Which AI is better — with a wrapper or without?
I liked a slide from the recent presentation Sequoia Capital AI Ascent 2025.
Big vendors after the launch of ChatGPT insisted that niche and industrial startups consuming AGI intelligence are unpromising.
They disdainfully called them AI wrappers, believing that they have no protection against competitors.
A couple of years later, we observe record growth precisely in such companies as Cursor ($300 million ARR), Loveable, Windsurf (bought by OpenAI for $3 billion), and thousands of new industrial startups — in finance, insurance, e-commerce, legal, accounting, healthcare, and other sectors.
Meanwhile, AI tokens are becoming the fastest depreciating technology and currency in history.
According to Sam Altman himself, over time the cost of AI will equal the cost of energy.
Giants have started giving access to their most powerful AI models to seize leadership in the new technological era.
I have already written about a unique market moment: when, being an expert in any subject area, you combine your knowledge with the growing capabilities of AI — and get a tool that solves real human problems for which clients are ready to pay immediately.
Now these very AI wrappers have turned into serious businesses.
The obvious challenge for entrepreneurs is that AI skills and specialists are increasing in value much faster than other segments of the IT market.
Startups and mature companies with subject matter experts already face difficulties attracting strong AI engineers, but at the same time, according to the results of the first internal hackathons, I see a rapid increase in the number of those who caught the trend and felt in AI a breath of fresh air in the enterprise world.
In the coming years, young founders and enthusiasts who live by technology, see trends ahead, and tirelessly experiment by creating new products will win rapidly.
Time to act!
I liked a slide from the recent presentation Sequoia Capital AI Ascent 2025.
Big vendors after the launch of ChatGPT insisted that niche and industrial startups consuming AGI intelligence are unpromising.
They disdainfully called them AI wrappers, believing that they have no protection against competitors.
A couple of years later, we observe record growth precisely in such companies as Cursor ($300 million ARR), Loveable, Windsurf (bought by OpenAI for $3 billion), and thousands of new industrial startups — in finance, insurance, e-commerce, legal, accounting, healthcare, and other sectors.
Meanwhile, AI tokens are becoming the fastest depreciating technology and currency in history.
According to Sam Altman himself, over time the cost of AI will equal the cost of energy.
Giants have started giving access to their most powerful AI models to seize leadership in the new technological era.
I have already written about a unique market moment: when, being an expert in any subject area, you combine your knowledge with the growing capabilities of AI — and get a tool that solves real human problems for which clients are ready to pay immediately.
Now these very AI wrappers have turned into serious businesses.
The obvious challenge for entrepreneurs is that AI skills and specialists are increasing in value much faster than other segments of the IT market.
Startups and mature companies with subject matter experts already face difficulties attracting strong AI engineers, but at the same time, according to the results of the first internal hackathons, I see a rapid increase in the number of those who caught the trend and felt in AI a breath of fresh air in the enterprise world.
In the coming years, young founders and enthusiasts who live by technology, see trends ahead, and tirelessly experiment by creating new products will win rapidly.
Time to act!
❤2🔥1
Power BI Interview Questions for Entry-Level Data Analysts (Easy-Medium Difficulty) 📊
