Ace Your Tech Interview As A Software Engineer [Part 14] - Referrals

Having a current employee put you into their hiring pipeline via a referral is one of the most powerful ways to level up your job search. However, referrals are often misunderstood by software engineers. This lesson teaches you:

- The 2 different types of referrals and which one is better (spoiler: engineers usually struggle getting the better one)
- The massive difference between *weak referrals* and *strong referrals*
- Why you are more special than you realize and how you can leverage that to get more strong referrals
- How to approach professional networking properly to cultivate huge amounts of strong referrals over time

To help you get strong referrals, check out our networking course: [Networking Guide: Build Deep Relationships Quickly In Tech](https://www.jointaro.com/course/networking-guide-build-deep-relationships-quickly-in-tech/)

Ace Your Tech Interview As A Software Engineer [Part 13] - Cold Messages

You're applying to tons of software engineer jobs, and it's not working out. In your desperation, you come up with a genius idea: You'll reach out to company employees directly with a cold message. That'll work right? Guess again. This lesson teaches you:

- Why cold messaging isn't as effective as software engineers think
- How a reliance on cold messages often mask a deeper personal problem for the engineer
- The necessary conditions for a cold message to have a high likelihood of working
- Why cold messages are far more effective with startups and near useless for Big Tech
- How to write an excellent cold message, demonstrated by a thorough example of a bad cold message vs. a good cold message

Ace Your Tech Interview As A Software Engineer [Part 12] - Job “Requirements”

We've all seen the insane "entry-level" job postings that require 3-5 years of experience. This lesson teaches you:

- Why job postings are so ridiculous (hint: it's how capitalism works)
- How treating job requirements as a wish list feeds into the overall strategy of quantity &gt; quality
- The amount of requirements met that you need to justify applying for a job

Ace Your Tech Interview As A Software Engineer [Part 11] - Struggling? Send More Applications

One of the most common reasons for a struggling software engineer job search is that they simply aren't applying enough. The good news is that this can be easily fixed with the proper behavior adjustments. This lesson teaches you:

- How you can conquer the job search with sheer math
- A healthy conversion rate for application -&gt; interview chance
- Why you should almost never spend too much time on any individual application (quantity &gt; quality)
- The framework to follow on whether you should apply a ton or apply more selectively

Here are the Big 2 job searching websites:

- <https://www.linkedin.com/jobs/>
- <https://wellfound.com/>

On top of the Big 2, we've seen engineers have success with:

- <https://otta.com/>
- <https://www.workatastartup.com/> - Jobs at Y Combinator startups specifically, the greatest incubator in the world which is behind Stripe, DoorDash, Airbnb, and many more FAANG-adjacent companies

Ace Your Tech Interview As A Software Engineer [Part 10] - Order Matters

We all want to speed run our way into FAANG. The bad news is that this is almost never pans out for software engineers, and aggressively pursuing this strategy can easily lead to your downfall. This lesson teaches you:

- The true way to actually get better at interviewing and why it can't be avoided (no matter how painful it is)
- How to properly structure your job search when Big Tech is one of your goals
- The general approach you should take when it comes to applying to jobs and sequencing your interviews

Ace Your Tech Interview As A Software Engineer [Part 9] - Polish Your Resume

Your resume is the most important professional document in your life. However, a lot of software engineers are severely lacking in this department. This lesson teaches you:

- The perspective of the often underappreciated tech recruiter and why they automatically reject the overwhelming majority of resumes, especially if they work for a top company like Big Tech
- How to write a resume that recruiters won't hate and instantly throw in the trash, leveraging that empathetic mentality from before
- The steep, underestimated cost of basic resume mistakes, which are incredibly common among immigrant engineers where English isn't their first language
- Why you should make just 1 focused resume instead of several, especially if you're earlier-in-career
- How recruiters hyper-efficiently read resumes (spoilers: they often don't read the entire thing)

13 minutes isn't nearly enough to fully understand all the mechanics of a good resume, so you should dive deeper here: [\[Masterclass\] How To Write A Stellar Tech Resume That Gets You More Job Opportunities](https://www.jointaro.com/lesson/OnQV2V3J8DYVBBuGbZx6/masterclass-how-to-write-a-stellar-tech-resume-that-gets-you-more-job-opportunities/?playlistId=PJqfgn35DG82NSm3QyfT)

Ace Your Tech Interview As A Software Engineer [Part 8] - Interviewing While Employed

Finding a job as a software engineer is, in and of itself, practically a full-time job. But should you quit to actually treat it like an entire job? This video teaches you:

