In 2025, AI agents are changing how developers code, build, and think about software. In this video, an experienced solution architect Vladislav Vorobev explains the real differences between popular AI assistants like Copilot and Windsurf, how AI agents actually work in programming, what skills developers need to stay competitive, and where the line is between useful help and losing control over code quality. If you want to stay ahead in the era of AI-driven development, this video is a must-watch.

NAVIGATION

0:59 - Agents, Copilot, Windsurf - everyone talks about AI assistants. How do they actually differ, and what types of tasks is each best suited for?

2:36 - What is AI Agent for programming?

4:34 - What is the difference between AI Agents and LLMs?

5:19 - What are some real-world examples of using AI agents in development?

6:37 - IDEs like Windsurf or Cursor are often described as the "next step after GitHub Copilot." What fundamental advantages do they offer developers?

7:35 - Where is the line between convenience from AI assistants and the risk of losing control over the quality of code and solutions?

8:46 - What are prompting techniques and are they important for developers?

11:00 - What skills should programmers start developing today to remain competitive in the age of AI-driven software development?

12:02 - What should junior developers do in the age of AI?

12:42 - How is the role of a developer changing as more routine tasks shift to AI agents and copilots?

13:25 - If you were starting a programming career today, what AI tools would you recommend a newcomer learn first?

👉 Integrate GitHub Copilot and ChatGPT into your daily work: https://aw.club/global/en/courses/ai-supported-software-engineering

WHERE TO WATCH US AND LISTEN

🔸 YouTube: https://youtu.be/FF90PmbZ0T0

🔸 Apple Podcasts: https://bit.ly/awclub-en-apple

🔸 Spotify: https://bit.ly/awclub-en-spotify

🔸 Download mp3: https://anywhereclub.simplecast.com/episodes/35

#engx #engxspace #aiexents

In this first episode of our new podcast, Gordon Mullan and Govind Shukla discuss the latest news in the world of AI, plus other news from robotics, ethics, regulation, and more!

NAVIGATION

00:00 - Introduction

06:42 - Google

18:15 - OpenAI

21:44 - Microsoft

40:08 - Mistral

45:16 - China: Alibaba

52:40 - China: Manus

56:30 - Windsurf Editor

57:40 - Cursor IDE

59:27 - Opera

1:00:10 - Cohere

1:05:35 - Law and Order

1:16:45 - Science and Technology

1:31:34 - Conclusion

WHERE TO WATCH US AND LISTEN

🔸 YouTube: https://youtu.be/o6LIEhjB0_0

🔸 Apple Podcasts: https://bit.ly/awclub-en-apple

🔸 Spotify: https://bit.ly/awclub-en-spotify

🔸 Download mp3: https://anywhereclub.simplecast.com/episodes/36

SERVICES AND LINKS FROM THE EPISODE

🔹 Google's Investment in Anthropic: https://www.nytimes.com/2025/03/11/technology/google-investment-anthropic.html

🔹 AI Studio Gemini 2.0 Flash Experimental: https://aistudio.google.com/prompts/new_chat

🔹 Gemma-3: https://huggingface.co/collections/google/gemma-3-release-67c6c6f89c4f76621268bb6d

🔹 AI Mode in Google Search: https://blog.google/products/search/ai-mode-search/

🔹 Python Interpreter (code execution): https://developers.googleblog.com/en/gemini-20-deep-dive-code-execution/

🔹 Gemini Embeddings: https://ai.google.dev/gemini-api/docs/embeddings

🔹 ChatGPT for macOS now edits code in IDE: https://x.com/OpenAIDevs/status/1897700857833193955

🔹 New API Tools for AI Agents: https://www.youtube.com/live/hciNKcLwSes

🔹 NextGenAI Contracts with Universities: https://openai.com/index/introducing-nextgenai/

🔹 OpenAI's $20,000 AI Agents: https://www.theinformation.com/articles/openai-plots-charging-20-000-a-month-for-phd-level-agents