1. What is Power BI, and how does it fit into the data analysis workflow?
2. Difference between Power BI Desktop and Power BI Service?
3. How to import data into Power BI? What are the various data sources supported?
4. Explain the process of transforming data in Power BI. Which tools or features would you use for data cleaning?
5. What is data modeling in Power BI, and why is it important?
6. How would you create relationships between different tables in Power BI?
7. Explain cardinality and its significance?
8. Describe the steps to create a basic report/dashboard in Power BI?
9. What are best practices for creating effective visualizations in Power BI?
10. What is DAX, and why is it used in Power BI?
11. DAX formulas to calculate a new measure or column?
12. How does data refresh work in Power BI? What options are available for scheduling data refreshes?
13. Process of publishing a Power BI report to the Power BI service?
14. If a Power BI report is loading slowly, what steps would you take to identify and rectify the issue?
15. How do you optimize Power BI reports for better performance?
I have curated the best interview resources to crack Power BI Interviews 👇👇
https://topmate.io/analyst/866125
Hope you'll like it
Like this post if you need more resources like this 👍❤️
1. What is Power BI, and how does it fit into the data analysis workflow?
2. Difference between Power BI Desktop and Power BI Service?
3. How to import data into Power BI? What are the various data sources supported?
4. Explain the process of transforming data in Power BI. Which tools or features would you use for data cleaning?
5. What is data modeling in Power BI, and why is it important?
6. How would you create relationships between different tables in Power BI?
7. Explain cardinality and its significance?
8. Describe the steps to create a basic report/dashboard in Power BI?
9. What are best practices for creating effective visualizations in Power BI?
10. What is DAX, and why is it used in Power BI?
11. DAX formulas to calculate a new measure or column?
12. How does data refresh work in Power BI? What options are available for scheduling data refreshes?
13. Process of publishing a Power BI report to the Power BI service?
14. If a Power BI report is loading slowly, what steps would you take to identify and rectify the issue?
15. How do you optimize Power BI reports for better performance?
I have curated the best interview resources to crack Power BI Interviews 👇👇
https://topmate.io/analyst/866125
Hope you'll like it
Like this post if you need more resources like this 👍❤️
❤3
Frontend Development Interview Questions
Beginner Level
1. What are semantic HTML tags?
2. Difference between id and class in HTML?
3. What is the Box Model in CSS?
4. Difference between margin and padding?
5. What is a responsive web design?
6. What is the use of the <meta viewport> tag?
7. Difference between inline, block, and inline-block elements?
8. What is the difference between == and === in JavaScript?
9. What are arrow functions in JavaScript?
10. What is DOM and how is it used?
Intermediate Level
1. What are pseudo-classes and pseudo-elements in CSS?
2. How do media queries work in responsive design?
3. Difference between relative, absolute, fixed, and sticky positioning?
4. What is the event loop in JavaScript?
5. Explain closures in JavaScript with an example.
6. What are Promises and how do you handle errors with .catch()?
7. What is a higher-order function?
8. What is the difference between localStorage and sessionStorage?
9. How does this keyword work in different contexts?
10. What is JSX in React?
Advanced Level
1. How does the virtual DOM work in React?
2. What are controlled vs uncontrolled components in React?
3. What is useMemo and when should you use it?
4. How do you optimize a large React app for performance?
5. What are React lifecycle methods (class-based) and their hook equivalents?
6. How does Redux work and when should you use it?
7. What is code splitting and why is it useful?
8. How do you secure a frontend app from XSS attacks?
9. Explain the concept of Server-Side Rendering (SSR) vs Client-Side Rendering (CSR).
10. What are Web Components and how do they work?
React ❤️ for the detailed answers
Join for free resources: 👇 https://whatsapp.com/channel/0029VaiSdWu4NVis9yNEE72z
Beginner Level
1. What are semantic HTML tags?
2. Difference between id and class in HTML?
3. What is the Box Model in CSS?
4. Difference between margin and padding?
5. What is a responsive web design?
6. What is the use of the <meta viewport> tag?
7. Difference between inline, block, and inline-block elements?
8. What is the difference between == and === in JavaScript?
9. What are arrow functions in JavaScript?
10. What is DOM and how is it used?
Intermediate Level
1. What are pseudo-classes and pseudo-elements in CSS?
2. How do media queries work in responsive design?
3. Difference between relative, absolute, fixed, and sticky positioning?
4. What is the event loop in JavaScript?
5. Explain closures in JavaScript with an example.
6. What are Promises and how do you handle errors with .catch()?
7. What is a higher-order function?
8. What is the difference between localStorage and sessionStorage?
9. How does this keyword work in different contexts?
