Monthly Recap - 2026-01 January

January is always a month for planning. This year, I have a really ambitious roadmap, with several times more goals than I take on average. It will be challenging to meet them, but I am very excited about the prospect of having a more active year!

Achievements

Started AI Projects

One of my goals this year is to start leveraging AI more widely in my work. While I have been studying it and building some projects around generative AI tools, I want to incorporate it more in my everyday activities.

Not only I plan to use AI to get more work done, I am also determined to create a lot more systems that use AI creatively. I do not want to share the details yet, but I will surely write about them as the year goes. I already started with some, and the results have been very inspiring!

Released JenAI v1.8.0

I have been building JenAI since 2024, and despite its simplicity it is still a tool that is very much present in my routine. This month, I released a new version (v1.8.0) adding database support for both Postgres and SQLite. JenAI always had an emphasis on local environments, and one aspect of this was its usage of the filesystem as the only persistence option - while I remain fully commited to keep it local-only, supporting the usage of a database (which still has to be local, anyway) allows for more easily integrating complex features, such as AI-initiated chats and embedding JenAI as the underlying engine for a broader AI system (a future project of mine).

Downpoints

Personal studies lacking

Having difficulties to find time for personal studies was a recurrent theme last year - unfortunately this year started in a similar way. I am not too concerned about this, because I had very good reasons to divert my time to other projects and I have a strong plan on how to get back to this soon, but it still was a negative aspect of the month.

Plans for next month

More AI Engineering studies

Last year I started studying AI Engineering books alongside the classic career and hobby studies I do. This did not end well, as I was overwhelmed with tasks and almost never got the time to do them all. So for February I plan to retake these studies, and come up with a better plan on how to address all the needs in a healthy and sustainable manner.

Year In Review - 2025

2025 was a very busy year, marked by constant changes and several ups-and-downs. While I have been writing monthly recap blog posts for quite some time now, my plans to write an yearly review were left behind last year - I intented the first one to be about 2024, but only now I am able to catch up and write a first attempt at summarizing the year. I will try to be consistent with this, and follow up with one for 2026, 2027, and so on.

Highlights

I will not go deep into the details of each achievement, as that would lead to a very long post and the content would likely be redundant with other posts I did during the year. So, I will just arpeggiate them with a brief description.

Here were the main highlights of the year for me, grouped by their relevant categories:

Personal studies

As a direct consequence of participating in several technical book clubs at work, I took on a personal habit of picking books to study by myself, with the same level of attention that I give when attending a book club. I have been doing this since 2021 (so about four and a half years by now), and it has been an amazing source of personal growth for me. I aim to put around 30 minutes every working day in studying either a career-related book, or a hobby-related book.

This year, however, I was very inconsistent with how much time I was able to put into this. A mixture of going back to working on-site most days of the week, applying and moving to a new team inside my company and buying and moving into a new home meant that I was most often not doing these studies than doing them. Nevertheless, I was still able to go through a few books, here they are:

Studied The Captain Class

Great book about leadership, I started it in late December of 2024 and was able to finish early this year. I saw a lot of the Scrum Master role reflected in the Captain role that the book talks about, and was able to take several lessons about how I could be a more effective Scrum Master. I read this as part of career studies.

Studied Building Successful Communities of Practice

Short but useful book, which I picked up because I wanted to start some groups inside my old team as a forum for bringing improvements to what is a very, very old and static mindset. I ended up getting a position in a different team before I was able to stablish too many things, but I did set up a Code Quality forum that as far as I know is still going strong, so it served its purpose. I read this as part of career studies.

Studied The Prompt Report

Paper about prompt engineering, useful because I have been steadily trying to get more involved with AI Engineering these past few years (yes, before the crazy push we have right now for everyone to become an AI Engineer). I read this as part of career studies.

Started studying Fundamentals Of Software Architecture

Longer book which is an introductory-level presentation of Software Architecture as a field, with its responsibilities, history and peculiarities. I started it roughly in the middle of the year, but was not able to finish yet. So far it has been interesting, although nothing ground-breaking and seems pretty biased at times. I read this as part of career studies.

Started studying Rich Dad Poor Dad

The only hobby studies book I picked this year. I started reading it around August, and wasn't able to finish within the year. However, that should count in favor of the book, because it led me to start investing for the first time, and for several months all my personal time was spent in studying about different types of investment and structuring my finances. This book was really life-changing for me. While I have read several criticism of the book, and I do not agree with everything said in it (in fact, my personal interests and investment profile is very different than that of the author, and I would never want to make the same investments that he does), I still found the content very inspiring and educational. You do not need to blindly follow everything a book says to get value out of it. I read this as part of hobby studies.

