showcase my process of building a PDF converter product using windsurf 0:00 Platform overview 6:21 How does context aware engine works 10:45 Case study: Build PDF converter Sass ---- If you have any further question or want to get deep dive into more AI coding, you can join my community where I post tips weekly:

Better Cursor alternative? I've been playing with the new AI IDE Windsurf launched by Codeium past few days, and the result was impressive, particularly: 1. Code base understanding: One thing Windsurf did really well is its understanding of the whole code base & dependencies; This led to a big difference in terms of final code quality 2. Context aware: It actually knows everything I did in the editor, e.g. it automatically knows code edits I made without me prompt it; 3. Reflection: I noticed Windsurf has been finetuned to reflect and try to iterate/improve code it generated autonomously; This was a magic moment for me .... I shared key highlights i had and showcase my process of building a PDF converter product using windsurf 0:00 Platform overview 6:21 How does context aware engine works 10:45 Case study: Build PDF converter Sass ---- If you have any further question or want to get deep dive into more AI coding, you can join my community where I post tips weekly:

Jason Zhou

64,713 Aufrufe • vor 1 Jahr