10. What is JSX in React?
Advanced Level
1. How does the virtual DOM work in React?
2. What are controlled vs uncontrolled components in React?
3. What is useMemo and when should you use it?
4. How do you optimize a large React app for performance?
5. What are React lifecycle methods (class-based) and their hook equivalents?
6. How does Redux work and when should you use it?
7. What is code splitting and why is it useful?
8. How do you secure a frontend app from XSS attacks?
9. Explain the concept of Server-Side Rendering (SSR) vs Client-Side Rendering (CSR).
10. What are Web Components and how do they work?
React ❤️ for the detailed answers
Join for free resources: 👇 https://whatsapp.com/channel/0029VaiSdWu4NVis9yNEE72z
❤3
Anthropic is putting a limit on a Claude AI feature because people are using it '24/7'
Anthropic has introduced weekly rate limits for its Claude Code feature—used within paid Pro and Max plans—following reports that a small fraction of users have been running Claude “continuously in the background, 24/7,” which resulted in one individual accruing tens of thousands in usage on a $200/month tier and placing unexpected strain on infrastructure.
Starting August 28, 2025, the limits will cap weekly access (e.g. 240–480 hours of Sonnet 4 and 24–40 hours of Opus 4 for Max 20× subscribers), affecting under 5% of users and offering over‑limit users the option to purchase extra usage for continuity—but the move has drawn developer backlash, as some workflows are already being interrupted and critics argue the caps were poorly communicated
Anthropic has introduced weekly rate limits for its Claude Code feature—used within paid Pro and Max plans—following reports that a small fraction of users have been running Claude “continuously in the background, 24/7,” which resulted in one individual accruing tens of thousands in usage on a $200/month tier and placing unexpected strain on infrastructure.
Starting August 28, 2025, the limits will cap weekly access (e.g. 240–480 hours of Sonnet 4 and 24–40 hours of Opus 4 for Max 20× subscribers), affecting under 5% of users and offering over‑limit users the option to purchase extra usage for continuity—but the move has drawn developer backlash, as some workflows are already being interrupted and critics argue the caps were poorly communicated
❤3
Data science is a multidisciplinary field that combines techniques from statistics, computer science, and domain-specific knowledge to extract insights and knowledge from data. Here are some essential concepts in data science:
1. Data Collection: The process of gathering data from various sources, such as databases, files, sensors, and APIs.
2. Data Cleaning: The process of identifying and correcting errors, missing values, and inconsistencies in the data.
3. Data Exploration: The process of summarizing and visualizing the data to understand its characteristics and relationships.
4. Data Preprocessing: The process of transforming and preparing the data for analysis, including feature selection, normalization, and encoding.
5. Machine Learning: A subset of artificial intelligence that uses algorithms to learn patterns and make predictions from data.
6. Statistical Analysis: The use of statistical methods to analyze and interpret data, including hypothesis testing, regression analysis, and clustering.
7. Data Visualization: The graphical representation of data to communicate insights and findings effectively.
8. Model Evaluation: The process of assessing the performance of a predictive model using metrics such as accuracy, precision, recall, and F1 score.
9. Feature Engineering: The process of creating new features or transforming existing features to improve the performance of machine learning models.
10. Big Data: The term used to describe large and complex datasets that require specialized tools and techniques for analysis.
These concepts are foundational to the practice of data science and are essential for extracting valuable insights from data.
Join for more: https://news.1rj.ru/str/datasciencefun
ENJOY LEARNING 👍👍
1. Data Collection: The process of gathering data from various sources, such as databases, files, sensors, and APIs.
2. Data Cleaning: The process of identifying and correcting errors, missing values, and inconsistencies in the data.
3. Data Exploration: The process of summarizing and visualizing the data to understand its characteristics and relationships.
4. Data Preprocessing: The process of transforming and preparing the data for analysis, including feature selection, normalization, and encoding.
5. Machine Learning: A subset of artificial intelligence that uses algorithms to learn patterns and make predictions from data.
6. Statistical Analysis: The use of statistical methods to analyze and interpret data, including hypothesis testing, regression analysis, and clustering.
7. Data Visualization: The graphical representation of data to communicate insights and findings effectively.
8. Model Evaluation: The process of assessing the performance of a predictive model using metrics such as accuracy, precision, recall, and F1 score.
9. Feature Engineering: The process of creating new features or transforming existing features to improve the performance of machine learning models.
