Why mood tracking? I consider self-awareness and understanding your own feelings quite important. “Classic” journaling is a tried-and-true approach, but it requires regular effort, which I’m sure many people lack. Exactly like me :). That’s why an app where once or twice per day you tap one emoji, with an optional note, can be a good starting point. And once you build that habit, you can go further. Or not, if mood tracking by itself is enough.

Funiki 1.0

The starting point for Funiki was to become one of the best free mood tracking apps. Of course, it had to be different in some way, because this category is very saturated. The unique feature I chose was a wide range of emojis to characterize your mood, instead of the typical “very bad” to “very good” scale.

The app also had a map showing all your moods, but without any filtering or anything like that.

Another quite unique feature is a widget that tries to find a connection between the weather in your location and how you feel. It was actually interesting for me to understand whether weather has any meaningful impact on my personal mood, so I built the feature and made it available for others as well. By the way, it looks like I’m not affected by weather in any way :).

Other than these two features, the app provides pretty typical functionality for similar apps. You can log your mood, link some activities (standard ones or your own), create a journaling note, or add a photo to review later.

And then see how your mood changes day to day, which activities make you happy and which don’t, and which ones bring a lot of controversial feelings :).

Considering the limited free time I have, I had to deprioritize many things. So Funiki uses standard Material Design icons and in general looks very simple. My idea was that more extensive and unique functionality would make up for the design weaknesses.1.

So that’s it for Funiki 1.0, which I think was completed a few months ago when I added the Weather & Your Mood widget.

BUT. I never actually imagined Funiki as a simple mood tracking app. I wasn’t even sure about such a thing as mood tracking when I first thought about some of its features. Only later, when I searched for “log an emoji instead of describing your feelings,” did I find out that this is a whole separate category of apps. I just decided to start with the “mood tracker” path and then build everything else on top of it, assuming that some people would find the app useful for this functionality alone.

Togetherness

I didn't know this word before, but I know it now thanks to this post by Matt Webb: https://interconnected.org/home/2021/09/22/togetherness, and even more inspiring https://interconnected.org/home/2024/09/05/cursor-party. I love the idea of knowing that others are sharing something with you even when you just scroll a website, watch something or play a presumably single-player game.

The examples I love and got inspiration from (besides cursor party:)) are Journey and Megogo live event streaming.

Journey is a 2012 video game where you play an adventure sometimes seeing other characters close to you. I didn’t know this when I played the game for the first time, but those characters were actually other random players!

Megogo is a Ukrainian streaming service that has a nice feature where you can choose and send an emoji while watching live sports events. You also see emojis from other people popping up.

Both examples are great at giving you a feeling of doing something together with complete and anonymous strangers. And it’s beautiful.

As far as I know, there’s a somewhat similar experience in the game Death Stranding, where you see buildings built by other players in a kind of async multiplayer. But I’ve never played it, so I’m not sure how it works in practice.

There’s also another great example of togetherness that’s probably hard to understand for people outside of Ukraine: Telegram channel reactions. You might think: “is it something like post reactions in FB? Are you all boomers there?”. But in our specific case, these reactions are very “live.” They appear quickly on each post, and you can almost feel how many people share the same emotions. The specificity of the case is that we often spend nights following particular channels to understand which missiles or drones russia sent to kill us this time and how far they are from the places we live.

Like in the screenshot above, we see that russian strategic bombers are communicating via radio, which probably means they’ll fly and launch missiles tonight. Of course, they usually complement this with a few hundred drones that are already flying.

2.0

And so we come to Funiki 2.0.

Being a father of two beautiful little twins and having a quite demanding job, I usually work on the app in short stints late in the evening. So progress is slow (even with AI, which helps a lot). But this January I finally shipped the first feature that I consider part of version 2.0. It’s called “Shout Out”. The feature is optional and was disabled by default for all existing users to avoid accidental “shouting”:).

