Hustle Hub #34

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Hey hustler,

How are you doing? Last weekend I attended one of my best friend’s wedding in a very warm and cosy environment. It’s always a blessing to see people come together to celebrate love! 💜

In today's issue, I’d like to share with you how to negotiate a higher salary (after you get a job offer), focus on one highlight of the day, how to do great work (by Paul Graham), and build LLM applications with LangChain.

Let’s get to it! 🚀 

🛖 What's in the hub today?

• Tip: How to negotiate a higher salary (after you get a job offer)

• Mistake: I set unrealistic goals for the day

• Learning: Focus on one highlight of the day

• Article: How to do great work

• Tool: Building LLM applications with LangChain

⭐️ 1 Tip

How To Negotiate A Higher Salary (After You Get A Job Offer)

When I was at Micron, my salary was around $4,000. After I moved to Hackwagon as a data science instructor, my salary was $7,000 (almost doubled my original salary 🤯).

So how did I increase my salary by 75%? The answer is by negotiating a higher salary after I got the job offer. And I want to share with you how you can do the same so you won’t leave money on the table. 💰

Okay, I get it. You’re not comfortable asking for more money once you have an offer in front of you. You don’t want to screw things up, so you just want to take whatever is given to you.

🤝🏻 Explain why you think you deserve more

Don’t just counter with a higher number. Instead, highlight your strengths and the value that you can bring to the table. If possible, try to back this up with your past experiences. Quantify the potential ROI that you can bring to the company.

By doing this, you’ll build a strong case for why you deserve a higher salary compared to the initial offer.

🤝🏻 Prepare and practise for negotiation

Before you go for negotiation, it’s always a good idea to prepare a script and practise by rehearsing the negotiation flow with your friends.

Why? Because this will make you sound (or look) more confident when negotiating with recruiters/employers.

Many salary negotiations failed because candidates didn’t even believe in their strengths and values that they could bring to the table. So they lacked confidence during the negotiation, causing recruiters/employers to think they might be hiding something.

🤝🏻 Create a sense of urgency

Salary negotiation is a sales process. You are the seller who sells your skills and experience, and recruiters/employers are the buyers who buy your skills and time. If they see other buyers are interested in hiring you, you have better control of the situation.

In possible, try to have multiple job offers on the table around the same time when you’re negotiating salary with a company. This will create a sense of urgency for the company to increase the salary package to compete with others (if they think you’re good and they want you).

In summary, here are the 3 tips to negotiate a higher salary after you get a job offer:

• Explain why you deserve more

• Prepare and practise for negotiation

• Create a sense of urgency

⚠️ 1 Mistake

I tend to set unrealistic goals for the day. For example, on one day in my calendar, I could have multiple big tasks to achieve several goals in one day.

When I couldn’t complete all the tasks, I felt frustrated, thinking that I wasn’t productive enough. Even though I did complete 1-2 big tasks, I didn’t celebrate those small wins, making me even more unproductive in the following days because of the piled-up tasks.

Not good for productivity and mental health. 🙅🏻‍♂️

🧠 1 Learning

One day, I chanced upon a YouTube video by Ali Abdaal where he shared about his favourite productivity book called “Make Time”.

Honestly speaking, it has been a game changer to improve my productivity after watching his video and reading the book.

🧠 Here’s what I’ve learned:

• Every day, focus on one highlight of the day ⭐️

• A highlight is a task that gives you a sense of accomplishment and fulfilment after you have completed it by the end of the day

• Here’s how I use this framework:

  • Every night before I sleep, I’ll plan what I want to focus on the next day as the highlight of the day.

  • The highlight must be something that once I’ve completed the task, I’ll feel accomplished and fulfilled — that today is a day well spent.

📚️ 1 Article

How To Do Great Work (Paul Graham)

If you ever worked at a startup (or if you’re building a startup), chances are you might have already heard of the legendary story of Paul Graham.

He is a programmer, writer and investor who also co-founded Y Combinator — the world’s leading startup incubator that funded Airbnb, Stripe, Coinbase etc.

Paul Graham often publishes essays on his blog to share his thought about building a startup and living a purposeful life. Recently he wrote a new essay — How To Do Great Work.

It blew my mind and I just thought of sharing my learning with you here. The essay is quite long (took me 30+ mins to finish reading 😂), so here’s my takeaway.

📚️ Here are my takeaways from the book:

• There are 2 elements for you to do great work:

  • Passion — Do what you find interesting and exciting

  • Skill — Do what you’re good at

• How do you know what you’re passionate about and good at?

  • You’ll only know by trying and doing things.

  • For that to happen, you have to be curious about things.

• In short, curiosity leads to passion and skill.

  • When you’re passionately doing something you’re good at, you’ll obsessed. And obsession is the way to do great work.

🧰 1 Tool

LangChain is an open-source development framework for LLM applications. It was released in October 2022 in Python and it went viral ever since. And there’s a reason for that.

