Come Up With 500k+ User Project Ideas [Part 16] - Bias Towards Action

Talk is cheap. Action is expensive. Engineers often fall into a habit of thinking about what to do instead of actually doing anything. This lesson teaches you:

- How engineers struggle internally with their side projects, leading to nothing getting built
- Why you should just quickly build a side project idea after you have done some basic validation
- Why running a survey is one of the worst ways to validate a side project idea
- How most engineers struggle with user research (UXR)
- What book you should read if you really, really, really want to do UXR

Here's the UXR book Alex mentioned (it's one of the few books he's actually read): <https://www.momtestbook.com/>

Come Up With 500k+ User Project Ideas [Part 15] - Putting It All Together: Idea Scorecard

You now have a side project idea. How can you tell if it's good? This lesson teaches you:

- A systematic scorecard you can use to grade the quality of a side project idea
- What a bad side project idea looks like, demonstrated with concrete scorecard examples
- What a good side project idea looks like, demonstrated with concrete scorecard examples

Come Up With 500k+ User Project Ideas [Part 14] - Your Superpower: Thinking Small

As a software engineer building things on the side, there is no chance that you'll take down Google. The good news is that you don't have to in order to achieve massive career benefits with side projects. This lesson teaches you:

- The massive advantage you have over Big Tech companies when it comes to the types of products you can build
- Why taking the more humble outcome with a lower success ceiling is much better for you tactically (and statistically) when it comes to building side projects

Come Up With 500k+ User Project Ideas [Part 13] - Look For Gaps

You have found some competitors that you want to beat with your side project. Now how do you do that? This lesson teaches you:

- How adding efficiency and reducing clicks can be extremely compelling
- General basic UI/UX (user interface/user experience) improvements you can make for a product
- A simple way you can level up an application without doing anything (everybody hates ads)

Come Up With 500k+ User Project Ideas [Part 12] - Do A Search

The key towards building any successful product is to make something people want. Turns out that this actually isn't too difficult when it comes to side projects. This lesson teaches you:

- How to do a basic search to find relevant competitors and inspiration
- How to find core keywords that people use to find products in your space
- A simple, free way to understand the traffic of a website and see if it's worth building a similar webapp

You can download the Similarweb extension here: <https://www.similarweb.com/corp/extension/>

Come Up With 500k+ User Project Ideas [Part 11] - Simple Is Complex

Engineers tend to get excited for complex ideas and bored with simple ones. However, there's more to the technical realm than simply "complex" and "simple". This lesson teaches you:

- How simplicity and complexity aren't a binary spectrum
- How complexity can actually be created from simplicity if you come in with the right mentality
- Why striving for a certain level of quality always brings a meaningful degree of complexity, explained with how Alex made 60,000+ lines of code changes to grow Random Name Picker to a 1 million+ user app
- Why the "simple is complex" mentality is critical towards becoming a truly strong engineer

Come Up With 500k+ User Project Ideas [Part 10] - Keep The Stakes Low

Every piece of software inevitably breaks. This is incredibly important to remember when it comes to side projects. This lesson teaches you:

- Why side projects are especially vulnerable to production issues
- Why you want the stakes for your side project to be low
- What it means to have high stakes vs. low stakes with a product, explained with a concrete example

Come Up With 500k+ User Project Ideas [Part 9] - Single Player vs. Multiplayer

The most successful apps are those where users interact with other users - Facebook, Uber, and Airbnb are just a few. However, this model doesn't translate well to side projects. This lesson teaches you:

- The difference between a single-player product and a multi-player product
- Why multi-player products are both insanely hard to get off the ground and a recipe for disaster
- Why your side project really should be a single-player products
- The brutal chicken-and-egg problem multiplayer products must solve initially, shown with a concrete example from Alex's past

Come Up With 500k+ User Project Ideas [Part 8] - The 3 Levels Of Tech

One of the easiest and most common ways to sabotage a side project is build out an idea that's way too technically complex. This lesson teaches you:

- A 3-layer framework you can use to categorize side project ideas and their technical difficulty
- The difficulties of any level beyond Level 1 with Level 2 being incredibly hard and Level 3 being insane
- Why you should stick to Level 1 project ideas as an engineer working on side projects, especially if you're earlier-in-career

Take the code quality course here: [Level Up Your Code Quality As A Software Engineer](https://www.jointaro.com/course/level-up-your-code-quality-as-a-software-engineer/)