- Why currently being employed is usually the best time to find a new job
- The counterintuitive way that having a job boosts your interview performance when searching for another job
- How to find the time to do interview preparation when you're juggling a current job, including emergency levers
- The framework you should apply to determine if you should quit your current job for the job search grind

Ace Your Tech Interview As A Software Engineer [Part 7] - Stronger Together

The software engineer job search is extremely exhausting. We now know that grit is the most important trait for interview success, but it's hard getting there purely on your own. This lesson teaches you:

- The big difference between knowing something and applying something
- Why finding an accountability partner is crucial for learning and making genuine progress
- A very basic (but powerful) framework you can go through with your accountability partner to push one another to greater and greater heights on a consistent basis

Ace Your Tech Interview As A Software Engineer [Part 6] - Having The Right Mentality

A lot of software engineers actually have all the necessary skills to pass the interview - They just choke when the time finally comes. Why is that? Well, let's dive into why. This video teaches you:

- The terrible unhealthy mentality software engineers often have going into tough tech interviews, particularly with top companies like FAANG
- What mentality you should have instead to unlock your full potential and why it's hard to ascend to this level of mental clarity
- How having the right mentality greatly improves your interview performance, far more than any amount of preparation ever can

Ace Your Tech Interview As A Software Engineer [Part 5] - Dynamic State vs. Prepared State

The overwhelming majority of software engineers went to college and grew up in a very academically-inclined environment. Bringing the mentality cultivated from that experience to the job search often unfortunately has bad consequences. This lesson teaches you:

- Why traditional learning methods don't translate well to software engineering
- The difference between *prepared state* (how you grew up learning) and *dynamic state* (how you should actually learn)
- A defining trait of the most successful interviewers, which most candidates don't have
- How to train yourself properly when it comes to your interview preparation and overall learning

Ace Your Tech Interview As A Software Engineer [Part 4] - The #1 Trait For Interview Success

Software engineers overwhelmingly blame the wrong thing when it comes to why they aren't landing job offers, particularly their own lack of skill. This lesson teaches you:

- What the actual #1 trait among successful job searchers is
- How to build up your personal grit
- Why most software engineers have the wrong perspective post-interview and are unable to fully learn from their failures
- The success metric you should be weighing yourself against as you progress through the job search, viewing everything as more of a spectrum instead of a binary state

To go deeper into developing your grit and boosting your productivity, watch this video: [2 Ways To 100x Your Productivity That Nobody Does](https://www.jointaro.com/lesson/RXEca9zfyZG0pl015att/2-ways-to-100x-your-productivity-that-nobody-does/?playlistId=JNCZ1vbRF3NwsOQCqblt)

Ace Your Tech Interview As A Software Engineer [Part 3] - Interviewing: Why It Sucks

A lot of software engineers don't really know what happens on the other side (i.e. the interviewer giving you the questions), especially for top companies like FAANG. This lesson teaches you:

- Why interview processes are much messier than job candidates expect
- Why tech interviews are inherently unpredictable and random
- How incredibly hard it is to create a quality interview process that both only lets in good talent while not being too torturous for the candidates
- Why it's near impossible for this dark reality of terrible interviewers and interview processes to ever change

If you want to dive even deeper into the interviewer's perspective, check this out: [\[Masterclass\] How To Be An Amazing Interviewer In Tech](https://www.jointaro.com/lesson/OYKgGZ7syfymlvIJKzuf/masterclass-how-to-be-an-amazing-interviewer-in-tech/)

Ace Your Tech Interview As A Software Engineer [Part 2] - Organizing Your Job Search

A lot of software engineers struggle on the job search because they're just randomly flailing around, drifting from interview failure to interview failure without learning from the overall process. This lesson teaches you:

- The surprisingly basic master plan every successful job search must follow
- How to fix a job search where you are failing to get interviews to begin with
- Actions you can take when you are failing to pass interviews
- What a healthy time spent looks like depending on whether you are trying to *get* interviews vs. trying to *pass* interviews
- How you can organize your job search and turn it into a well-oiled machine where you are constantly overcoming obstacles and improving

Ace Your Tech Interview As A Software Engineer [Part 1] - How This Course Works

Let's not mince words: Looking for a job as a software engineer is *brutal*. It is so easy to lose heart on the journey and stop believing in yourself. This video (and broader course) will solve that for you by giving you the tools to overcome any job search adversity and stand out from the hordes of other candidates. 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 across top companies like PayPal, Course Hero, Meta, and Robinhood, explaining how he increased his TC (total compensation) by a whopping +800% across just 7 years and led thousands of engineers to interview success at top companies like Meta, Google, and Amazon.
- You'll understand why the existing landscape about interview preparation resources fails software engineers so miserably, particularly when it comes to data structures and algorithms (DSA) and LeetCode.
- We walk you through the course objectives. By the end of the course, you will understand how to organize your job search, learn interview skills properly, get job opportunities effectively, follow a framework to come prepared into any interview, and understand all the common software engineer interview round types.

