⚡️My top 10 Youtube Channel for Stock Market

1)SOIC @soicfinance
2)PPFAS @PPFAS
3)Finnovations
4)Value educator
5)Pranjal Kamra
6)Sunil Miglani
7)Power of Stocks
8)Dr Sagar Rv
9)Vishal Khandelwal
10)ElearnMarkets @elearnmarkets

Add if I missed someone 🔥

one of the things i like about Batman is that it's fundamentally about being orphaned, and being an orphan — how this guy stays tethered to the world in his own weird, abstract, extrajudicial way when he feels that his link to it has been violently severed

Batman does this by permanently recapitulating his own trauma: solving crimes for other people, protecting them. But that's actually just the beginning; he also recapitulates his own experience of orphanness by essentially raising several orphans

Dick is an orphan in the traditional sense: dead parents. Batman sees it happen. Jason, less so: missing dad, known mom who eventually dies. Tim, even less so: parents are around a while, and involved, before both dying. Carrie, even less than that: negligent parents.

Steph: evil father, who openly works against her. And then there's Damian, whose parents are both alive and yet both have identities that totally obliterate their role as his parents. He doesn't relate to them as a mother and father; he can't, and neither can they.

In all these different cases, Batman tries all these different ways of making orphanness for them not what it was for him: Either by trying to teach them the (arguably poor) coping skills early that he learned over a very long time, or by literally legally adopting them, etc.

1/ The first 18 months of starting a company is often life or death. I must've made 5 different companies that each failed within 9 mo. 😭 Each time the company failed I figured out what I could do better. Eventually startup #6 got to $40K/mo by month 18. Here’s what I learned...

2/ Stay focused! Ignore things that are a waste of time: meetups & conferences, meetings with no clear agenda, fundraising if you're not fundraising, reading lots of tech media articles, etc. Every week should feel like significant progress in the first year.

3/ Your first 5 hires will be the difference between life or death. Choose carefully. Be picky. Many of the things we do at the company still are a result of those early hires' legacy. Have fun as a tight knit team. It will change & evolve as you get bigger so enjoy this moment.

4/ Growth may be flat for the first 9 months. It's gonna be okay. Almost every company has experienced this: Airbnb had to sell cereal in-between, Slack failed as a gaming company first, Tesla sold only 147 cars after 6 years! You probably won't be an overnight success either.

5/ In the beginning, do customer support yourself. You will learn a lot about why your product sucks. I did 5,000+ support tickets when it was the two of us. Delight customers & fix things fast while you learn. It will help you build an amazing intuition about your customers.

Most software founders, particularly in B2B, need to get radically better at sales. @Steli , who is the best person for explaining the scrappy stages in the beginning and then building out a team with scripts and processes, wrote a guide to:

For technical founders it is irrationally, obscenely hard to reverse years of programming (ba dum bum) that sales is a value-destroying activity. Sales is CLEARLY a value-creating activity, contingent on you have a value-creating product.

The world will not drop what they are doing to adopt your work. This is particularly true in B2B, where simply building a better mousetrap won't overcome the activation energy required to get people with additional non-mice problems to prioritize changing mousetraps today.

This is very non-obvious for founders because founders are not often people who *want* to be sold to. We often come from a background where trying out tools is a bit of a fun hobby. We like looking at all the options, making charts, and ripping out partially complete tests.

"This week I unsuccessfully trialed four software options for automating that thing that has been killing us. Our actual production process remains the same as last week. Don't worry; this was a great use of time." is not a thing you want to write in a progress report to manager.

1 There's a chasm between an NLP technology that works well in the research lab and something that works for applications that real people use. This was eye-opening when I started my career, and every time I talk to an NLP engineer at @textio, it continues to strike me even now.

2 Research conditions are theoretical and/or idealized. A huge problem for so-called NLP or AI startups with highly credentialed academic founders is that they bring limited knowledge of what it takes to build real products outside the lab.

3 A product is ultimately a thing that people pay for - not just cool technology or user experience. But I’m not even talking about knowledge gaps in go-to-market work. I'm talking purely technical gaps: how you go from science project to performant + delightful user experience.

4 Most commoditized NLP packages solve well-understood problems in standard ways that sacrifice either precision or performance. In a research lab, this is not usually a hard trade-off; in general, no one is using what you make, so performance is less important than precision.

5 In software, when you’re making something for real people to use, these tradeoffs are a big deal. Especially if you’re asking those people to pay for what you’ve made (can’t get away from that pesky GTM thinking). They expect quality, which includes precision AND performance.