10. Big Data: The term used to describe large and complex datasets that require specialized tools and techniques for analysis.
These concepts are foundational to the practice of data science and are essential for extracting valuable insights from data.
Join for more: https://news.1rj.ru/str/datasciencefun
ENJOY LEARNING 👍👍
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Quickly learn & retain new skills!
Try these top 10 ChatGPT prompts:
⏳ Explain Using Analogies
Prompt: "Explain the concept of (concept/theory) using an analogy or comparison to something familiar. Make it relatable and easy to understand with clear examples."
⏳ Develop a Quick Reference Guide
Prompt: "Create a quick reference guide for (skill/subject) that includes essential formulas, key points, and concise summaries for easy review."
⏳ Design Interactive Learning Activities
Prompt: "Suggest interactive activities or exercises that will help me actively engage with and better understand (topic/skill). Include step-by-step instructions and expected outcomes."
⏳ Simulate Real-World Applications
Prompt: "Provide real-world scenarios or applications where I can apply (concept/skill) to reinforce my learning. Include detailed examples and practical exercises."
⏳ Identify Common Mistakes
Prompt: "List common mistakes or pitfalls to avoid when learning (skill/subject) and provide strategies for overcoming them. Include tips for maintaining good practices."
⏳ Create a Daily Practice Routine
Prompt: "Design a daily practice routine to help me steadily improve in (skill/subject) over time. Include specific exercises, time allocations, and progression milestones."
⏳ Use Mnemonics for Memory
Prompt: "Create mnemonic devices to help me remember important information related to (topic/subject). Explain how each mnemonic works and provide examples."
⏳ Set Achievable Micro-Goals
Prompt: "Break down (skill/subject) into small, achievable goals that will keep me motivated and on track. Include a timeline and criteria for measuring success."
⏳ Leverage Peer Learning
Prompt: "Suggest ways to find or create a study group or learning community to practice and discuss (skill/subject) with peers. Include strategies for effective group learning."
⏳ Apply Spaced Repetition Technique
Prompt: "Set up a spaced repetition schedule to review and retain information for (topic/subject). Include intervals, review methods, and tips for long-term retention."
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Like for more ❤️
All the best 👍 👍
Try these top 10 ChatGPT prompts:
⏳ Explain Using Analogies
Prompt: "Explain the concept of (concept/theory) using an analogy or comparison to something familiar. Make it relatable and easy to understand with clear examples."
⏳ Develop a Quick Reference Guide
Prompt: "Create a quick reference guide for (skill/subject) that includes essential formulas, key points, and concise summaries for easy review."
⏳ Design Interactive Learning Activities
Prompt: "Suggest interactive activities or exercises that will help me actively engage with and better understand (topic/skill). Include step-by-step instructions and expected outcomes."
⏳ Simulate Real-World Applications
Prompt: "Provide real-world scenarios or applications where I can apply (concept/skill) to reinforce my learning. Include detailed examples and practical exercises."
⏳ Identify Common Mistakes
Prompt: "List common mistakes or pitfalls to avoid when learning (skill/subject) and provide strategies for overcoming them. Include tips for maintaining good practices."
⏳ Create a Daily Practice Routine
Prompt: "Design a daily practice routine to help me steadily improve in (skill/subject) over time. Include specific exercises, time allocations, and progression milestones."
⏳ Use Mnemonics for Memory
Prompt: "Create mnemonic devices to help me remember important information related to (topic/subject). Explain how each mnemonic works and provide examples."
⏳ Set Achievable Micro-Goals
Prompt: "Break down (skill/subject) into small, achievable goals that will keep me motivated and on track. Include a timeline and criteria for measuring success."
⏳ Leverage Peer Learning
Prompt: "Suggest ways to find or create a study group or learning community to practice and discuss (skill/subject) with peers. Include strategies for effective group learning."
⏳ Apply Spaced Repetition Technique
Prompt: "Set up a spaced repetition schedule to review and retain information for (topic/subject). Include intervals, review methods, and tips for long-term retention."