Many developers are using LangChain in their LLM applications because it provides:

• Modular components — You can build multiple chains to feed the output of one chain as the input to another chain. Besides, you can use agents to route your prompts to the right chain to make decisions.

• Data connection — You can connect to various data sources (CSV, databases, Notion etc) to run your prompts.

Because of these functionalities, LangChain basically opens up a whole new ecosystem for developers like us to build LLM applications for different use cases.

LangChain is also the framework that I’m using to build an AI platform to help SMEs analyse data by just asking questions.

🔥 Hustler Spotlight 🔥

👋🏻 How would you introduce yourself?‍

‍I’m Dat, co-founder and CTO of priceloop which is a no-code AI pricing solution for Amazon sellers and Enterprises. Before I co-founded priceloop, I was leading the AI efforts at Axel Springer, a large media publishing house where my team worked on text-to-speech and NLP topics. My interests are diverse from traditional machine learning, deep learning, AI in general to engineering topics. I have a lot of experiences from devising realistic data-driven use cases to the actual implementation into a real product; more than capable of distinguishing hype, buzzwords and wannabes from substance. I’m a big fan of agile practices, lean product development and open-source technologies. In fact, my team open-sourced several projects like imagededup or image super resolution. I also regularly blog about my work on Medium and also speak at conferences.

👀 What’s your day to day like in your current role as a CTO & Co-Founder at Priceloop?

‍‍My day to day is quite diverse as I wear different hats at Priceloop. Moreover, since the company is still young and small I’m still able to code. So on one day it can happen that I’m implementing new features or fixing bugs. On another day, I work on management tasks i.e. doing performance reviews or also creating investor presentations. It never gets boring!

⭐️ What has been the biggest highlight of your career so far?

‍There are many “biggest” highlights in my career so far but if I have to name one it would probably be a project that I managed at idealo.de. At this time, we had a huge revenue goal to achieve with CRM. At the beginning of the year it didn’t seem that this was possible but with the help of my team we turned it around. With a little bit of data engineering and also simple ML models we could automate CRM processes which resulted in EUR 1 million additional revenue in the 1st year. In the 2nd year, we already reached EUR 2 million. So this was really a nice feeling to achieve this goal.

🚀 What's a data or AI trend you're watching this year?

‍I have two trends that I’m excited about. First one is stable diffusion models, a deep generative model released already last year. I’m pretty excited where it will be applied this year and how it can be used to generate all these cool images. The second trend is all these new cool language models such as GPT-4 which powers solutions like ChatGPT. Pretty excited to see all the use cases that you can solve with it.

💼 What advice would you give someone starting out in Data Science?

Giving advice is always challenging for people in this field. There is the same generic advice that I would probably give to anyone, but it also depends on luck at the end of the day.

What I saw as a good pattern was doing capstone projects: doing projects in machine learning to learn how things work. Then, if you really want to go into this field, either you're lucky (meaning you are in a corporation which already has machine learning teams and you can ask for a transfer to that department), or you could do an internship where you can showcase that you have the skills and can build your practical experience.

Those are the two options for people to grow into this field. What I’ve observed so far, which is very challenging, is people doing paid courses and then trying to get into the field. It’s very challenging because in the data science/machine learning world. It’s very competitive. Everyone is looking for senior people and not juniors. But everyone who wants to get into the field are juniors, and that's why it's very challenging to do these courses and apply for companies. It is very difficult to get a job with that approach.

🤯 What’s the most important career lesson you wish you’d learned earlier?

My most important career lesson that I wish I would learn earlier is that money isn’t everything. When I finished my undergraduate studies, I was about to enter a career into investment banking. I did several internships in this field but hated it. Money was good but I realized after five internships that this is not everything. So it took me a while to understand this.

🧠 How would you learn Data Science if you had to start over?

Simple answer. I would always start with Andrew Ng’s Machine Learning course. It was and I believe is still one of the best introductory courses for machine learning.

🔥 Where can we find your amazing work?

On Medium and Github:

• https://github.com/datitran

• https://medium.com/@datitran

📚 What's your favorite book?

I have many “favorite” books but if I have to name one then it is Freakonomics by Steven D. Levitt and Stephen J. Dubner. It’s an amazing book that applies economic theory on diverse topics that are quite unusual e.g. drug dealing. So if you haven’t read it then you should grab a copy of it.

🚀 Whenever you’re ready, there are 4 ways I can help you:

1. Book a coaching call with me if you need help in the following:

2. Promote your brand to 1,000+ subscribers in the data/tech space by sponsoring this newsletter.

3. Watch my YouTube videos where I talk about data science tips, programming, and my tech life (P.S. Don’t forget to like and subscribe 💜).

4. Follow me on LinkedIn and Twitter for more data science career insights, my mistakes and lessons learned from building a startup.

That's all for today

Thanks for reading. I hope you enjoyed today's issue. More than that, I hope it has helped you in some ways and brought you some peace of mind.

You can always write to me by simply replying to this newsletter and we can chat.

See you again next week.

- Admond