If you want to learn how Alex cracked the FAANG interview, you can check out his story here: [How Alex Got Into Meta With 0 Prior LeetCode Experience](https://www.jointaro.com/lesson/ZYiTbN21FsqFxFdpwt5a/how-alex-got-into-meta-with-0-prior-leetcode-experience/)

Taro Book Club - The Fundamentals of Data Engineering - Chapter 3: Designing Good Data Architecture

Discussion led by [Gideon Blinick](https://www.linkedin.com/in/gideonblinick/)\
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In this session, we'll discuss Chapter 3 (Designing Good Data Architecture) of [**"The Fundamentals Of Data Engineering"**](https://drive.google.com/file/d/1ZM6Wf-uyFjO5TXFGF8vIaVKi4XEhAeYf/view?usp=drive_link).

How do you do good Data Architecture? Wouldn’t it be great if there were principles you could follow? Well, there are! Google has 5 in their Principles for Cloud-Native Architecture. Amazon has 6 in their AWS Well-Architected Framework. But I’m here to tell you that there are 9.

This is a great chapter for those interested in System Design!

Check out #taro-bookclub in the [**Taro Premium**](https://www.jointaro.com/membership/) Slack for more details.\
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Event link: <https://www.jointaro.com/event/taro-book-club-the-fundamentals-of-data-engineering-chapter-3-designing-good-data-architecture/>

Taro Book Club: Designing Data Intensive Applications - Chapter 1

Discussion led by: [**Ankur Agrawal**](https://www.linkedin.com/in/erankuragr/) & [**Raj Shah**](https://www.linkedin.com/in/therajshah/)\
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In this #taro-bookclub discussion, we'll go over Chapter 1 of the book [**"Designing Data-Intensive Applications"**](https://www.amazon.com/Designing-Data-Intensive-Applications-Reliable-Maintainable/dp/1449373321) by Martin Kleppmann. This chapter is about Reliable, Scalable, and Maintainable Applications and will provide good mental models to think about reliability, scalability and maintainability of Distributed Data Systems.

Here's the agenda:

- We’ll break down and discuss the key concepts from Chapter 1.
- There will also be time for any questions and answers you might have.

Get ready for our first session on this engaging and informative book!

We hope to see you for Chapter 2 as well: [**Taro Book Club: Designing Data Intensive Applications - Chapter 2 (Data Models and Query Languages)**](https://www.jointaro.com/event/taro-book-club-designing-data-intensive-applications-chapter-2-data-models-and-query-languages/)

If you don't have a Taro Premium membership, you can get it at a discount with Ankur's special link here: [**https://www.jointaro.com/r/eventu507/**](https://www.jointaro.com/r/eventu507/)

Becoming A Staff Engineer In Big Tech (Panel Discussion)

The journey to Staff Engineer is unique for everybody. Let’s talk about all the ways we got there! Senior Engineer is a terminal level at most tech companies.

Staff Engineer is the next level up. This is referred to as Staff at Meta/Google, or Principal Engineer at Amazon/Microsoft. ([Rahul's promotion story](https://www.jointaro.com/lesson/qvp2quodqAEWSkN7sayt/case-study-building-a-meta-internal-tool-to-empower-an-entire-org-staff-promotion-story/).)

Partial list of questions discussed:

- How do you know which problems are worth solving?
- How do you communicate to your manager that you want Staff promo? And what do you look for in a manager?
- What type of teams do you think best support growth into the Staff level?

Panelists:

- [**Zach Wilson** - Airbnb](https://www.linkedin.com/in/eczachly/)
- [**Rahul Pandey - Meta**](https://www.linkedin.com/in/rpandey1234/)
- [**Carly Taylor - Activision**](https://www.linkedin.com/in/carly-taylor-data/)
- [**Lee McKeeman - Google**](https://www.linkedin.com/in/lmckeeman/)
- [**Ryan Peterman - Meta**](https://www.linkedin.com/in/ryanlpeterman/)

See discussions about Staff Engineers on Taro: <https://www.jointaro.com/topic/staff-engineer/>

Watch the full [Senior to Staff course on Taro](https://www.jointaro.com/lesson/NE3J4vWP7BoWlNgbRtCw/becoming-a-staff-engineer-in-big-tech-panel-discussion/).

