DataSense

𝗡𝗲𝘄 𝗣𝗿𝗼𝗷𝗲𝗰𝘁: 𝗔𝗴𝗲𝗻𝘁𝗶𝗰 𝗘𝗧𝗟 (Free till June 30)

I just released a 3 hour hands on project where you build an 𝗔𝗜 𝗗𝗮𝘁𝗮 𝗠𝗶𝗴𝗿𝗮𝘁𝗶𝗼𝗻 𝗣𝗹𝗮𝘁𝗳𝗼𝗿𝗺 that moves files from Snowflake to Google Cloud Storage using LLM agents.

Instead of static ETL scripts, you build an AI orchestrated system where the agent understands natural language, inspects storage, decides what to move, handles versioning, and automates the full pipeline through a chat UI.

𝗛𝗶𝗴𝗵𝗹𝗶𝗴𝗵𝘁𝘀:

1. LLM agent with tool calling to Snowflake and GCS
2. React chat dashboard plus FastAPI async backend
3. LangChain agent with tool routing
4. Conflict aware versioning and automated cleanup
5. Natural language control over the whole pipeline

𝗦𝘁𝗮𝗰𝗸: React, FastAPI, LangChain, Snowflake, GCS

Free in my Skool community until June 30. After that it moves under the paid subscription.

Link- www.skool.com/the-agent-lab-3899/about

1 day ago | [YT] | 0

DataSense

𝐀𝐫𝐞 𝐲𝐨𝐮 𝐬𝐭𝐢𝐥𝐥 𝐩𝐫𝐨𝐦𝐩𝐭𝐢𝐧𝐠 𝐲𝐨𝐮𝐫 𝐚𝐠𝐞𝐧𝐭, 𝐨𝐫 𝐝𝐞𝐬𝐢𝐠𝐧𝐢𝐧𝐠 𝐭𝐡𝐞 𝐥𝐨𝐨𝐩 𝐭𝐡𝐚𝐭 𝐩𝐫𝐨𝐦𝐩𝐭𝐬 𝐢𝐭 𝐟𝐨𝐫 𝐲𝐨𝐮?

This Saturday, 27 June, I am running a free 90 minute live workshop on 𝐇𝐚𝐫𝐧𝐞𝐬𝐬 𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫𝐢𝐧𝐠 and 𝐋𝐨𝐨𝐩 𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫𝐢𝐧𝐠.

We will break down:

✅ Prompt → Context → Harness → Loop
✅ Heartbeat, cron, hook, and goal loops
✅ How Claude Code and Codex run under the hood
✅ How to build an agent that finds work, does it, verifies it, and reports back

🗓️ 𝐒𝐚𝐭𝐮𝐫𝐝𝐚𝐲, 𝟐𝟕 𝐉𝐮𝐧𝐞
⏰ 𝟖:𝟎𝟎 𝐏𝐌 𝐈𝐒𝐓
⏱️ 𝟗𝟎 𝐦𝐢𝐧𝐮𝐭𝐞𝐬
💸 Free live session

Save your seat here:

fnusatvik07.github.io/harness-loop-workshop/

Comment 𝐋𝐎𝐎𝐏 if you are joining. 🔁

2 days ago | [YT] | 1

DataSense

𝗤𝘂𝗶𝗰𝗸 𝗾𝘂𝗲𝘀𝘁𝗶𝗼𝗻 𝗳𝗼𝗿 𝗲𝘃𝗲𝗿𝘆𝗼𝗻𝗲 𝗵𝗲𝗿𝗲 𝗯𝘂𝗶𝗹𝗱𝗶𝗻𝗴 𝘄𝗶𝘁𝗵 𝗔𝗜 𝗿𝗶𝗴𝗵𝘁 𝗻𝗼𝘄:

What's the ONE thing about agentic AI / LLM systems that nobody is talking about, but should be?


Drop it in comments. I'll turn the best ones into full videos.