Started studying AI Engineering

While I usually separate my studies in either career or hobby, the accelerating pace of AI led me to try a new approach this year. I started adding a technical book as well into the mix, effectively making it three categories. This did not go as well as I expected, I ended up having way too many tasks with less free time, and started skipping the studies for weeks at a time. In 2026, I plan to restrict it to at most 2 categories again. Regardless, the first technical book I picked up was AI Engineering, which is a foundational book for the most hyped type of development of our current times. I have not yet finished it, and so far it has been instructive but not particularly engaging. I read this as part of technical studies.

Started studying Beyond Vibe Coding

The second technical studies book I picked up was Beyond Vibe Coding, which tries to give some guidance of how to effectively incorporate AI development tools into solid engineering practices. This has been more useful than the AI Engineering book I mentioned previously, but it does have the feel of an extended blog post. It is unclear if the content in it will still be relevant 2 or 3 years from now. Nevertheless, I intend to finish it in 2026. I read this as part of technical studies.

Portfolio projects

I like to keep a portfolio of representative projects in my Github profile. These are not only public and open source, but also display, as much as possible, the engineering practices that I value: automated tests, automated CI/CD pipeline, good documentation, etc.

Each year I try to develop at least 1 new project, but I also keep releasing new version of older ones when I have anything I want to add to them. Most of the new projects are focused on exploring how to incorporate LLMs and other generative AI tools into software systems as more than mere chatbots.

Here are the relevant developments of 2025:

Several new versions of JenAI

JenAI was my first portfolio project around generative AI tools, and is basically a terminal chatbot (I have written a blog post about it). I use it extensively for personal purposes, and have built quite a bit of tooling around it for myself. It is intended to be a personal tool, so I have no plans of putting effort into making it generally useful to a large audience, despite being very fond of the project.

In 2025, I released two patches for it: v1.7.2 and v1.7.3, both to improve the sanitization of strings so that it doesn't break when exotic characters are used in the conversation.

Developed LLP (Local Language Practice)

Local Language Practice (LLP) is a system to practice languages through a roleplay chat with LLMs (I have also written a blog post about this one). This was my main project for the year, and it is around a topic that I really want to explore further in the near to medium future: generative AI applied to education. It is a project I have used quite a bit for real learning, but not as much as I wanted because I have had very little time to invest in studying languages this year, unfortunately.

I released the first version in April of 2025 (v1.0.0), and two more versions later in the year (v1.1.0 and v1.1.1).

Developed LicLacMoe

LicLacMoe was more of a fun project, one in which you can play tic-tac-toe against an LLM (as per usual, I have a blog post about this one as well). I like to think of it as "the most useless application of LLMs you will likely ever see". Despite the obvious silliness, it was also an interesting study about how to use LLMs for specific tasks, instead of a generic chat interface. It also allowed to verify the (admittedly obvious) fact that reasoning models are better at playing games with logical rules than vanilla models.

I also released three versions of this one in 2025, all of them in May (v1.0.0, v1.0.1 and v1.1.0).

Finished 4 first steps into AI Engineering projects

Back in 2024 I had started a series of four projects I called "First Steps Into AI Engineering" (guess what? I also have a blog post about this). These consisted of JenAI, Chargen, LLP and LicLacMoe. In 2025 I was able to complete the last two, and wrap up the series. This series was very useful for me to learn how to build systems around generative AI tools (not only LLMs, but also image generation ones), something that is likely to become the baseline of contemporary software development.

Created programming language learning projects curriculum

Late in the year, after moving to a new team that was using Go as the primary programming language (and having no prior experience or knowledge about Go at all), I saw myself having to very quickly learn a new language and tech stack, with the all-too-helpful but way-too-helpful assistance of AI coding tools. While I was able to very quickly become productive, I felt like I didn't understand very well the code I was shipping, and that annoyed me. So I set out to create a curriculum of projects for myself that covers most of the basic concepts I have used in my career, the purpose of which being that if you implement all the projects it contains in a particular language, you should feel very comfortable developing software in that language. I am currently applying it to Go, and so far it has been proving itself as useful as I intended it to be. (Of course, I have a blog post about that).