How does it work? When you enable Shout Out, your last mood is put onto the map. Of course, it’s not showing your username. And of course, each time the location is randomly chosen within your city or region to avoid any privacy risks. The mood stays there for up to 24 hours and then disappears.

This is how an inherently “single-player” mood tracking experience turns into “multiplayer” and thus maybe, hopefully, helps people who use the app feel a little better :).

That’s it for now, but I’ve got more ideas to implement. They will definitely work better if more people use Funiki. So I hope people discover the app and start using it!

Links for convenience:

1. Website: https://funiki.app

2. App Store: https://apps.apple.com/us/app/funiki/id6749832223

3. Google Play Store: https://play.google.com/store/apps/details?id=app.funiki.funiki

My latest pet project is a mobile app for tracking your moods and emotions, as well as for simple journaling. I don’t think it’s the best journaling experience though. For those people who prefer writing many words, there are better alternatives out there.

The app is written in Flutter, and I love how efficient Cursor helps me here. I would probably never be able to complete it without vibe coding.

It is called Funiki and is available for both iOS and Android:

https://apps.apple.com/us/app/funiki/id6749832223

https://play.google.com/store/apps/details?id=app.funiki.funiki

The main feature in Funiki is that it allows you to choose from a wide range of emojis, instead of a simple scale from “very bad” to “very good”. It also has various statistics and shows how you felt in different places.

I wrote a short review for it here: https://moodtrackers.org/funiki-the-most-feature-rich-free-mood-tracking-app-preview/, you can check the screenshots and more info on the app there.

Personally, I consider Funiki being in a “public beta” as it misses a few crucial features like reminders and custom activities, but I think it’s better to add them gradually.

There are lots of mood tracking apps out there, but not so many of them actually provide proper free functionality (almost none I guess:)), so I hope Funiki will find its users.

Will see.

Like for any pet project, the work is being done extremely slow with many interruptions, but I’m fine with this:).

In parallel, I had an idea to start a blog where I’d review various mood tracking apps with the hope to also mention mine when it’s ready. My idea was that my app would be among the few free ones and would stand out even with fair and honest review from my side. This blog (in my mind) would start bringing some visitors who would try different apps and hopefully download mine as well.

I write 1-3 posts per month, use Yoast SEO plugin for Wordpress that says my “SEO” (whatever it means) is ok-ish, but it seems that Google doesn’t want to show the blog to people. I get only single-digits search impressions and that’s it. My assumption was that it will change over time, but the result is still the same. I’m as far from SEO area as it’s possible, so decided to ask AI for help:).

It made some general suggestions that are already implemented. Like making sure the website is indexable, added to Google Search Console, has clear headers etc. But it seems that it’s not enough for Google to consider the blog trustworthy or something. The only thing I’m missing from the general SEO suggestion is having some “backlinks”, i.e. other websites that link to mine.

I definitely don’t want to spam any Reddits or websites with such links, so let’s try to have the one and only backing here on my blog:). It seems fair that I can post it here and let’s if it helps Google to find my website.

The URL is https://moodtrackers.org.

There are two main categories with free and paid app reviews to check out:

• https://moodtrackers.org/category/free-mood-tracking-apps/

• https://moodtrackers.org/category/paid-mood-tracking-apps/

If you can check it and let me know what can be improved there, I would be glad to here it as well!

I see the following reasons for the slower AI tools adoption among some people.

Note: we work on the successful and mature product, the team consists of good experienced engineers who know their craft and our stack/services/etc very well. I can imagine that in a company that creates something from scratch, or works in a more dynamic and unstable environment, as well as with less experienced people, the situation will be different.

1. Initial experience with early versions of AI assistants was subpar. The lack of context and «knowledge» about the coding style, the particular language version and design approaches led to incorrect coding suggestions happening way too frequent. So people preferred to just write code like they always did only asking ChatGPT some specific questions.

2. Experienced engineers are very good at what they do. They don’t need help with defining a UI layout or writing some DB access code and business logic. The tasks where any (even basic) AI assistant is good is just not useful for them.