Come Up With 500k+ User Project Ideas [Part 7] - The Alex Formula

Repeated excellence is the key to any very successful tech career. Alex has accomplished this time and time again with around a dozen side projects that have 10,000+ users, and he's here now to spill the beans. This lesson teaches you:

- The exact playbook Alex uses to repeatedly build successful apps with several thousand users
- The "Honer vs. Innovator" philosophy when it comes to understanding engineer types
- Why you should (probably) stop trying to be Steve Jobs and go hard down the innovator route
- How honers are often incredibly underrated and can still achieve stellar career outcomes
- The ideal place to be on the honer &lt;-&gt; innovator spectrum when it comes to side projects

Come Up With 500k+ User Project Ideas [Part 6] - Your Idea Is Worthless (For Now)

While the idea behind a side project or any tech product is extremely important, ideas as a whole are usually placed on a pedestal they don't deserve. This lesson teaches you:

- Why ideas are initially worthless
- What truly makes a side project valuable (hint: it's not that much about the idea)
- Why you shouldn't build out the vision of that random MBA you just met for 0 pay and 10% equity

Come Up With 500k+ User Project Ideas [Part 5] - Tech Stack Rankings

Machine learning, web, back-end, DevOps, mobile - There are so many different tech stacks software engineers can specialize in. So how does the type of engineer you are affect your side project potential? This lesson teaches you:

- The rankings for tech stacks when it comes to side projects, starting from which one is the best suited and which ones are the worst suited
- Why mobile engineers in particular are extremely well-positioned to build impressive side projects
- The unfair advantage front-end engineers have when it comes to building side projects and getting credit
- Ideas for non-front-end engineers to build great side projects
- The pros and cons of every tech stack when it comes to side projects

Come Up With 500k+ User Project Ideas [Part 4] - Finding Inspiration

Good side project ideas don't grow on trees, but finding them actually isn't that difficult. This lesson teaches you:

- The mentality you should have with your day-to-day life to organically stumble into great software product ideas
- How frustration in general is actually a blessing in disguise, not just for side projects but for engineering in general
- Tactical ways you can improve on existing products in your life

Come Up With 500k+ User Project Ideas [Part 3] - The Key To A Great Project Idea

Most engineer resume projects are half-baked school projects or wrappers around basic tutorials, lacking the necessary continuity to be impressive and get users. This lesson teaches you:

- The #1 cause of death with engineer side projects
- The key that every good side project idea needs to even have a chance of being successful
- What it means for a side project idea to satisfy that key, explained with a concrete example showing the inspiration behind Alex's Random Name Picker app, which has over 1.1 million users

Come Up With 500k+ User Project Ideas [Part 2] - What Makes A Project Valuable

Most engineers optimize for the wrong thing when they build personal software projects, which is 99% of engineer portfolio projects don't matter at all. This lesson teaches you:

- The only metric that matters when it comes to the quality and impressiveness of your side project
- Why getting actual users supercharges the learning and growth you get from building a side project, far more than choosing the best "modern" tech stack ever could
- Common traps engineers fall into that make their side project meaningless, especially when it comes to recruiting

Come Up With 500k+ User Project Ideas [Part 1] - How This Course Works

Are the projects on your resume not helping you at all when it comes to impressing hiring managers and getting job opportunities? Let's fix that. Here are the core parts of the lesson:

- Your instructor [Alex Chiou](https://www.linkedin.com/in/alexander-chiou/) walks you through his extensive 10+ year Silicon Valley background with rapid career advancement, ending up as a high-performing tech lead making $750k at Robinhood. Most importantly, he goes through how he's built 30+ side project apps with 3 of them getting 500k+ users, getting him interviews at top companies like OpenAI, Google, Uber, Instacart, and more
- The exact definition of what a side project is and how it shouldn't be a startup
- You'll understand the many benefits of side projects and why they're almost always underrated by engineers. Side projects can do a whole lot more than getting you interviews and helping you pass them
- We walk you through the course objectives. By the end of the course, you will understand:
  - 💎 Understand what makes a side project **valuable**

  - 🫸 Avoid **common traps** that produce terrible ideas

  - ⚙️ Have a **process** to generate *feasible*, quality ideas

  - 💡 Follow a **framework** to judge a project’s quality

  - 💪 Set up the **right mentality** to build projects long-term

If you want to learn more about Alex's rocket ship career trajectory, take our overall job searching course here: [Ace Your Tech Interview And Get A Job As A Software Engineer](https://www.jointaro.com/course/ace-your-tech-interview-and-get-a-job-as-a-software-engineer/)