Developed Catcher Server project

In the end of the year I also developed the Catcher Server project (and wrote a blog post about it). It is somewhat of a break with the large line of AI-related projects I have been implementing in the past two years, but I think it is a nice little tool that already proved useful to me a few times. I also used it as an opportunity to apply full vibe coding in building something a little more complex than simple scripts - applying this to a simple and low risk project was very good to build experience for more challenging ones in the future.

Professional

I also had a quite busy year at work, being involved in a series of initiatives, moving to a new position and winning a few prizes.

Open Source Champion

I have been an Open Source Champion within my company since late 2024. However, the first months were mostly onboarding and ramping up in the topic and the role. In 2025 I was finally able to really make some meaningful contributions in this role. Beyond just Open Source, I have also been heavily involved in the topic of Innersource (applying Open Source concepts and techniques in the context of a private company). As part of this role, I presented the topic at internal developer conferences of the company, organized hackathon-style events and delivered workshops as part of some of our internal development curriculums.

Innoweeks as Dev Lead and MVP

At my company we have a month-long event called Innoweeks, in which we get together with customers to build an MVP that solves a real business project in a burst of short iterations. I had participated in 2019 and 2024, and I did so again in 2025. This year, I was the dev lead for the team, and received the MVP prize for my team at the end of the event.

Won third place prize at Innovation in my location

I work at one of the biggest locations my company has - we have over 3000 full time employees here. Which means we get to do a lot of cool events and initiatives based here. In 2025, the location offered prizes to the people who got involved the most in boosting innovation at the company. The way it worked was that each participation in innovation events or activities would give the participant a certain number of points along the year, and the people who won the most points at the end of the year would win. I was very honored and happy to be in the podium for this, I was the third person who contributed the most among the 3000+ employees we have.

Moved to a new team

I rejoined my company in 2024, but I did so in a team that was really not a good fit for me - it was responsible for a very old monolithic system and still operated with waterfall methodology, both of which I am strongly opposed to. After I concluded the one year that the company demands you stay in a position before applying to another one, I applied to join a new team working in building the platform that the company runs on. While I am enjoying the current technology stack, and our technical scope, much more than the previous one, unfortunately the new team also has several leadership and organization issues that I am trying to improve, little by little. But overall I am much happier now than last year.

Learned Go programming language

With the move to the new team, I also had to pick up the technology stack the team was using. In this case, it was mostly the Go programming language, with Kubernetes as the runtime. I am already quite familiar with Kubernetes, but I had never worked with Go before. So that was an opportunity to learn the language, and add another tool to my toolkit.

Monthly Recap - 2025-12 December

December was a very nice wrap up for the year, in which I could get a lot more done than in previous months. Big changes, lots of catching up, and an overall bump in productivity. While not everything is yet perfect, it certainly helped to improve morale.

Achievements

Back to personal studies

First off, after a long stretch (almost half an year!) without being able to focus on personal studies, I was finally able to get back to it. While I am not entirely back to my normal pace, I made a lot of progress in both books I am working through, and put some time into it most weeks. I am almost finishing Rich Dad, Poor Dad now.

Blog posts

I was also able to set aside some time during the holidays to write several blog posts I had been planning to. These were all based on projects I undertook in the last three months of the year, but that I was too busy to document.

Here they are:

• Projects Curriculum For Learning Programming Languages
• Learning Golang
• Project: Catcher Server

Attending TDC

December is usually the month in which The Developers' Conference (TDC) has its Porto Alegre edition. This year was no different, and fortunately I was once again able to attend it in person. This is the third year in a row that I do this, and it is always one of my favorite times of the year.

Just like last year, this edition was smaller than the normal version of the event. While last year it followed the "AI Summit" format (which I highly dislike), this time it used the "TDC Experience" format, which I found better than the AI one, but still not as good as the full version. The event took place in a different venue from the classic Uniritter campus - while I liked the space (inside the Barra Shopping), I felt it had a less distinct atmosphere. Nevertheless, this time I was able to attend it together with other colleagues from my company and even my team, so it was overall a great and pleasurable experience.

The talks themselves focused more on seeing AI through a more mature and seasoned perspective, keeping the high expectations while starting to recognize and analyse several of the possible pitfalls it offers. I think this shows the "growing up" of the software development ecosystem with regards to this technology, and I only wished my company was at this stage as well - unfortunately, we are only now getting into the "starry-eyed adolescent" phase, a good 3 years behind the whole world.

Downpoints

While there were no major negative points this month, I do feel I am not yet fully back to speed, after all the chaos of changing jobs and moving to a new place. There are several days in which I still get stuck with some minor problem to solve and can do no useful work. Thankfully, these have been getting rarer lately.