3. Experienced engineers got used to their existing IDEs, they know all the key shortcuts and efficiently use everything. So trying another workflow, or even different IDE (i.e. Cursor instead of IntelliJ IDEA or Rider) causes a significant inconvenience and initial performance hit.

4. Good engineers actually love their work (or most parts of it:)). So where I, as a non-programmer, am happy that Cursor wrote that JSON parsing function for me, they actually prefer to write it themselves! Because that’s what makes their work pleasant and gives satisfaction. They might use the AI to help with writing tests here though (as it’s less fun part of work).

5. Telling the AI what to do seems not as simple and straightforward as just writing code yourself if you’re good at it. This is very close to the p.4, but still slightly different. And this point can explain the fact that many indie hackers or managers (including me:)) are so excited with AI-assisted programming and many programmers are more skeptical.

What does it mean for the industry? JetBrains has a good chance of catching up to Cursor, Windsurf and Zed if they find a way to improve their own AI assistant quickly and integrate it with the existing IDE workflows in a smart way. They’ve got many devs who love their tools and do not want to stop using them.

I think it’s also true for any other dev tools creators (MS, Apple, Unity etc), but they need to act fast. Otherwise, the initial hurdles of migrating to another coding editor will be overcome by more and more engineers and the new standard will replace them.

It seems that MS (or any other company) could also fight the new competing AI coding editors by providing rich and consistent AI experience with the extensions for all popular IDEs. However, they do not do this for some reason and deliver the newest preview features only of VSCode. I’m curious if we end with many VSCode forks as a typical editor for almost any programming job in the end:).

LLMs have been with us for quite a while. ChatGPT or Claude have become irreplaceable helpers for many users when they search for something, want to understand how things work or need help with creating content. Lots of innovations continue happening in this area and we see AI-related news daily. There is a big trust among investors in the power of generative AI tools to improve productivity and even replace workers completely in some cases.

However, despite all of the LLM accomplishments, many people remain skeptical of their capabilities. It’s also common to make fun of companies which declare that they now “utilize AI” by integrating a ChatGPT-powered “ask a question” window to their software. For some, it seems that LLMs can strive as chatbots and autocomplete tools but nothing more.

It’s interesting that people in charge of software tech companies understand that chatbot is not the only way of utilizing LLM capabilities. For example, Notion CEO mentioned this in 2023: https://www.inc.com/jason-aten/ai-isnt-just-for-arguing-with-chatbots-why-notions-ceo-thinks-it-will-fundamentally-change-way-we-all-work.html

However, if we take a look at the ways different apps integrate AI, it turns out they still usually do it with chatbots, sometimes chatbots with a few predefined buttons and prompts. The same buttons as we have in any regular messenger chatbot. That’s it.

Here are some of these examples.

MS Copilot has a classical AI chatbot panel with a few generic buttons.

Notion has in-place “Ask AI” textbox that has predefined buttons. It's definitely better for some scenarios because it allows applying the AI action in the desired place and saves time for common actions. But still, I would argue that such company could do much better.

Why do I think so? Because recently I saw a very nice small example of “proper” AI usage by Google. And this is the company that usually doesn’t create the best UIs. Check out this Google Sheet recording:

Though very simple, it really demonstrates how AI-powered UX can be implemented to feel like magic. No prompting input field, no separate panels taking 20% of the screen. Just the app that understands your intention, asks for one confirmation click and does all the things for you! This is exactly how all of the software companies should start looking at their UX and adjust it where applicable.

ChatGPT was once called a “glorified autocomplete”. This name supposed to be dismissive, but it highlights one thing modern LLMs are quite good at: autocompleting text. That’s why it is very clear how beneficial they are for developers who write code (go check out Cursor AI by the way;)). There are following things that make LLMs useful here:

1. Context (a file or multiple ones with code).

2. Intention (developer writes a prompt or comment acting as a prompt or just starts typing their code).

3. Naturally limited set of possible outputs (code must follow a syntax, should reuse the existing variables and functions from the context etc). This helps with limiting possible hallucinations.