👉WhatsApp Channel: https://whatsapp.com/channel/0029VaI5CV93AzNUiZ5Tt226
👉Telegram Link: https://news.1rj.ru/str/addlist/ID95piZJZa0wYzk5
Like for more ❤️
All the best 👍 👍
❤4👍1
How to be a Prompt Engineer 101
The shortest and most comprehensive guide
1. start with an explanation
Make a denoscription and character situation at the beginning of the Prompt
Error example:
Please help me read the following code:
{your input here}
Correct example:
2. Prompt to describe the situation
In the prompt, it is necessary to describe the context, result, length, format and style as much as possible
Error example:
Write a short story for kids
Correct example:
3. gives output in the format
If you are doing data analysis, please give the input template of the format
Error example:
Extract house pricing data from the following text.
Text: """
{your text containing pricing data}
"""
Correct example:
4. Add some example questions and answers
Sometimes adding some question and answer examples can make GPT more intelligent
Correct example:
The question and answer example is also a standard template example in fine-tune
5. Simplify the sentence and clarify the purpose
Keep your words as short as possible and don't say useless content
Error example:
ChatGPT, write a sales page for my company selling sand in the desert, please write only a few sentences, nothing long and complex
Correct example:
6. Good at using introductory words
Error example:
Write a Python function that plots my net worth over 10 years for different inputs on the initial investment and a given ROI
Correct example:
The shortest and most comprehensive guide
1. start with an explanation
Make a denoscription and character situation at the beginning of the Prompt
Error example:
Please help me read the following code:
{your input here}
Correct example:
Now let's play the role, you are a senior information security engineer, I will give you a piece of code, please help me read the code and point out where there may be security vulnerable.
Text: """
{your input here}
"""2. Prompt to describe the situation
In the prompt, it is necessary to describe the context, result, length, format and style as much as possible
Error example:
Write a short story for kids
Correct example:
Write a funny soccer story for kids that teaches the kid that persistence is the key for success in the style of Rowling.3. gives output in the format
If you are doing data analysis, please give the input template of the format
Error example:
Extract house pricing data from the following text.
Text: """
{your text containing pricing data}
"""
Correct example:
Extract house pricing data from the following text.
Desired format: """
House 1 | $1,000,000 | 100 sqm
House 2 | $500,000 | 90 sqm
... (and so on)
"""
Text: """
{your text containing pricing data}
"""4. Add some example questions and answers
Sometimes adding some question and answer examples can make GPT more intelligent
Correct example:
Extract brand names from the texts below.
Text 1: Finxter and YouTube are tech companies. Google is too.
Brand names 2: Finxter, YouTube, Google
###
Text 2: If you like tech, you'll love Finxter!
Brand names 2: Finxter
###
Text 3: {your text here}Brand names 3:The question and answer example is also a standard template example in fine-tune
5. Simplify the sentence and clarify the purpose
Keep your words as short as possible and don't say useless content
Error example:
ChatGPT, write a sales page for my company selling sand in the desert, please write only a few sentences, nothing long and complex
Correct example:
Write a 5-sentence sales page, sell sand in the desert.6. Good at using introductory words
Error example:
Write a Python function that plots my net worth over 10 years for different inputs on the initial investment and a given ROI
Correct example:
# Python function that plots net worth over 10
# years for different inputs on the initial
# investment and a given ROI
import matplotlib
def plot_net_worth(initial, roi):❤4👍1
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VIEW IN TELEGRAM
Ideogram Character is a powerful tool to create studio-quality AI headshots in seconds. Perfect for LinkedIn and social profiles.
Quick tutorial + master prompt below:
Professional headshot portrait. Person is [expression], wearing [wardrobe]. Background is [setting]. Lighting is [atmosphere].
Quick tutorial + master prompt below:
Professional headshot portrait. Person is [expression], wearing [wardrobe]. Background is [setting]. Lighting is [atmosphere].