Plans for next month

January is usually a month to plan things and set up new routines. The only thing I am mostly convinced I will be focusing on for next year is improving AI skills, so I expect to already get started with some of that. But mostly it will be coming up with a solid plan for 2026.

Monthly Recap - 2025-11 November

After several chaotic months, in November things finally started to settle down a little. While it was still far from my normal, I was able to put some time working on things I wanted to do, and had some nice achievements. Here's a quick summary.

Achievements

Programming language learning projects

For a long time I wanted to create a personal curriculum of projects to develop in order to become proficient in any new programming language. Having gone through the process of learning Go during the second half of this year led me to finally do this. I created a list of ten projects which get progressively more complex and cover most of the essential programming concepts. I have made this personal curriculum open source on Github, and wrote a blog post about it.

Go learning projects started

I immediately started applying the previously mentioned curriculum to my learning of Go. I am slowly working through it, and so far the experience has been really great. I can already feel the benefits, as I feel way more confident developing software in Go now than when I started. I am keeping the projects in private repositories on Github, as for now I do not see the value in making them public - this might change in the future.

Catcher server project

This month I also published another new open source project, catcher-server. It is a simple Python web server that logs to the console information about any request it receives, useful for debugging and validating applications that make outbound requests. The need for something like this came when I was working with microservices and a very new platform which does not have full observability capabilities yet - while I could look for existing alternatives, I thought the scope was perfect to have some fun and vibe code plus open source a simple project. The combination worked pretty well! I have also written a blog post about it.

Downpoints

Personal studies blocked again

While November allowed me to dedicate some time to work on personal projects, it was not yet enough to fully get back with personal studies. It has been a rough year, and I have been blocked on this front for several months already.

Plans for next month

Get back to personal studies

I expect December to continue the trend of things getting less chaotic, and with that to have more time to focus. One of the main things I expect to get back on track is my personal studies habit, as it has suffered tremendously already this year.

Project: Catcher Server

Every now and then, while building and gluing together different pieces of a system, I run into the need for exactly one thing: a tool that will tell me, in the most direct way possible, what a given service is sending out as an HTTP request. No frills, no mystery, no surprises... just give me everything, and don't ask questions.

This is precisely the itch that catcher-server was built to scratch. It's a minimal open source HTTP server designed with only one job in mind: to receive any HTTP request, on any endpoint, and log clearly to the console its method, endpoint, and payload. You throw requests at it, it logs them. That's all there is to it.

Why did I build it?

The motivation came from real needs in my day-to-day work. I was working with a new platform at my job, dealing with limited deployment and observability capabilities. When you are working in such an environment, the quickest way to validate and debug what is happening is often to set things up locally. So, rather than guessing at what my services were really sending, or trying to wade through partial logging and indirect clues, I wanted something that would display the complete truth about outgoing requests, with zero ceremony.

You might reasonably ask why not look into one of the many alternatives out there. The answer is simple: I wanted something I could run locally, that would be mine, with zero licensing or learning curve to think about. Just something I could launch instantly, trust, and forget.

Vibe Coding

There's another reason why I consider this project relevant. It is a great example of a good use for vibe coding. Catcher-server is not a polished product for broad public consumption, but rather a practical and friendly tool, spun up to fulfill a personal/internal need. Projects like these are perfect for a more relaxed, collaborative coding session, especially when working with AI tools to speed up the boring parts. I see vibe coding as an ally for prototypes, utilities, and experiments - fast, fun, and effective in their scope, even if not suited for rigorous software that needs to last forever.

Under The Hood

True to its spirit, catcher-server is built on Python with Flask. That's it: no frameworks or engines beyond what is needed. The idea was to keep everything as simple as possible. No clever tricks or fancy abstractions, just a straight line from incoming HTTP requests to the console log.

Use Cases

While I personally used catcher-server for a microservices project, the intention is broader: it's meant for debugging, testing or observing outgoing HTTP requests from any project. If you want to get the real payload, headers, or query params from your code, without distractions, catcher-server is here for you. It isn't opinionated, and it isn't limited to any domain. Point your requests at it, and it will always catch them!

Conclusion

Catcher-server is the kind of tool I like to have at hand: minimal setup, instant feedback, and the freedom to use and adapt it however I want. It's not going to change the world, but it just might prevent some early gray hairs!

Links

Source code: Github

Learning Golang

This year marked a significant shift in my professional journey as I transitioned to a new team, where Go stands as the primary programming language. As someone who hadn't previously engaged with Go, these past months have been a deeply immersive learning experience. In this post I will briefly share some of my thoughts about this process.