What did Google do in this simple example? They implemented the autocomplete! Just not for text, at least not for the text directly shown to user. How I see its possible implementation:

1. App sees the spreadsheet as a context.

2. App recognizes intention. For some typical actions it’s possible to identify them quite easily with simple algorithm, i.e. in the video above it is “user fills 5+ cells with values from a limited set”.

3. App “asks” the AI to generate the action based on the intention, data from the context, and only chose the action from limited set of “API for LLM” functions.

4. LLM choses the needed functions and does the job.

The “API for LLM” is the key here, as otherwise we cannot be sure in the successful result. The Braindump.me post linked in the beginning of this one addresses the issue nicely, but maybe I will explore the topic further and share my findings as well.

With the growth of possible AI-enhanced actions the app creators will need to put a lot of efforts into identifying user intentions and contexts. No understanding of intention - and you just end up with regular menu with 20 buttons. An incorrect context will render any action useless and only irritate user. So this is the area to explore, and probably the companies which succeed here will be able to amaze users. And when we see more such AI usages, people will understand that this “glorified autocomplete” when used properly, can be a very powerful thing.

Stack Overflow recently announced that they would partner with OpenAI:

• OpenAI will officially use the data from Stack Overflow in their models and products

• Stack Overflow will have some benefits when using OpenAI technology for various purposes including their OverflowAI extension

Gergely Orosz in his newsletter mentions that some users are not happy with this collaboration and even delete their answers. The author’s conclusion is that the website has passed its best days and this partnership is a rational step for Stack Overflow.

I obviously don’t know how fast Generative AI evolves and if it soon becomes close to replacing humans at complex jobs like programming. If it happens this way, the world will change completely, and it’s too difficult to even reason about how our lives will look like in it. But if it doesn’t, and AI remains in a helper role to humans, Stack Overflow might have a significant and bright future.

How can it look like? Imagine a Copilot/Copilot Chat like tool that helps you with code suggestions and answers. But the connection between you and the service is not one-directional, but bi-directional instead.

Now you don’t only get help from the service, but actively help it (and other users) back! All while being in your favorite IDE. If a code suggestion has a mistake, you fix it and the data goes back to system. You might write an explanation why it wasn’t good. And you, as a user, get some reputation points for this. The AI can edit the code automatically to make sure nothing sensitive is shared back. It can also adjust the grammar and tone for your answer for you instead of human moderators. And if some other user gets your answer or suggestion later, they can upvote (accept would count as upvote automatically) or downvote it.

If the service becomes popular, you can imagine a possibility of live interactions between users, sharing code snippets, asking questions etc. All this with AI-based tools for privacy and security enforcement when needed. Got a problem where you got stuck and AI cannot meaningfully help as well? Try a live screen share (with sensitive data dynamically hidden of course) with AI-chosen user who definitely knows how to help! Will this person be paid with reputation points, achievements or money is an interesting question here that suggests some new monetization options as well.

So while Stack Overflow still has a big and powerful community, I think they should revamp their service to empower this community with AI and make helping each other much easier instead of just selling data to the companies that will destroy their business in a year.

OverflowAI release shows that the company can create an app or extension needed and the question is if they are ready to execute a much bigger vision of it in the near future.

Now, the companies training new and more powerful models run into the problem: there is not enough data for this task.

So what do they do, besides synthesizing data for training and performing other clever tricks? They extend the sources of real, high quality data of course!

Now imagine that everyone can get a pair of new XR glasses. They are so functional, versatile and useful that you cannot even think of your life without them! All influencers wear these fancy devices, there are collaborations with clothing brands suitable for any audience. Also, they are dirty cheap.

What makes the glasses so cheap you could ask? Maybe ads that are shoveled right into your eyes? Or governmental Big Brother that sees you and controls what you say? Nope, though the second option is somewhat close.