Paper Reading: ClickHouse - Lightning Fast Analytics for Everyone

Session led by [Dharin Shah](https://www.linkedin.com/in/dharinshah/)

Link to Paper: [**https://www.vldb.org/pvldb/vol17/p3731-schulze.pdf**](https://www.vldb.org/pvldb/vol17/p3731-schulze.pdf)

This paper presents an overview of ClickHouse, a popular opensource OLAP database designed for high-performance analytics over petabyte-scale data sets with high ingestion rates. Its storage layer combines a data format based on traditional log-structured merge (LSM) trees with novel techniques for continuous transformation (e.g. aggregation, archiving) of historical data in the background. Queries are written in a convenient SQL dialect and processed by a state-of-the-art vectorized query execution engine with optional code compilation. ClickHouse makes aggressive use of pruning techniques to avoid evaluating irrelevant data in queries. Other data management systems can be integrated at the table function, table engine, or database engine level. Real-world benchmarks demonstrate that ClickHouse is amongst the fastest analytical databases on the market.\
\
We will go into the details of why and how Clickhouse is one of the fastest OLAP database, its underlying storage engine, and the overall philosophy for performance.

Paper Reading: Llama 2: Open Foundation and Fine-Tuned Chat Models

Session led by [Mike A](https://www.linkedin.com/in/malik-mike-a-32b63818b/)

Join us for the second installment of our three-part paper reading series on the LLaMA series of Large Language Models (LLMs).

In this session, we will dive into **Llama 2**, the second iteration in the LLaMA family of models, introduced by Meta AI in mid-2023. This follow-up to the original LLaMA models brings significant advancements, offering foundational and fine-tuned versions with parameter counts ranging from 7B to 70B. Llama 2 models set new benchmarks in helpfulness and safety, showcasing impressive capabilities in dialogue-based tasks and outperforming many open-source alternatives.

We will explore the innovations behind the **Llama 2** models, focusing on their **pretraining methodology**, the **fine-tuning process** that incorporates Reinforcement Learning with Human Feedback (RLHF), and the novel techniques Meta AI used to enhance model safety and alignment. Particular emphasis will be placed on the **Llama 2-Chat models**, optimized for multi-turn conversations, along with references to their performance on real-world safety benchmarks.

This session will be an insightful discussion of how the Llama 2 models have helped to close the gap between open-source and closed-source systems like ChatGPT, examining their architecture, training data, and the steps taken to ensure responsible release and deployment. We'll highlight key takeaways from Meta AI's comprehensive evaluation of these models and discuss how they are still reshaping the landscape of open-source AI.

Whether you're a researcher, developer, or AI enthusiast, this paper reading will offer you an in-depth understanding of the **Llama 2** models and their contributions to the ongoing development of LLMs. This is a unique opportunity to review cutting-edge advancements in **LLM safety**, **dialogue optimization**, and their impact on the future of open-source AI systems.

Mark your calendars for an informative hour of "Llama 2: Open Foundation and Fine-Tuned Chat Models," as we continue to chart the progress of AI language models and explore the innovations that continue to shape the future of the field!

[https://lmarena.ai/\
https://github.com/meta-llama/llama](https://lmarena.ai/￼https://github.com/meta-llama/llama)

Paper Reading: Adaptive Radix Tree - ARTful Indexing for Main-Memory Databases

**Session Led by:[ Dharin Shah](https://www.linkedin.com/in/dharinshah/)**

**Link to Paper:[ ](https://db.in.tum.de/%5C~leis/papers/ART.pdf)[https://db.in.tum.de/\\\~leis/papers/ART.pdf](https://db.in.tum.de/~leis/papers/ART.pdf)**

This paper reading session, we will deep dive into a in-memory optimized index structure, that leverages modern CPU caches to make IOPS faster, also allowing range queries.

Abstract—Main memory capacities have grown up to a point where most databases fit into RAM. For main-memory database systems, index structure performance is a critical bottleneck. Traditional in-memory data structures like balanced binary search trees are not efficient on modern hardware, because they do not optimally utilize on-CPU caches. Hash tables, also often used for main-memory indexes, are fast but only support point queries.

What Order Should You Study Data Structures & Algorithms?

Instead of doing random problems, you need to structure your DSA prep to tackle concepts in the right order.

Course: <https://www.jointaro.com/course/crash-course-data-structures-and-algorithms-concepts/>

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