It's particularly pertinent to consider this journey amidst the current, somewhat chaotic, integration of AI into every facet of software development. It offers a valuable opportunity to pause and reflect on what it truly means to acquire new skills in an era where some people claim AI makes all skills obsolete.

My Learning Trajectory 

My approach to learning any new subject, especially a programming language, typically involves a structured path. While often a single video course suffices, I added a few more steps in this case. I began with the official language tutorial, followed by a full video course, and, finally, embarked on a series of personal projects to solidify my understanding.

Official Tutorial 

The initial step involved working through the tutorials on the official Go programming language website. This proved effective for environment setup and familiarizing myself with the core code-build-run cycle. My exploration here was primarily foundational, extending only slightly beyond the "Hello World" scope.

Udemy Course 

After gaining a basic grasp of project bootstrapping, I sought a more in-depth, structured resource. For years, Udemy has been my go-to platform for professional development in software. Thankfully, I found out that Maximilian Schwarzmüller offered a "The Complete Guide" course covering the language. Having completed several of his courses previously, I had high confidence in the quality, and I wasn't disappointed. Though perhaps less comprehensive than some of his other offerings, it provided a robust foundation in the language's fundamental concepts and constructs.

Projects 

While a thorough video course usually equips me sufficiently, in this instance, I felt the need for more. This followed from a confluence of factors: Go not being my immediate choice for personal applications, its less-than-intuitive aspects, and the workplace emphasis on AI-generated code over manual development. All of this motivated me to deepen my learning through practical application.

That is when I created a list of 10 application projects to develop in the language, which would progressively make me exercise more and more complex concepts. I have wanted to create such a "curriculum" for a long time now, so this was the perfect opportunity to do so. I tried to frame the projects in a way that could be used for almost any language, and put the list in a public Github repository. I also wrote a blog post about it.

Challenges 

AI

Artificial Intelligence undeniably offers substantial productivity gains in our field. However, the prevailing directive from upper management to uncritically deploy AI-generated code introduces significant challenges, particularly concerning knowledge acquisition and retention.

When your only incentive is to push out as much code as possible, as quickly as possible, it is easy to not put the effort (and time) into learning new things. If it seems to mostly work most of the times for the things you already know, you end up assuming it will also work when you do not know enough to make a judgement on what it is producing. But the catch here is in the "most" and "mostly" part: there are very significant and problematic cases in which you need to use your judgement to override something the AI made. If you are using AI to ship something in a language you do not know, you are not able to do that.

My approach has been to use AI as dictated while at work, and while creating things for personal use that I already know deeply how they work. But to avoid as much as possible relying on it while I am learning something new - I try to write all new code by myself, researching when I do not know how to do something, and only resorting to generated code when I am at an absolute loss. I then use generative AI models to analyse and evaluate my final implementation, asking it to give tips about best practices and where I could improve. I believe this approach not only preserves the learning benefits of a pre-AI era but also augments them, maximizing the value derived from this new technology. It is a shame that it is so hard to communicate this to the highest level of management at companies, these days.

Overlapping 

Another challenge I found is the fact that I do not see myself using Go for my personal projects. The language seems to overlap a lot with other languages (mostly Java, also some Python and JavaScript) that I already master and that work perfectly fine for me. I feel like I have to put conscious effort to choose Go as the main language for any new project I might start, and I am not sure how sustainable this is in the long run.

Thoughts So Far 

Overall, I find Go a pleasant language to work with and considerably simpler to learn than I anticipated. While it is definitely not my favorite language (not by a long shot), and I don't foresee continued investment in it beyond my current professional requirements, it effectively serves its purpose, generating optimized executables with minimal overhead.

Error Handling Code Everywhere

One aspect of the language that I find slightly weird is how much error handling code it needs. I do not know if this is just a skill/experience issue, but having seen code for fairly seasoned Go developers I am inclined to conclude that it really is intrinsic to the language. It feels like half of every Go source code file I read consists of "if err != nil".

While I do appreciate the safety that this might bring to programs, it still makes the code feel slightly uglier than in other languages, to me.

Dependency management

The only other point that I find disconcerting is Go's dependency management mechanism. Coming from a Java and JavaScript background, I am used to having solid, unambiguous and strict manners of declaring and managing your dependencies. Go's approach feels very idiosyncratic and flaky, and at least once per month I have very experienced Go developers telling me to run some arcane command to "just fix your vendoring" without being able to explain what the command is actually doing.