The price comes with the condition to share all you see, hear and say while wearing the device with one of the Big Tech companies (in anonymized, absolutely safe, privacy-conscious way). They use your data to train the AIs and AIs become better to improve the society wellbeing. So you don’t only get a beautiful functional product and services for almost free, you also help the humanity! Together with 7 billion other people who wear glasses as well.

Do you like this vision of the future? I’m sure you do. So we can use some more imagination to ask ourselves additional questions about such world. For example, if most people wear XR glasses and minority does not, what does it mean? Are the ones who refuse wearing them are considered as just harmless weirdos, or are they evil criminals?

Or, another interesting one: are all the people equal in regards of their “usefulness” for data training? Is it possible that things many people see, hear and say are so generic and typical, that their “life logs” are almost useless for AI models? The models already trained on similar experiences and do not benefit from more of them. If this is the case, then naturally, there will be a category of “more useful” people who have unusual lives and share rare thoughts. Probably any company wants to have more such users and somehow incentivizes them to use particular devices. Do we actually see that these people are more special with some kind of open ILS (interesting/impactful life score)?

One more thing coming to mind is that not all experiences people share might be “good” or “moral”. But probably they can be very useful from the practical point of view. So, is there a black or gray market for such data?

And of course, considering the fact that over time our AI training data becomes bigger, there is an inflation of experiences. I.e. every year there are fewer things that companies consider unique and of high quality. People might get upset about this inflation especially if it affects their social status.

I guess there could be a nice short story written about such world as it’s interesting to think about life in it. And I also think it would be nice if we would stop at only imagining it rather than living it in the future. This world definitely looks better than The Matrix where people were just numb physical batteries for machines, but I would say still not very pleasant. Will see what happens next.

All images in the post are generated by meta.ai

Skeuomorphism was widely popular in UI design for computers, mobile phones and then smart watches for a long time. Probably the most famous example is Apple UI under Steve Jobs leadership. The purpose of skeuomorphism was to make interfaces “affordable” and easily understandable by users who didn’t have prior experience of interacting with new devices.

Here is an Audio Recorder app screenshot from iOS6 as a very prominent example:

Over time, it became clear that people got used to the virtual interfaces and there was no more need in direct representation of physical things on our screens, so the design became flat and minimalistic.

Of course, skeuomorphic elements are still used now, but in most cases these elements are not as “direct” as they were previously. Such approach allows using the limited screen space more efficiently and have consistent and slick UI.

Knowing that almost every person on Earth has experience of using mobile phones, I thought that skeuomorphism will be used only as a nice touching and aesthetic improvement of UI designs, and we will never see its return as it was. But yesterday saw a post on Threads by @yasirbugra:

It came to my mind that this is the real possibility of seeing skeuomorphism back, maybe even in a more functional form than we had on flat screens! If AR/XR devices like Quest, Vision Pro and their successors become popular among wide audience, it might be easier and more convenient for people to start using them with UI that closely resembles real objects, and not flat screens hanging around. This is not the case for any usage obviously, but I can imagine that “leaving” virtual “things” (like a notebook or a book) on a table or a bookshelf can be a nice step of making AR blend with our daily life seamlessly. And unlike for the case with 2d screens, we can now interact with virtual object in different ways by moving them around, rotating etc.

I can also imagine that some blockchain maxis will probably try to get back their unique NFT-like objects to our lives, but that’s another topic:).

Anyway, I am sure that the new devices will bring new interesting experiences and make our lives more fun, with or without skeuomorphism. But I personally would prefer to see some nice warm skeuomorphic UIs again.

If you don’t feel like reading the text, you can just get the app and try it yourself at implai.app (Apple App Store or Google Play Store).

Many years ago I stumbled upon a very interesting project. It was Matt Richardson’s Descriptive Camera: https://mattrichardson.com/descriptive-camera

The idea of the project was fascinating: you point the camera at something, press the shutter button, and get a paper with the text description of what the camera was pointing for. I was in awe about this simple but powerful idea. In 2012, when the project appeared, the solution to have this feature was to upload the actual picture to Amazon Mechanical Turk service where real humans described what they saw.