🔹 Microsoft MAI: https://fortune.com/2025/03/07/microsoft-creates-in-house-ai-models-it-believes-rival-openais/?utm_source=www.therundown.ai&utm_medium=newsletter&utm_campaign=ilya-s-secret-asi-roadmap&_bhlid=dfb9c2edd83857673d88b02ebd6081ea969029c8

🔹 Mistral OCR: https://mistral.ai/news/mistral-ocr

🔹 QwQ-32B: https://qwenlm.github.io/blog/qwq-32b/

🔹 Fine-tuning QwQ-32B (START): https://www.alphaxiv.org/abs/2503.04625

🔹 Alibaba’s R1-Omni Model: https://www.bloomberg.com/news/articles/2025-03-12/alibaba-releases-emotional-intelligence-model-to-rival-chatgpt

🔹 R1-Omni on Hugging Face: https://huggingface.co/StarJiaxing/R1-Omni-0.5B

🔹 Qwen Chat Enhancements: https://x.com/Alibaba_Qwen/status/1899497336889659775?utm_source=alphasignal

🔹 Qwen Chat: https://chat.qwen.ai/

🔹 AI-agent Manus: https://manus.im/

🔹 Manus reveals internals to users: https://x.com/jianxliao/status/1898861051183349870?s=46&t=dUCVh9akIWxxNUIkrDJwJg

🔹 Prompt for Manus: https://gist.github.com/jlia0/db0a9695b3ca7609c9b1a08dcbf872c9

🔹 Mistral OCR: https://mistral.ai/news/mistral-ocr

🔹 Anthropic’s Request for AI Regulation: https://www.anthropic.com/news/anthropic-s-recommendations-ostp-u-s-ai-action-plan

🔹 Gemini Robotics from Google: https://deepmind.google/discover/blog/gemini-robotics-brings-ai-into-the-physical-world/

🔹 AI Scientist by Sakana AI: https://sakana.ai/ai-scientist-first-publication/

🔹 Users Form Emotional Bonds with AI Voices: https://arstechnica.com/ai/2025/03/users-report-emotional-bonds-with-startlingly-realistic-ai-voice-demo/

🔹 Cohere Releases Command Model: https://docs.cohere.com/v1/reference/generate

🔹 AI Content Labeling Law in Spain: https://www.elconfidencial.com/espana/2021-02-01/sentencia-tsjc-elecciones-catalanas-14f_2931096/

🔹 Windsurf Editor Update: https://windsurf.dev/blog/ai-first-editor

🔹 Raycast Pro AI: https://www.raycast.com/blog/raycast-pro

🔹 OpenAI’s Agents SDK Library: https://platform.openai.com/docs/guides/agents

🔹 OpenAI to Sell High-End AI Agents: https://www.theinformation.com/articles/openai-plots-charging-20-000-a-month-for-phd-level-agents

#aiapodcast #engx #manus

Discover an easy Introduction to the Software Development Life Cycle (SDLC) in this video! Aleksandr Gushchin, a Delivery Manager for big clients, breaks down the SDLC in software engineering with a simple, clear approach. Learn the fundamentals, explore SDLC models, and uncover best practices that drive engineering excellence.

In just 40 minutes, you'll get a simplified overview—from "What is Software Development Life Cycle" to "Software Engineering Best Practices You Should Follow" and "What AI tools should Developers use?". See how agile methods and AI help senior programmers write better code, deliver business value faster, and reduce costs. If you're looking for a straightforward guide to the software development lifecycle, this video is a must-watch!

