Learning Quickly Q&A and Videos

I have worked primarily on the backend, but my company now has assigned me features concerning our Android app, which is built mainly on XML for layouts & Java.

How can I get started on this, be productive & contribute effectively?
Thanks.

What does Alex Chiou read?

How does he think when he writes?

Is there a certain number of drafts?

Does he get someone to read it and give their thoughts etc?

When I read Alex's work, it makes me think better. I learn something new because I think - oh, I could also think this way. Oh, someone else can think this way. Oh, I learned something new.

Hello, I've seen the term "maintenance projects" (basically, projects where you do bug fixing most of the time) and green field projects (projects where you write code from scratch).

I've been told that the maintenance projects are generally the ones that you want to avoid since you won't learn much.

I didn't see this view against software projects on TARO, like to divide the projects in to these categories from a high level view and I was wondering if you guys can tell me more about this business view of the software projects.

Are there other categories besides maintenance and greenfield? How can I avoid maintenance ones or recognize them?

Layoffs are making me quite anxious. I understand job security might not really be a thing when it comes to big tech, but I do want to try pursuing employment security, if that makes sense. How do I "get good" so I can be a little more resilient when it comes to layoffs and employment? I'm not really sure where to start.

Hi,

I am a mid level engineer. Recently I was given a task which had a tight deadline. I started looking at the task and was stuck as the results from the code run were not as expected while testing. I was unfamiliar with this area of code so tried my best to understand the code and investigate the cause of unexpected result. I raised this with the team and also raised this as a blocker. I mentioned that I did not have confidence in going ahead with the task without understanding the cause of the unexpected results. My team was unhappy with this as the code has been working okay so far without any issues and the unexpected results were likely because of a gap in my understanding. The team assumed that I did not want to do the task whereas my hold up was not wanting to proceed without having a clear understanding of what's going on.

Should I have approached the situation differently? How to work with an unknown or hardly known area of code on a tight deadline?

I have had issues in the past with the team because of performance and other reasons. I have recently improved my performance but fear falling back to the old ways.

Thanks

Hi Taro Community,

I’ve encountered an interesting situation at my company, where I was the sole member in India until recently. In March, we hired an internal manager in India, whom I now report to. In our latest 1:1, he mentioned that I wouldn’t be assigned direct coding tasks possibly until September or October. For now, my work involves renaming elements within the codebase, and while I understand the rationale behind these changes, I’m missing out on more substantive coding work.

Given this context, I’m seeking advice on how to proactively engage with and understand our codebase. Without being assigned direct coding tasks, what are some effective ways to delve deeper into the code, learn its intricacies, and prepare myself for future assignments?

• Should I take the initiative to review and study different parts of the codebase independently?
• Could I propose small, self-initiated coding projects to demonstrate my understanding and initiative?
• How can I use this time effectively to ensure that when coding tasks are assigned, I’m fully up to speed and ready to contribute meaningfully?

Any tips or shared experiences on how to navigate this period would be highly appreciated.

Thank you for your help.

I don't have a CS degree but I am working as a junior engineer. I am currently in the process of learning software engineering concepts and building foundational knowledge of systems (haven't really gotten into it but that's my next plan).

With the whole AI frenzy going on, my attention keeps diverting from one area of focus to another. It's hard to prioritize the things that I want to learn, and I am getting quite overwhelmed. Why? Because I've 1 year of experience and as a result of this constant flip flopping, I don't think I have really gained foundational knowledge of a certain topic which is appalling.

I failed out of my computer science program at university for this exact reason - did way too many hackathons at the cost of gaining a foundational understanding of topics. I want to do things right this time and not fall for the same trap where I sacrifice becoming good foundationally.

Has anyone faced this issue before? Looking for some advice on how to manage expectations and learning to grow as a developer.

After finishing my Bachelor's Degree in Computer Science and and working as a Machine Learning Engineer for ~5 years I'm looking for something new. So far, I've been mostly focused on building software for real time systems, deployments, basic modelling, information retrieval (search) and troubleshooting "legacy" code and systems.

I'm now preparing for a new round of interviewing and I hope to make the jump to a highly paid job, possibly in the US (I'm based in Europe).

After assessing my skills and profile, I noticed that my data engineering skills are really superficial and I'm absolutely not confident in this area. E.g. I know basic SQL, but haven't build a data pipeline or ETL, I don't know hadoop etc.

Now, my question is if it would be wise to do Zach Wilson's  Boot Camp.

What I'd hope to gain from it: data engineering skills, more confidence in this area, and a higher chance of succeeding in (finding) a high paying job.

Do you think it's worth the investment, both in terms of time and money? Or do you think I should direct my focus elsewhere?