This year, while exploring Azure Cognitive Services, I found the service that automatically (and quite nicely) did what was previously possible only for people: described the picture! Some further research showed that it’s been awhile since such possibility has been enabled by ML, and can now be done even on devices.

So I started thinking about the concept and decided to do something with it. The first idea was to create a simple game where you would take a text “photo” with ML-generated description of something, and challenge your friends to get the same text pointing to what they have at hand. But while continuing to think how ML can describe and adjust the descriptions of what we see, I decided to create something else. The new idea was to not only use ML to describe the image, but also to add some kind of improvement or “vibe” to it, in the same way Instagram introduced filters to regular photos.

This is how Implai app was created, as well as the concept of a “tilter”.

At first I planned it as a simple “two weekends” project, but of course when you start working on something, it’s usually quite difficult to stop:). So now there is an app that allows users to take these text “photos”, share them with anyone, get comments, follow people etc.

Here is how you can do it.

1. Take a picture. Better of someone nice and cute of course, like Vasia:

2. Upload it so the image is recognized:

   

3. Create a text “photo” with the optional description:

   

4. Apply “tilter” to change the text and appearance. And voila, here is your post:

This is basically the main flow in the app, but I encourage you to try it yourself! Here are the links: Apple App Store and Google Play Store . The app doesn’t need your phone number, doesn’t ask for location or contacts. Just email. There is no validation for one-time email services by the way, so feel free to use them if you don’t want to share your real one.

I can imagine the concept from Implai can be a nice way to share our daily life things not as a mere boring text, but also not as photos that sometimes feel a little bit too revealing (and introduce obvious privacy concerns). But maybe I’ll share some more thoughts about it later:).

For now, looking for the app feedback!

The easiest way to understand the concept is to see an example. So, here it is.

Let’s say we have a text “a cat lying on a couch”. Like this:

And now, let’s apply some tilters to it!

September rephrases the text as if it was written in an essay by a 5th grader and obviously uses blue cursive:

Spooky rewrites it as a sentence from a horror novel:

And Summer Fun tries to use a hip language and adds bright pink background:

That’s it!

You can try it yourself in Implai app that allows to post and share text “photos” and apply tilters to them.

Used almost all of the current hype words in the title but could not think of a better one, sorry:)

A few years ago I interviewed at Grammarly and installed their extension to see what value it brings to users.

One of the features really caught my attention and sparked some thoughts. It was tone detection. The feature read your sentence and decided if it was “formal” or “friendly” and also offered to rephrase it according to your needs to change the tone to the desired one.

For me, it looked like a first step towards possibility of a mass-altered communication in a company or even wider group of people. I imagined that if a similar and slightly more advanced system was deployed across all text communication channels in some organization, it could check, adjust and even “censor” all the messages being sent. Depending on the needs it could make everyone sound either very polite, or extremely direct, or even change the content to forbid discussions of some topics. In a fully remote async workspace where people mostly use text, some could try enforcing specific behaviors and culture values!

Of course, in the real life we still use audio and video calls, often meet in person, and impact of adjusting only text will be very limited. But with the second coming of VR when Apple releases their Vision1 the idea might become a (dystopian) reality. Instead of video of our faces we might quickly get used to talk using generated avatars (https://www.theverge.com/2023/6/5/23750096/apple-vision-pro-headset-persona-facetime).

And the latest generative AI technologies allow to not only rephrase text, but also to generate realistic audio with the simulated voice of any person. So what you say can be “dubbed” to adjust what other people hear from you. This dubbing is not real time yet, but probably soon will become close to it.

And thus, we can imagine combining all these features together. Now your disappointed and angry colleague will say some harsh words, but their avatar in your VR headset will smile and politely explain you the situation they are upset with.

Looks like a scenario from a Black Mirror episode, but the technology is almost here. Will we use it and if yes, then to which extent is an open question though.