2 months ago | [YT] | 0

DataSense

𝗪𝗲 𝗝𝘂𝘀𝘁 𝗟𝗮𝘂𝗻𝗰𝗵𝗲𝗱 - 𝗔𝗜 𝗦𝗼𝗳𝘁𝘄𝗮𝗿𝗲 𝗔𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗲 𝗠𝗮𝘀𝘁𝗲𝗿𝗰𝗹𝗮𝘀𝘀

Most people learn AI by building small demos. But 𝗿𝗲𝗮𝗹 𝗰𝗼𝗺𝗽𝗮𝗻𝗶𝗲𝘀 𝗱𝗼𝗻’𝘁 𝘀𝗵𝗶𝗽 𝗱𝗲𝗺𝗼𝘀… they ship production-grade AI systems.

Today we officially launched our new course where we teach how real AI software is designed, built, and deployed end-to-end — from idea → architecture → agents → production.

𝗛𝗲𝗿𝗲’𝘀 𝘄𝗵𝗮𝘁 𝘄𝗲 𝗰𝗼𝘃𝗲𝗿👇

🔹 How real AI applications are structured

🔹 Chatbot vs Agent vs Workflow vs Multi-Agent systems

🔹 How LLM + Tools actually work internally

🔹 Tool calling, runtime execution & API architecture

🔹 Memory, Knowledge, Action & Computation tools

🔹 FastAPI layer for exposing AI systems

🔹 CI/CD → Docker → Containers → Kubernetes flow

🔹 Scaling, Load Balancing & Self-Healing systems

🔹 How companies move from prototype → production

🔹 Real architecture thinking for production AI

This course is for AI Engineers, Developers, and Architects who want to move beyond demos and understand how real AI systems are built in industry.

If you want to build production-grade AI, not just notebooks, this is for you.

👉 𝗘𝗻𝗿𝗼𝗹𝗹 𝗵𝗲𝗿𝗲: topmate.io/datasense/page/nGXIdGuoyDmNJ2m9u0

#AI #GenAI #AIEngineering #SoftwareArchitecture #Agents #LLM #SystemDesign #MLOps #Kubernetes #DataSense

4 months ago | [YT] | 0

DataSense

𝗠𝗼𝘀𝘁 𝗥𝗔𝗚 𝘁𝘂𝘁𝗼𝗿𝗶𝗮𝗹𝘀 𝘄𝗼𝗿𝗸 𝗶𝗻 𝗱𝗲𝗺𝗼𝘀 𝗮𝗻𝗱 𝗯𝗿𝗲𝗮𝗸 𝗶𝗻 𝗽𝗿𝗼𝗱𝘂𝗰𝘁𝗶𝗼𝗻.

This workshop is about understanding why that happens and how to fix it.

𝗜𝗻 𝘁𝗵𝗶𝘀 𝗳𝗿𝗲𝗲 𝗹𝗶𝘃𝗲 𝘀𝗲𝘀𝘀𝗶𝗼𝗻, 𝘄𝗲’𝗹𝗹 𝗯𝘂𝗶𝗹𝗱 𝘆𝗼𝘂𝗿 𝗳𝗶𝗿𝘀𝘁 𝗥𝗔𝗚 𝗽𝗿𝗼𝗷𝗲𝗰𝘁 𝗲𝗻𝗱-𝘁𝗼-𝗲𝗻𝗱, then deliberately break it to understand:

1.⁠ ⁠Why toy RAG systems fail in real-world usage

2.⁠ ⁠⁠The core layers of production-grade RAG architecture

3.⁠ ⁠⁠Common issues teams face after deployment (latency, bad retrieval, cost, drift)

4.⁠ ⁠⁠What matters beyond chunking & embeddings

5.⁠ ⁠⁠How these issues are actually handled in production systems

This is not a copy-paste tutorial.

You’ll build a working RAG app first, see its limitations, and then learn how those problems are addressed in real production-grade applications.


📅 Sunday, 8 Feb | 8 AM IST

🎯 Free • Live • Limited spots



👉 𝗘𝗻𝗿𝗼𝗹𝗹 𝗵𝗲𝗿𝗲: topmate.io/datasense/page/LXPdG322V3zusdumql

4 months ago | [YT] | 0

DataSense

𝗦𝗤𝗟 𝗣𝗿𝗼𝗷𝗲𝗰𝘁 𝗪𝗼𝗿𝗸𝘀𝗵𝗼𝗽 #𝟮: 𝗦𝗻𝗮𝗽𝗰𝗵𝗮𝘁 𝗦𝘁𝗿𝗲𝗮𝗸 𝗔𝗻𝗮𝗹𝘆𝘀𝗶𝘀

Ever wondered how apps like Snapchat keep users coming back every single day?