On most projects that I worked it was enough to have a high-level of how the higher picture of the code works and for the most tasks it was enough to copy paste and adapt existing code and for debugging it was also enough to have grasp the high level image.

However, I worked only on maintenance projects, that weren't very innovative. In order to have the chance to work on a good project how well should I know the tech stack?

For example for the stack: java/spring/elasticsearch/kafka/AWS, should I know the newest annotations or how the framework works under the hood, and probably be able to extend the framework, how to debug machine on VM etc?

Is there any sort of metric with respect to how in depth you should know your tech stack? Because in order to write code in a tech stack you don't need a lot of time to learn if you know the basics, but to write state of the art code I feel like you need years.

I was watching the course on "" video from the coding course

As an MLE how narrow should my focus of a tech stack be? and what constitutes as a tech stack?

99% of my work is in Python, but at 1 job I did 90% of my work in PyTorch

At my current job I'm doing 40% sklearn/keras (it's a simpler version of PyTorch implementing same things, but is mostly used for ML stuff where models need low customization) + Pandas

Rest 60% of my job needed me to start working with Polars which is pandas but faster and is more heavy weight (similar to PySpark/Dask)

Is that too much branching? or Should I be narrowing my focus?

TL;DR it's ideal to hone in on 1 tech stack, but changing circumstances need me to use different frameworks depending on the problem. Is that bad?

With a background in hardware, firmware development and validation , I was able to get a master in MLE and transition to machine learning position, but my current machine learning role doesn't focus on building and deploying model but mainly on building infrastructure for machine learning which require a tech stack different from my previous experiences and background. Due to that, my code velocity is pretty slow and I'm also worrying that if I continue with that role, my machine learning skill will fade away or I won't able to build technical depth and be very proficient at machine learning. What do you recommend?

I have been looking to switch tech stacks for a while now and although i have made progress in upskilling, its quite a slow process. Work responsibilities always take over and leaves me little time for my own learning or side projects. Also i feel like there are tons of things to learn every single time i sit down. Could you help me with some tips to go about learning and deal with overwhelm when it comes to learning in tech?

Also, another reason this is hard is because the reward I get for spending more time on office work is immediate and helps me feel safe in terms of job security, but of course in the longer run it wont keep me happy which is why i need to spend more time on my education outside of work.

Thanks!

I worked 3.5 years on the backend for a large applications with the stack of java, spring, hibernate and mysql + bunch of internal frameworks. Now I switched to another company and for 3 years I worked on the backend for another large applications (thousands of users) but with multiple languages. There were microservices in python, go, java and C++. I was also required to write some react code. While I was able to hack around (not the top notch code) and ship things that work, I was wondering if this kind of experience will damage my profile in the job market, since everyone wants someone that is specialized.

Hi Taro Community,

I’m a recent addition to my company and have embarked on my journey with a few initial tickets, completing 3 PRs in the span of 2.5 weeks. Alongside these tasks, I’ve been provided with architectural and design documents to help me grasp the broader system. However, these documents are quite high-level and, at times, challenging to comprehend fully, especially without knowing which sections are most pertinent to my current work.

Given the breadth of information and my eagerness to effectively contribute, I’m contemplating the best approach to balance my tasks with learning. Here are a few points I’m considering and would love your insights on:

1. Targeted Learning from Documents: Should I consult with my mentor on which specific parts of the document would be most beneficial for me to focus on initially, considering my current assignments?
2. Codebase Familiarization: How should I approach diving into the codebase? Is it advisable to ask my mentor for guidance on specific modules or areas that align with my tickets or overall team objectives?
3. Balancing Tasks and Learning: What strategies have you found effective for simultaneously working on assigned tickets, understanding high-level documentation, and becoming familiar with the codebase? Is there a recommended balance or sequence that could optimize my ramp-up process?

Navigating the initial phase and ensuring I’m building a solid foundation is my top priority. Any experiences, strategies, or advice you can share on managing these early stages of onboarding would be greatly appreciated.

Thank you for your support and guidance.

How can I map out what to do in the first 90 days in a new role (staff and senior staff) and a new job (given factors like new codebase, new processes, people, and work ethics), especially when the domain and coding language are also new?

Does working in different area - infra, developer experience, product, backend, frontend over the career period hurt in terms of becoming/staying a staff engineer or manager?

Everyone has heard of the 80/20 rule. I was wondering as an intern / junior engineer, what are the few things that I need to do that will give me the most impact on my career prospects?

I'm working on my side project. A web app.

I know a little of html and css just the basics but now I want to extend my app and make it more visually attractive and I noticed I went to Udemy to look for Modern CSS course etc.

It will take me 20+ hours just to know what to do plus the time I take doing the work.

This approach is not working for me and not gonna finish the project by the deadline I set myself.

What are your thoughts? How you learn something while applying it at the same time?