These thoughts sometimes lead us to desire of implementing these ideas, making them happen in real life. And here comes the challenge. Any finished product requires tons of effort to be completed. If our idea is not a part of our daily job, the typical and unfortunate result is… nothing. Or almost nothing. Like a purchased domain name, a few screen mockups and maybe a partially assembled backend service. There also might be a sense of disappointment and even guilt. But unfortunately, not something we are ready to show to the world.

So how do we counter this? There is a concept of Minimum Viable Product (MVP). It is a version of a product with just enough features to be usable by early customers who can then provide feedback for future product development (from Wiki: https://en.wikipedia.org/wiki/Minimum_viable_product).

Inspired by this concept, I propose to choose a Minimum Lazy Product path when building your pet projects. Like an MVP, MLP is a minimalistic implementation to present the idea, validate hypothesis etc. But in addition, MLP is a way to approach work considering our nature.

Oh, by the way, here is how Bing+DALL-E see MVP and MLP.

It looks like there is not much difference:

Probably because this term is not widely used, or maybe I’m not good at googling.

Anyway, let’s assume you want to create a new online game like Agar.io, something that looks very simple on the surface, but has many challenges when approached closer. You are a JS developer with most experience in writing front end apps and websites. When you start the implementation, you will see that some tasks go very fast, easy and fun, while others are a dreadful experience full of fails and setbacks. The idea of MLP is to list all of the tasks to be completed and split them into categories: Easy/Fun and Hard/Unfun (there is no such word, I know:)). For our example, they could be:

• Easy/Fun: frontend client app, UI, domain, hosting, gameplay design, game logic, story

• Hard/Unfun: server app (all these web sockets), DB, auth, graphics

By only defining the tasks and putting them into corresponding categories, you will make your life easier.

Firstly, because every time you pick up a next task, you will see in which group it resides and decide if you’ve got enough mental resources to deal with it today. You won’t also feel guilty if you fail to complete a Hard task, as it’s expected to be not easy, right?

Secondly, looking at each of these Unfun tasks, you should consider not doing them. Either not doing them at all (do you really need an auth, maybe having anonymous players with their name stored in localStorage is enough?) or giving this work to someone else. This could be a person or service, doesn’t matter. What matters is that for your pet project to be completed, you need to have your willpower and mental resources at a good level during the whole project development. Even one dreadful task can stop the whole project from being completed, so clearly defining unpleasant work and making sure you don’t do it unless it’s absolutely necessary can save the whole endeavor!

Hopefully, the approach will help to consciously spend your time, ship the product faster, get some feedback and decide what to do next. And this is what we usually want, a feeling of making your idea alive, right?

Same happens with the story and related quests. You learn about the game world, its characters and goals you have. Lots of interesting and sometimes complicated things happen around!

The experience is great when you are really into video games and can afford to play regularly. But what happens if you don’t have such possibility and play occasionally, for example on weekends? This:

You feel lost. You obviously know how to move, but doing something more complex like a proper attack becomes a challenge. If it’s some kind of a story-driven adventure/RPG, you might be in a state when you don’t remember what to do next, and why you need to complete one quest or another.

I often find myself in such frustrating situation and it turns out there is a very similar case with programming for me. I thought that it’s just some rare kind of mental peculiarity, but it looks like that at least for games, the problem is quite frequent: https://www.resetera.com/threads/do-you-remember-how-to-play-a-game-after-you-take-a-break-from-it.436346/

Talking about programming. Now I work as a manager, and have not coded anything at work for a few years. Occasionally, I get an idea of a pet project that I want to try developing or find an online hackathon and need to get back to the development after a long pause.

The last few times I attempted to write an app, I was feeling exactly like these unfortunate guys from Gravity Falls:

There was an additional challenge as I tried using the technologies or languages I’m new to. But even taking this novelty into account, I still felt that sometimes the work was just too difficult. Even simple things like “how to navigate across screens” or “how to send request and parse response with complex object from server” required googling, then seeing error messages and debugging them (sometimes with additional googling in the process). Of course I was able to get the result, but the progress was painfully slow and it demotivated to continue.