In this hands-on workshop, we’ll reverse-engineer the streak & retention logic using advanced SQL Window Functions and build real product-level analytics.

📅 𝗦𝘂𝗻𝗱𝗮𝘆, 𝗙𝗲𝗯 𝟭 | ⏰ 𝟵 𝗔𝗠 𝗜𝗦𝗧

𝗪𝗵𝗮𝘁 𝘆𝗼𝘂’𝗹𝗹 𝗹𝗲𝗮𝗿𝗻:

• Track user streaks and activity gaps

• Predict churn using LAG/LEAD & rolling windows

• Segment users by engagement consistency

• Write interview-ready window function queries

This is not theory. You’ll build a complete retention analytics project that you can showcase in interviews.

👉 𝗥𝗲𝗴𝗶𝘀𝘁𝗲𝗿 𝗵𝗲𝗿𝗲: topmate.io/datasense/1921480

4 months ago | [YT] | 0

DataSense

𝗝𝘂𝘀𝘁 𝗟𝗮𝘂𝗻𝗰𝗵𝗲𝗱: 𝗚𝗲𝗻 𝗔𝗜 𝗣𝗿𝗼𝗷𝗲𝗰𝘁 𝟱 - 𝗔𝗴𝗲𝗻𝘁-𝗗𝗿𝗶𝘃𝗲𝗻 𝗗𝗮𝘁𝗮 𝗠𝗶𝗴𝗿𝗮𝘁𝗶𝗼𝗻

We’ve just released Gen AI Project 5, a hands-on, 𝟯-𝗵𝗼𝘂𝗿 𝗽𝗿𝗼𝗷𝗲𝗰𝘁 𝘄𝗵𝗲𝗿𝗲 𝘆𝗼𝘂 𝗯𝘂𝗶𝗹𝗱 𝗮 𝗿𝗲𝗮𝗹 𝗔𝗜-𝗮𝗴𝗲𝗻𝘁 𝗽𝗼𝘄𝗲𝗿𝗲𝗱 𝗘𝗧𝗟 𝘀𝘆𝘀𝘁𝗲𝗺 𝘁𝗵𝗮𝘁 𝗺𝗶𝗴𝗿𝗮𝘁𝗲𝘀 𝗱𝗮𝘁𝗮 𝗳𝗿𝗼𝗺 𝗦𝗻𝗼𝘄𝗳𝗹𝗮𝗸𝗲 → 𝗚𝗼𝗼𝗴𝗹𝗲 𝗖𝗹𝗼𝘂𝗱 using:

🤖 LLM Agents
⚙️ LangChain + FastAPI
🧭 Agent Orchestration
📊 Cloud-grade ETL Design
💬 Chat-based Control Panel
🔁 Automated Sync & Versioning

This is how modern data platforms are moving:
From static pipelines ➜ to autonomous, reasoning agents.

𝗣𝗲𝗿𝗳𝗲𝗰𝘁 𝗳𝗼𝗿:
Data Engineers • AI Engineers • Cloud Architects • GenAI Builders

𝗢𝘂𝘁𝗰𝗼𝗺𝗲:
You’ll walk away with a production-style Agentic ETL Platform and a strong portfolio project.

👉 𝗘𝗻𝗿𝗼𝗹𝗹 𝗵𝗲𝗿𝗲: lnkd.in/gwawsXzH

hashtag#GenAI hashtag#DataEngineering hashtag#AIProjects hashtag#AgenticAI hashtag#ETL hashtag#LangChain hashtag#FastAPI hashtag#Snowflake hashtag#GoogleCloud hashtag#DataSense

5 months ago | [YT] | 1

DataSense

𝗚𝗲𝗻𝗔𝗜 𝗶𝗻𝘁𝗲𝗿𝘃𝗶𝗲𝘄𝘀 𝗮𝗿𝗲𝗻’𝘁 𝗮𝗯𝗼𝘂𝘁 𝗺𝗲𝗺𝗼𝗿𝗶𝘇𝗶𝗻𝗴 𝘁𝗼𝗼𝗹𝘀 𝗼𝗿 𝗯𝘂𝘇𝘇𝘄𝗼𝗿𝗱𝘀.


