Ketan Sahu

@Upgrade_Today keep building

@ketansahu27 Let’s go 🚀🚀

Hey founders ! Looking to connect with people building in: 🍽️ SaaS 🚀 Tech 🧠 AI tools 🤖 Automation Systems 📱 Product Development 🔥 Web Apps 📲 Devs 📸 Video editing Drop what you're working on before the week end and let's #connect with each others 👇🏻

@_PXLWorld_ Hello, Nice to see you

@ketansahu27 Full on ai builder here !! Hey 👋

@udaykirancodes Hello UdayKiran

@ketansahu27 Hello let's connect

@3bitlemon Nice to connect with you and seeing progress in your development.

@ketansahu27 hey, im on a codeintel pipeline rn (python + tree-sitter) feeding a knowledge graph from agent traces. weekend hours mostly. blr swe. followed btw, lets connect

@AKaur1570 Nice to see you.

@ketansahu27 let's connect! check this out nicheloom.com

@JoelAbenhaim Let's be connected Joel and keep building.

@ketansahu27 Hey, I work on AI dev tools. Let's connect!

@ShishiraP86746 Hello, Happy to connect with you .

@DeependraGaur15 Nice to see you solving a real problem which comes in startup life.

Biggest tension in startups right now: Founders want to move fast. Devs want clean code and work-life balance. One bad hire can kill velocity for months. Founders: What's your best hiring hack in 2026? Devs: What's a red flag you wish more founders knew? Reply and help the community 👇

@DeependraGaur15 Honest question - how many of us are using AI to build faster, or just to avoid talking to customers?

Founders & devs: AI tools let solo teams build in weeks what used to take months. But 90% of startups still fail from bad market fit or running out of cash. Question: Are you using AI to ship faster or just adding features no one asked for? What's your biggest AI win (or trap) this year? Drop it below 👇

Why Data Scientists spending 80% of their time on cleaning data 🧹 I just finished Day 1 of my learning and building AI, and the biggest takeaway is clear: "Better data > Better models." Without proper data cleaning and preprocessing, you run into: ❌ Overfitting & Underfitting ❌ Biased results ❌ Lack of trust in the model's predictions The 80/20 Rule of AI: Data scientists actually spend 80% of their time cleaning and rectifying data, and only 20% on the actual model training. My Day 1 Focus: 1. Data Cleaning: Removing errors and inconsistencies so the model can see the real patterns. 2. Preprocessing: Transforming data into the right format for training. 3. Handling Missing Values: Using strategies like deletion, imputation, and forward/backward filling to ensure accuracy. The quality of your data is directly proportional to the effectiveness of your AI. Excited to dive deeper into Day 2! #buildinpublic

@bryan_johnson My daily experience is also same.

How to avoid tons of life problems: go to bed on time.

Once again, my appeal to Indians in America on a visa. Please come home. Even if you feel it is hardship and sacrifice, self-respect should dictate your course. Let's make Bharat proud 🙏

@Ishansharma7390 Filled with CEOs, builders , news , geopolitics.

tell me your twitter feed and i'll tell you your future.

If you're doing things for passion, curiosity and impact instead of just money, then you will definitely win in life.

Let's take the examples of Homi Bhabha or Vikram Sarabhai or Abdul Kalam. They were clearly not doing it for money. Japan has had a tradition of great engineers/scientists like this. Likewise in America of old. The greatest inventions very often came from people who did not worry about making the most money. It is the recent Finance-dominated era that has reduced every motive to money. We confused Finance with "capitalism", and capitalism is really about building capital in the broadest sense of that word, which includes physical infrastructure as well as capabilities in people, as well as building trusted commerical relationships (that includes things like branding). I will say this with confidence; obsessing about money is not even the best way to make money!

@svembu Are you investing in R&D on cooling technologies for sustainable Datacenters?

We are investing in foundational technologies across the board: recently in quantum sensing, advanced materials, and soon metallurgy. I am a big proponent of metallurgy R&D in particular. Without it, we cannot build nail cutters or precision machinery or jet engines. These are not flashy billion dollar investments to make headlines, they are foundational R&D that cost millions a year, stretched out over many years. The key is to SUSTAIN them for a decade or longer. Scientists and engineers need time and rock solid support. We also don't aim for prestige, we want to first replicate know-how already there. We have also been looking to partner with small Japanese companies with critical know-how. I have two fluent Japanese speakers with me now!

A few days ago, I finally got the permission to work on my startup under my university's Startup incubation. I am building my AI startup from scratch. I will be showing all my journey online from knowing nothing about AI to learning and building an entire company.