Paper Reading: Refactoring vs Refuctoring: Advancing the state of AI-automated code improvements

Paper Discussion led by [Adi Pratheek](https://www.linkedin.com/in/pratheekadi/)

"**Refactoring vs Refuctoring**" is the conclusion of a benchmark study of the most popular Large Language Models (LLMs) and their ability to generate code for refactoring tasks. This paper aims to illustrate the current standards and limitations, and seek to show new methodologies with higher confidence results.

**What's in store?**

In this paper reading session, we will be examining:

- The performance of the most popular Large Language Models (LLMs) on code refactoring
- How does an AI err?
- A novel innovation by CodeScene for fact-checking the AI-output and augmenting the proposed refactorings by measuring the confidence levels

Companies build pretty substantial codebases over a period of time (sometimes decades). As and when the companies grow, a significant amount of time and energy are constantly invested by development teams on code refactoring (also covered in this paper).

But, how well do the existing AI tools/models actually perform this task? Are we there yet to confidently say "**AI will replace software developers**"? Join this session where we dive deep into the paper to find more answers.

Link to the paper: [**Refactoring vs Refuctoring: Advancing the state of AI automated code improvements**](https://codescene.com/hubfs/whitepapers/Refactoring-vs-Refuctoring-Advancing-the-state-of-AI-automated-code-improvements.pdf)\
Event Link: <https://www.jointaro.com/event/paper-reading-refactoring-vs-refuctoring-advancing-the-state-of-ai-automated-code-improvements/>

Paper Reading: AlphaGeometry: Advancing Automated Reasoning in Olympiad-Level Geometry

Paper Discussion led by [Lucia Mocz](https://www.linkedin.com/in/lucia-mocz-ph-d-35a98a1b6/)

Solving mathematical problems at the Olympiad level is incredibly difficult, requiring advanced problem-solving skills, a deep understanding of mathematical principles, and the ability to think critically and creatively under pressure. Those who excel in Olympiad-level problem solving usually have exceptional talent, undergo extensive preparation, and possess a unique problem-solving mindset. Achieving human-level automated reasoning in mathematical theorem proving, especially when competing with top performers, is a significant milestone in artificial intelligence research.

In this paper reading session, we introduce AlphaGeometry, a groundbreaking theorem prover tailored for Euclidean plane geometry. Unlike traditional methods that rely on human demonstrations, AlphaGeometry autonomously synthesizes millions of theorems and proofs across various complexities without human intervention. By combining a neural language model trained on vast synthetic data with a symbolic deduction engine, AlphaGeometry employs a neuro-symbolic approach to navigate intricate problem spaces. Notably, AlphaGeometry generates human-readable proofs and has successfully tackled challenging problems from previous International Mathematical Olympiads, even discovering new generalizations of established theorems.

Whether you're an AI researcher, engineer, or simply curious about this achievement in AI research, join us as we explore the intricacies of AlphaGeometry and its potential implications for automated reasoning in mathematics.\
\
Paper: [**https://www.nature.com/articles/s41586-023-06747-5**](https://www.nature.com/articles/s41586-023-06747-5)\
Event Link: <https://www.jointaro.com/event/paper-reading-alphageometry-advancing-automated-reasoning-in-olympiad-level-geometry/>

Blog: [**https://deepmind.google/discover/blog/alphageometry-an-olympiad-level-ai-system-for-geometry/**](https://deepmind.google/discover/blog/alphageometry-an-olympiad-level-ai-system-for-geometry/)

GitHub: [**https://github.com/google-deepmind/alphageometry**](https://github.com/google-deepmind/alphageometry)

Paper Reading Session: Simple Testing Can Prevent Most Critical Failures

Paper Discussion led by [Sudhi Awasthi](https://www.linkedin.com/in/sudhiawasthi/)

In this session, we will be discussing this paper titled "[Simple Testing Can Prevent Most Critical Failures: An Analysis of Production Failures in Distributed Data-Intensive Systems](https://www.usenix.org/system/files/conference/osdi14/osdi14-paper-yuan.pdf)".

Large, production quality distributed systems still fail periodically, and do so sometimes catastrophically, where most or all users experience an outage or data loss. This paper presents the result of a comprehensive study investigating 198 randomly selected, user-reported failures that occurred on Cassandra, HBase, Hadoop Distributed File System (HDFS), Hadoop MapReduce, and Redis, with the goal of understanding how one or multiple faults eventually evolve into a user-visible failure and how simple testing can prevent majority of them.\
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Event Link: <https://www.jointaro.com/event/paper-reading-session-simple-testing-can-prevent-most-critical-failures/>

Tech Career Growth Videos

Our instructional videos provide software engineers with insights needed for career growth. Masterclasses go incredibly in-depth on a specific tech topic while case studies are real examples from established engineering leaders.