Projects Curriculum For Learning Programming Languages

While learning the Go programming language, I did something I have been wanting to do for a long time and created a short "curriculum" of projects to develop when learning a new language. The idea of this curriculum is to progressively expand one's understanding of how to do several common programming tasks in the desired language, and should be agnostic enough to work for almost any language.

I made this list public in a Github repository, and in this post I will briefly describe the reasoning behind it and introduce the initial set of projects.

Reasoning 

For many developers, embracing new programming languages is an intrinsic part of the professional journey. While some may comfortably settle into a familiar stack, the evolving technological landscape often rewards those who frequently broaden their linguistic horizons.

While it is possible to become reasonably proficient by fumbling your way around, especially if you already know a very similar language, the results are better when you apply deliberate effort to the learning journey. A mixture of understanding the concepts and getting your hands dirty creating something with the language works the best. This curriculum covers only the second part, you should first have taken a short course or read the basic tutorials of the language to get the concepts and theory.

My initial list has 10 projects, starting from the simplest behavior possible (logging some text to the console) and ending with an application to fully manage a resource. Along the way, it exercises programming constructs, interaction with the filesystem and exposing a service through HTTP requests.

By following this sequence and implementing each project, one can acquire a robust intuition for tackling the vast majority of tasks encountered in any language. This gives the confidence to then use the new language effectively for any project requirement.

A Note On Perspective 

This list is heavily shaped by my own experience, as someone who has mostly developed for the cloud and desktop, and with a backend focus. It might not cover several things that are important for frontend, mobile and AI/ML development.

The Projects

I created a public Github repository with the list of projects, and I intend to enrich their descriptions and refine the list as insights emerge from using it.

Here is the initial list, with a short description of what each project contributes:

1. Hello World

Classic first program in any language, just print out the message "Hello World" to the console. This makes you understand how to set up, build and run a project in this language.

2. Current day and time greeting

Print to the console a short greeting informing the current day and time. This allows you to learn how to use the standard library of the language, move away from hardcoded values to start using variables, and string formatting.

3. Guess the number game (CLI)

Simple game in which the application chooses a number between 1 and 100 and the user has to guess it in 7 or less attempts. This introduces handling user input, conditionals and loops.

4. Note taking (CLI, local filesystem)

Start a CLI that reads user input until a certain pattern is entered (such as /exit or similar), then saves all the text entered to a file named with the current date and time to a standard folder - optionally, offer a "view" mode in which the notes already saved are displayed. Focus here is learning how to interact with the filesystem and an initial mode of persistence.

5. To-do app (CLI, database/sqlite)

Application that allows users to create tasks and mark them as done from the terminal. Learn how to interact with databases in the language, a good first option usually being sqlite.

6. Hello World (GUI)

Same as the first project, but now displaying "Hello World" in a graphical interface. This project makes you learn the very basics of creating an UI in the language. Depending on the language, this (and the next two projects) might not be relevant, or be redundant - in a language usually applied in a stack that is graphical by nature, the CLI version of these projects will already teach how to create graphical interfaces.

7. Guess the number game (GUI)

Same as the third project, but now with a graphical interface. Most important learnings here being how to receiver user input in a GUI and how your custom logic interacts with the UI rendering loop (often requires basic multithreading understanding). Depending on the language, might not be relevant or be redundant.

8. To-do app (GUI)

Same as the fifth project, but now with a more sophisticated user experience to edit tasks. The main benefit I see for this project is to give a holistic understanding of a complex end-to-end scenario, going from an user interface all the way to a database and back - after finishing this project it should feel like you can comfortably use this language to solve real-world problems in a user-friendly way.

9. Quotes app (REST)

Web application that returns famous quotes from certain people (can be hardcoded) through HTTP requests, preferably applying the read-only parts of REST. This project allows you to learn how to run a web server in this language, and use your custom logic to respond to requests. I do not see the need to also implement the client part for this project, but frontend-focused developers might see the benefit.

10. Album manager app (REST)

Web application that fully manage an "album" resource - allowing the creation, edition, listing and viewing of musical albums. The challenge with this project is implementing the full management of a resource, including its nested entities (an Album has an Artist, a list of Musics, etc.) and database persistence. It serves as a capstone - if you are able to do this, you should feel confident to say you are proficient in the language. Most entry-level jobs would have very similar (if not lesser) expectations, and if you reached this stage it should be very easy for you to go after any subsequent knowledge as the need arises.