COURSES BY ENGX

👉 Software Delivery Cost Optimizer: https://aw.club/global/en/courses/engx-code-review

👉 EngX Code Review: https://aw.club/global/en/teams/software-delivery-cost-optimizer

NAVIGATION

0:00 Intro

1:19 Fundamentals of SDLC

3:01 Enhancing Efficiency in SDLC

4:27 Reducing Costs and Avoiding Waste

5:09 Importance of Market Research in SDLC

6:33 Initial Phases of SDLC

7:50 Solution Design and Custom Development

8:52 Implementation and Testing of Solutions

10:10 Ensuring High-Quality Development Standards

11:02 Effective Communication and Documentation

12:13 Managing Known and Stable Project Scopes

13:25 Application of Agile in Predictable Environments

14:19 Factory Model in Software Development

15:09 Handling Dynamic Project Environments

16:15 Strategy and Management in Unfamiliar Situations

17:09 Experimentation and Proof of Concept in SDLC

18:23 Importance of Clear Requirements and Testing

19:17 Enhancing Developer Focus and Testing

20:09 Quality Gates and Development Output

21:10 Addressing and Managing Technical Debt

22:10 Improving Performance with Quality Initiatives

23:32 Role of Unit Testing in Quality Assurance

24:24 Continuous Quality and Assurance Practices

25:24 Shift-Left Approach in Testing

26:05 Analyzing and Optimizing Delivery Pipelines

27:26 Role of AI in Streamlining SDLC Processes

28:52 Choosing the Right Management Methodology

30:10 Efficiency of Regression Testing and Automation

31:38 Agile and Continuous Delivery in Complex Projects

33:18 Advantages of Kanban and Continuous Delivery

34:26 Evaluating and Improving SDLC Processes

35:44 Reworking Tasks for Testability and Independence

37:14 Code Documentation and Traceability

38:20 Developer's Role in Business Value Delivery

39:27 Reducing Maintenance Costs through Quality Assurance

40:29 Utilizing AI for Routine Task Automation

41:37 Enhancing SDLC with Quality Gates

42:33 Implementing Advanced Security and Analysis Tools

43:48 AI Assistance in Development and Testing

45:23 Leveraging AI for Testing and Quality Improvement

47:26 Encouraging Continuous Learning and Engagement

47:26 Final words

WHERE TO WATCH US AND LISTEN

🔸 YouTube: https://youtu.be/3ADcI14kiNM

🔸 Google Podcasts: https://bit.ly/awclub-en-google

🔸 Apple Podcasts: https://bit.ly/awclub-en-apple

🔸 Spotify: https://bit.ly/awclub-en-spotify

🔸 Download mp3: https://anywhereclub.simplecast.com/episodes/34

#engx #sdlc #engineering

In this episode of "Interview Anywhere," we explore data structures and algorithms coding interview questions and answers. This episode will be helpful for beginners as well as for experts with more than four years of experience. Watch as Pratik Jagtap, our candidate, solves coding challenges and handles in-depth questions from our expert interviewer, Saurabh Shekhar.

NAVIGATION

00:00 Intro

01:14 Introduction of participant

02:31 Theoretical part 1

02:54 ArrayList vs LinkedList

05:11 Internal HashMap

09:23 Quick Sort vs Merge Sort

11:47 Building a Leaderboard

15:07 Solving the Leaderboard Problem

20:11 Optimizing Complexity

27:39 Implementation and Testing

34:30 Data Updates

42:42 Testing and Debugging

50:21 Reducing and Sorting Maps

01:00:19 Kadane’s Algorithm

01:09:07 Handling Negative Values

1:14:39 Feedback session

01:16:15 Expert verdict

01:18:17 Final Thoughts

COURSES BY ENGX

👉 Integrate GitHub Copilot and ChatGPT into your daily work for streamlined, efficient development. with course "AI for software Engineers on EngX": https://aw.club/global/en/courses/ai-supported-software-engineering

👉 Integrate a generative AI toolset into your product development processes to boost team performance with course "AI adoption for teams": https://aw.club/global/en/courses/generative-ai-adoption-for-engineering-teams

👉 Mini AI Workshop for Dev Teams: https://aw.club/global/en/courses/engx-ai-adoption-workshop