They test how you think, design, and explain real GenAI systems.


In this workshop, we focus only on what interviewers actually evaluate.


𝗪𝗵𝗮𝘁 𝘄𝗲’𝗹𝗹 𝗰𝗼𝘃𝗲𝗿:

1.⁠ ⁠Do you really need Machine Learning before GenAI (and when you don’t)

2.⁠ ⁠⁠What GenAI interview questions actually look like

3.⁠ ⁠⁠How interviewers expect you to explain agents

4.⁠ ⁠⁠What RAG optimization really means in interviews


No theory overload. No hype. Just interview-relevant clarity.


👉 𝗥𝗲𝗴𝗶𝘀𝘁𝗲𝗿 𝗵𝗲𝗿𝗲: lnkd.in/g26j7axZ

6 months ago | [YT] | 2

DataSense

𝗚𝗲𝗻𝗔𝗜 𝗶𝗻𝘁𝗲𝗿𝘃𝗶𝗲𝘄𝘀 𝗼𝗳𝘁𝗲𝗻 𝗳𝗼𝗰𝘂𝘀 𝗼𝗻 𝗵𝗼𝘄 𝘆𝗼𝘂 𝗲𝘅𝗽𝗹𝗮𝗶𝗻 𝘀𝘆𝘀𝘁𝗲𝗺 𝗱𝗲𝗰𝗶𝘀𝗶𝗼𝗻𝘀, 𝗻𝗼𝘁 𝗷𝘂𝘀𝘁 𝘄𝗵𝗮𝘁 𝘁𝗼𝗼𝗹𝘀 𝘆𝗼𝘂’𝘃𝗲 𝘂𝘀𝗲𝗱.

I’m hosting a session on How to Crack GenAI Interviews, covering how interviewers typically evaluate:

• RAG and system design questions
• agent and tool-based workflows
• trade-offs around cost, latency, and reliability

It’s practical and interview-focused.

𝗕𝗼𝗼𝗸 𝗵𝗲𝗿𝗲: lnkd.in/gqkxKnF5

hashtag#GenAI hashtag#AIInterviews hashtag#LLM hashtag#RAG hashtag#GenAIEngineer

6 months ago | [YT] | 1

DataSense

𝗠𝗼𝘀𝘁 𝗽𝗲𝗼𝗽𝗹𝗲 𝗸𝗲𝗲𝗽 𝘄𝗮𝘁𝗰𝗵𝗶𝗻𝗴 𝘁𝘂𝘁𝗼𝗿𝗶𝗮𝗹𝘀, 𝘄𝗮𝗶𝘁𝗶𝗻𝗴 𝗳𝗼𝗿 𝘁𝗵𝗲 “𝗿𝗶𝗴𝗵𝘁 𝘁𝗶𝗺𝗲” 𝘁𝗼 𝘀𝘁𝗮𝗿𝘁 𝗯𝘂𝗶𝗹𝗱𝗶𝗻𝗴. 𝗧𝗿𝘂𝘁𝗵 𝗶𝘀 - 𝘁𝗵𝗮𝘁 𝗺𝗼𝗺𝗲𝗻𝘁 𝗻𝗲𝘃𝗲𝗿 𝗰𝗼𝗺𝗲𝘀.


So here’s your chance to build something real.

𝗝𝗼𝗶𝗻 𝗣𝗿𝗼𝗷𝗲𝗰𝘁 𝗶𝗻 𝟭𝟴𝟬 – 𝗧𝗵𝗲 𝗚𝗲𝗻𝗔𝗜 𝗕𝘂𝗶𝗹𝗱 𝗖𝗵𝗮𝗹𝗹𝗲𝗻𝗴𝗲, 𝗮 𝟯-𝗵𝗼𝘂𝗿 𝗵𝗮𝗻𝗱𝘀-𝗼𝗻 𝘀𝗽𝗿𝗶𝗻𝘁 where you’ll get a real-world problem statement, build a working GenAI project in 2 hours, and spend the last hour reviewing and improving your solution together.


Limited seats. Enrollments are open.

👉 topmate.io/datasense/1807073

7 months ago | [YT] | 3