❤3
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7. Python ➝
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8. SQL ➝
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9. Git and GitHub ➝
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10. Blockchain ➝
◀️ https://news.1rj.ru/str/Bitcoin_Crypto_Web
11. Mongo DB ➝
◀️ http://mongodb.com
12. Node JS ➝
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13. English Speaking ➝
◀️ https://news.1rj.ru/str/englishlearnerspro
14. C#➝
◀️https://learn.microsoft.com/en-us/training/paths/get-started-c-sharp-part-1/
15. Excel➝
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16. Generative AI➝
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ENJOY LEARNING👍👍
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🔖 8 Chat Prompts to Grow a Marketing Agency in 2025 📈💼
1️⃣ Define a Profitable Niche
✅ Prompt: "Help me choose a profitable niche for my marketing agency based on market demand and competition."
2️⃣ Craft an Irresistible Offer
✅ Prompt: "Write a compelling marketing offer for my agency that helps [target business type] generate leads/sales through [service]."
3️⃣ Client Outreach Message
✅ Prompt: "Create a cold email/DM pitch for my agency offering [Facebook ads, SEO, content marketing, etc.] to [target industry]."
4️⃣ Service Package Builder
✅ Prompt: "Help me design 3 tiers of service packages for my agency, including features, pricing, and deliverables."
5️⃣ Agency Website Copy
✅ Prompt: "Write persuasive homepage copy for a [niche] marketing agency that highlights results, credibility, and a CTA."
6️⃣ Lead Magnet & Funnel Idea
✅ Prompt: "Suggest a lead magnet idea + email funnel for generating leads for my [type of] marketing agency."
7️⃣ Client Onboarding Process
✅ Prompt: "Build a smooth client onboarding checklist for my agency to make a great first impression and set expectations."
8️⃣ Retention & Upsell Strategy
✅ Prompt: "Give me 5 strategies to retain clients longer and upsell them on more services."
Double Tap ❤️ for more!
1️⃣ Define a Profitable Niche
✅ Prompt: "Help me choose a profitable niche for my marketing agency based on market demand and competition."
2️⃣ Craft an Irresistible Offer
✅ Prompt: "Write a compelling marketing offer for my agency that helps [target business type] generate leads/sales through [service]."
3️⃣ Client Outreach Message
✅ Prompt: "Create a cold email/DM pitch for my agency offering [Facebook ads, SEO, content marketing, etc.] to [target industry]."
4️⃣ Service Package Builder
✅ Prompt: "Help me design 3 tiers of service packages for my agency, including features, pricing, and deliverables."
5️⃣ Agency Website Copy
✅ Prompt: "Write persuasive homepage copy for a [niche] marketing agency that highlights results, credibility, and a CTA."
6️⃣ Lead Magnet & Funnel Idea
✅ Prompt: "Suggest a lead magnet idea + email funnel for generating leads for my [type of] marketing agency."
7️⃣ Client Onboarding Process
✅ Prompt: "Build a smooth client onboarding checklist for my agency to make a great first impression and set expectations."
8️⃣ Retention & Upsell Strategy
✅ Prompt: "Give me 5 strategies to retain clients longer and upsell them on more services."
Double Tap ❤️ for more!
❤7👏2👍1
🚀 AI Journey Contest 2025: Test your AI skills!
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3. Create your solution and submit it by 30 October 2025.
🚀 Ready for a challenge? Join a global developer community and show your AI skills!
Join our international online AI competition. Register now for the contest! Award fund — RUB 6.5 mln!
Choose your track:
· 🤖 Agent-as-Judge — build a universal “judge” to evaluate AI-generated texts.
· 🧠 Human-centered AI Assistant — develop a personalized assistant based on GigaChat that mimics human behavior and anticipates preferences. Participants will receive API tokens and a chance to get an additional 1M tokens.
· 💾 GigaMemory — design a long-term memory mechanism for LLMs so the assistant can remember and use important facts in dialogue.
Why Join
Level up your skills, add a strong line to your resume, tackle pro-level tasks, compete for an award, and get an opportunity to showcase your work at AI Journey, a leading international AI conference.
How to Join
1. Register here: https://short-url.org/1fN0p
2. Choose your track.
3. Create your solution and submit it by 30 October 2025.
🚀 Ready for a challenge? Join a global developer community and show your AI skills!
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