WHERE TO WATCH US AND LISTEN

🔸 YouTube: https://youtu.be/3Bgk8Mft00E

🔸 Apple Podcasts: https://bit.ly/awclub-en-apple

🔸 Spotify: https://bit.ly/awclub-en-spotify

🔸 Download mp3: https://anywhereclub.simplecast.com/episodes/33

#engx #mockinterview #dsa

In this insightful video, Viktor Vedmich, Senior Developer Advocate at AWS, delves into a suite of AWS services meticulously crafted for developers. He provides an in-depth exploration of Amazon Q, a generative AI-powered assistant designed to streamline development workflows. Viktor also introduces Amazon Q for Developers, an extension that offers advanced coding assistance, and Amazon Bedrock, a fully managed service that simplifies the creation and scaling of generative AI applications. This comprehensive guide is essential for developers aiming to leverage AWS's cutting-edge AI tools to enhance productivity and innovation.

NAVIGATION

0:00 Start

0:17 Generative AI

1:13 What kinds of AI-related services

does AWS provide for developers?

3:46 What is Amazon Q?

8:29 How can we start working with

Amazon Q Developer?

9:46 More about

Amazon Q Developer

and IDE integration?

11:28 How can you convince your boss

that Amazon Q is safe enough

to use on a project?

14:00 Final words

AI IN AWS

🔸 Amazon Bedrock: https://aws.amazon.com/bedrock

🔸 Amazon Q: https://aws.amazon.com/q/

🔸 Amazon Q for Developers: https://aws.amazon.com/q/developer/

COURSES BY ENGX

👉 Integrate GitHub Copilot and ChatGPT into your daily work for streamlined, efficient development. with course "AI for software Engineers on EngX": https://aw.club/global/en/courses/ai-supported-software-engineering

👉 Integrate a generative AI toolset into your product development processes to boost team performance with course "AI adoption for teams": https://aw.club/global/en/courses/generative-ai-adoption-for-engineering-teams

👉 Mini AI Workshop for Dev Teams: https://aw.club/global/en/courses/engx-ai-adoption-workshop

WHERE TO WATCH US AND LISTEN

🔸 YouTube: https://youtu.be/0kXQHpaVLFM

🔸 Apple Podcasts: https://bit.ly/awclub-en-apple

🔸 Spotify: https://bit.ly/awclub-en-spotify

🔸 Download mp3: https://anywhereclub.simplecast.com/episodes/32

#awclub #engx #ai

In this episode, Aleksas Drozdovskis, an Experience Consultant, and Roman Zatitsky, a Product Manager, dive into the idea of "product thinking" from an engineer’s point of view. They chat about how product thinking helps with career growth, influences business decisions, reduces team stress and burnout, and makes engineers more aligned and effective.

🔹Aleksas Drozdovskis: https://www.linkedin.com/in/drozdovskis/

🔹Roman Zatitskiy: https://www.linkedin.com/in/zatitskiyrb/

NAVIGATION

00:00 Introduction of Aleksas Drozdovskis

00:58 What is product mindset

04:24 Why should i care about discovery and business value

10:03 Who gets more promotion?

11:36 How product mindset can decrease the tension between engineers teams and business teams

14:27 Story about project to product transformation

17:09 How to cultivate a product-oriented culture in a team

20:53 How product mindset influence on the impact that engineers have

24:22 Engineers build features based on discovery that don't get used

28:57 Sum up

31:09 Final

COURSES FROM EPISODE

👉 Generative AI for managers: https://aw.club/global/en/courses/gen-ai-for-managers

👉 AI adoption workshop for engineering teams: https://aw.club/global/en/courses/engx-ai-adoption-workshop

👉 EngX HI: Navigating Team Dynamics: https://aw.club/global/en/courses/navigating-teams-dynamics

