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Artificial Intelligence & ChatGPT Prompts
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πUnlock Your Coding Potential with ChatGPT π Your Ultimate Guide to Ace Coding Interviews! π» Coding tips, practice questions, and expert advice to land your dream tech job. For Promotions: @love_data
Show moreπ Analytical overview of Telegram channel Artificial Intelligence & ChatGPT Prompts
Channel Artificial Intelligence & ChatGPT Prompts (@curiousprogrammer) in the English language segment is an active participant. Currently, the community unites 42 135 subscribers, ranking 3 216 in the Technologies & Applications category and 9 415 in the India region.
π Audience metrics and dynamics
Since its creation on Π½Π΅Π²ΡΠ΄ΠΎΠΌΠΎ, the project has demonstrated rapid growth, gathering an audience of 42 135 subscribers.
According to the latest data from 19 June, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by 187 over the last 30 days and by 2 over the last 24 hours, overall reach remains high.
- Verification status: Not verified
- Engagement rate (ER): The average audience engagement rate is 2.08%. Within the first 24 hours after publication, content typically collects 0.62% reactions from the total number of subscribers.
- Post reach: On average, each post receives 877 views. Within the first day, a publication typically gains 261 views.
- Reactions and interaction: The audience actively supports content: the average number of reactions per post is 3.
- Thematic interests: Content is focused on key topics such as learning, algorithm, detection, llm, pattern.
π Description and content policy
The author describes the resource as a platform for expressing subjective opinions:
βπUnlock Your Coding Potential with ChatGPT
π Your Ultimate Guide to Ace Coding Interviews!
π» Coding tips, practice questions, and expert advice to land your dream tech job.
For Promotions: @love_dataβ
Thanks to the high frequency of updates (latest data received on 20 June, 2026), the channel maintains relevance and a high level of publication reach. Analytics show that the audience actively interacts with content, making it an important point of influence in the Technologies & Applications category.
42 135
Subscribers
+224 hours
+207 days
+18730 days
Posts Archive
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Hey marketers!
You know what? I just found these stories. I hope it will encourage you as much as they encouraged me.
1.
Walt Disney was rejected before anyone invested in Mickey Mouse
Walt Disney is one of the most creative minds ever, but his creativity wasn't immediately recognized by the world around him. When he was 22, Disney was fired from a Missouri newspaper for his lack of creativity. When he brought the idea of Mickey Mouse to more than 300 investors, they thought it was absurd. Eventually, Disney went on to garner 59 Academy Award nominations and 32 wins, the most by any individual.
2.
The Museum of Modern Art turned down Andy Warhol's gift of a drawing
In 1956, famous pop artist Andy Warhol attempted to gift one of his drawings, "Shoe," to the MoMA in New York. He received a rejection letter, saying the museum did not have space for it. Today, art experts expect Andy Warhol paintings to sell for $50 million at auctions, and the MoMA now has 168 pieces by the artist.
3.
Jim Lee was rejected multiple times by Marvel before being hired as a cartoonist
Today, Jim Lee is known for his legendary comics style, drawing "X-Men" in the 1980s and founding his own comics company, Image Comics. However, Lee sent multiple comic submissions to Marvel and DC before he was hired, and they were all rejected. Lucky for all of us, the cartoonist was eventually hired by Marvel to draw "Double Vision," and his career blossomed from there.
I know itβs not really marketing post. But I want to inspire you to do big things, two of the most important traits to have are perseverance and belief in yourself. These now-legendary creatives received crazy rejections but didn't give up, ultimately climbing to their great levels of success.
Go for it!!!
Product management tools & tech stack
Tools for capturing qualitative user feedback
βͺ Zoom and Chorus.ai for conducting interviews
βͺ Slack, Google Docs, or Notion for making notes of key points and action items
βͺ Zendesk and Intercom for meeting customers where they are
βͺ Saleforce for better understanding the needs and pain points of prospects
Tools for capturing quantitative feedback
βͺ FullStory records how people flow through your product
βͺ Amplitude and Mixpanel help you dive deep into product analytics.
βͺ SurveyMonkey allows you to measure your NPS score, get a sense of product/market fit, and understand how happy/unhappy people are with your product.
Tools for validating the problem
βͺ Miro enables virtual whiteboarding to communicate your ideas visually.
βͺ Loom lets you record a screen capture along with audio, making it easy to walk people through your thinking
Product management tools for exploring the solution space
Tools for ideating solutions
βͺ Figma lets you create interactive prototypes
Tools for prioritizing your work
βͺ Productboard helps you decide which projects and features to move forward with, what sort of timeline to address them in, and how to keep stakeholders in the loop.
Product team cases where a #productteams improved content discovery
Case: Netflix and Personalized Content Recommendations
Problem: Netflix wanted to improve user engagement by enhancing content discovery and reducing churn.
Solution: Using a product outcome mindset, Netflix's product team developed a recommendation algorithm that analyzed user viewing behavior and preferences to offer personalized content suggestions.
Outcome: Netflix saw a significant increase in user engagement, with the personalized recommendations leading to higher watch times and reduced churn.
Learn more: You can read about Netflix's recommendation system in various articles and research papers, such as "Netflix Recommendations: Beyond the 5 stars" (by Netflix).
Case: Spotify and Music Discovery
Problem: Spotify users were overwhelmed by the vast music library and struggled to discover new music.
Solution: Spotify's product team used data-driven insights to create personalized playlists like "Discover Weekly" and "Release Radar," tailored to users' listening habits.
Outcome: The personalized playlists increased user engagement, time spent on the platform, and the likelihood of users discovering and enjoying new music.
Link: Learn more about Spotify's approach to music discovery in articles like "How Spotify Discover Weekly and Release Radar Playlist Work" (by The Verge).