WHERE TO WATCH US AND LISTEN

🔸 YouTube: https://youtu.be/R9hKz5pJEwk

🔸 Apple Podcasts: https://bit.ly/awclub-en-apple

🔸 Spotify: https://bit.ly/awclub-en-spotify

🔸 Download mp3: 'simplecast episode link placeholder'

#awclub #engx #productthinking

👉 Course: "AI-supported software engineering": https://epa.ms/ai-swe

👉 Course: "AI-Supported Testing": https://epa.ms/ai-aqa

👉 Course: "Prompt Engineering Foundations": https://epa.ms/ai-pef

👉 Join the EngX: https://epa.ms/engx-club

How AI is Revolutionizing Cancer Research and Treatment? In this episode of the ZuriAI podcast, we explore how AI is transforming the prediction, diagnosis, and treatment of cancer. Artem Shmatko, a doctoral student and ML researcher at the German Cancer Research Center, explains AI’s growing influence in oncology.

We discuss:

What cancer is and why it’s challenging to prevent and diagnose

How AI is impacting drug discovery

Medical data aspects and limitations

The role of computer vision in histopathology

Challenges related to data management and patient privacy

NAVIGATION

0:00 Start

0:43 EngX

1:20 Meet our expert, Artem Shmatko

1:49 What is cancer? Complexity and diversity of cancers.

6:52 Why is it so difficult? Challenges of preventing cancer

10:17 How AI is becoming a pivotal tool in cancer prevention and treatment strategies.

12:40 MRI as a prevention technique.

14:38 The role of AI as a decision-support system in clinical settings.

22:01 AI in drug discovery. Transforming cancer treatment pipelines.

26:42 AI-powered recommendation systems for defining focus groups in clinical trials.

28:14 The complexities of data ingestion and collection in cancer research.

30:39 Handling patient-sensitive data: The ethical and technical challenges.

34:13 Certification and regulation in AI-driven oncology.

36:24 How computer vision and histopathology diagnostics are being redefined by AI.

38:27 The importance of image size and resolution in cancer diagnostics.

41:44 Discussing the potential of 100k*100k pixel resolution in medical imaging.

43:05 The technical limitations in cancer detection using computer vision.

46:03 Multiple instance learning

49:27 Data challenges in AI-driven oncology.

53:35 The role of open-source platforms in advancing medical AI.

57:26 Forecasting the impact of AI on the future of cancer prevention and diagnostics.

1:00:35 What industry challenges can AI overcome in oncology?

LINKS FROM THE EPISODE

🔹 AI's Evolution in Music/ ZuriAI #1: https://www.youtube.com/watch?v=KRJV-1Y61SM

🔹 What is cancer: https://www.cancer.gov/about-cancer/understanding/what-is-cancer

🔹 Classification of brain tumours: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8328013/

🔹 AI based solutions for determination of cell origin: https://www.nature.com/articles/s41586-021-03512-4

🔹 On diagnosing cancer using blood samples: https://doi.org/10.1093/nar/gkz942

🔹 Content-Based Image Retrieval (CBIR) for histological images: https://doi.org/10.1016/j.media.2020.101757

🔹 Automating drug discovery: https://doi.org/10.1038/nrd.2017.232

🔹AI for computational histopathology: https://www.nature.com/articles/s43018-022-00436-4

🔹 Pretrained feature extractors for Multiple Instance Learning (MIL) pipelines: https://www.nature.com/articles/s41591-024-02857-3

🔹 https://www.nature.com/articles/s41586-024-07441-w

🔹 Predicting DNA mutations from histological images: https://www.nature.com/articles/s43018-020-0085-8

WHERE TO WATCH US AND LISTEN

🔸 YouTube: https://youtu.be/XreqENCkpqE

🔸 Google Podcasts: https://bit.ly/awclub-en-google

🔸 Apple Podcasts: https://bit.ly/awclub-en-apple

🔸 Spotify: https://bit.ly/awclub-en-spotify

🔸 Download mp3: https://anywhereclub.simplecast.com/episodes/30

#awclub #engx #ai #oncology