In this matter, hobby programming looks similar to video games for me. If you’ve got a regular practice in a language, you can write compilable code even on a piece of paper. But if not, then almost every attempt to write something leads to being stuck on a ridiculous problem and spending embarrassingly much time on solving it.

This post could be just a useless rant about difficult life, but a couple of weeks ago I started a trial of GitHub Copilot. Initially, I was a little bit skeptical of it, seeing people describe it as improved auto-complete on the Internet.

But then I installed the extensions (I use Rider and VSCode for C# and Flutter respectively) in hopes to make my new pet project development easier.

By the way, it’s a new revolutionary AI-powered social networking app. Not as revolutionary as IRL, but I hope it will be fun to use for some people. The world obviously needs more social networks and creating something new without adding AI nowadays is just pointless.

I read the prompting guide for useful tips and started working with the new tool. And… It turns out this was the exact thing I needed! Now, if I hesitate in the editor for a moment thinking how to write that arrow function, it magically appears by itself! Sometimes the suggested code exactly matches what I would write even without obvious hints around. Such moments make me doubt if I am in possession of imagination and free will, but that’s another topic to discuss.

And besides auto completion that now works significantly better than anything I tried before, the prompting can generate a new file with a simple working code, for example a Flutter widget. This code takes the context from the surrounding files and solves the pain of extending a typical boilerplate with what is needed.

There is obviously space for improvement for Copilot. But working with it for a week or so on my pet project made the experience faster and more pleasant. I’m happy with the progress even despite not so much time spent on it.

For those few who have not tried it yet, I definitely recommend to give a chance to GitHub Copilot.

Let’s now wait for Microsoft to include such a smart assistant for Xbox, and make sure people who play rarely don’t feel lost when trying to play a game once in awhile.

Imagine that you are managing a company. Not very small, but not too big either (I’ve never worked in big ones, so cannot perform this “imagine” thing about them, sorry). The big proportion of your time will be spent on strategic things, but you’ll probably spend tons of time on various status checks. You need to know how people are doing, are they happy or not, and what’s on their minds. Probably there are some particularly important projects that you’d like to track as well. Of course, it’s important to see some key metrics and trends. And maybe it’s useful to be aware of new big or unexpected problems happening too.

So many things to think about!

How do you perform all these checks now? I suppose a part of them is done using various tools for technical, customer support and sales metrics monitoring (Grafana, Monday). Lots of useful info can be seen using project management software (Jira). All these dashboards, roadmaps etc. As for people-related topics, another category of tools exists that allows to perform various surveys and analyze the data (CultureAmp).

However versatile and rich all these tools are, they still lack a universal and convenient UI for accessing random information and making insights. Their solution is providing possibilities to configure all kinds of dashboards to look at the data from different perspectives. This means that there is always someone who has to perform work to configure these dashboards before they are ready to use. As a consequence, you as a CEO will often come up with questions that cannot be answered by these tools immediately. The existing solutions for you are:

1. Obtain a certain level of expertise to be able to use SQL or JQL to query data yourself.

2. Ask your employees to answer the questions.

Option 2 is the typical way to go now, especially considering that lots of things happening in a company are not covered by the existing data analytics tools. You talk to your managers, and they answer the questions, give status updates, and raise any outstanding points to you.

Q1 is answered by the dashboard based on the data from Sales Team; Q2, Q3, and Q4 are asked on a 1-2-1 with your VP; they answer Q4 themselves, and go with Q2 and Q3 to the team and Team Lead respectively. Not very fast, but quite reliable, and you talk with nice people during the process.

So, despite all the new tools and technology progress, a CEO’s primary interface to their company is conversations (written or verbal) with people.

Now, let’s look at a typical software development remote company. All the project management is done in Jira, various information is stored in Notion. People communicate via Slack, Teams or Zoom. There are also software tools for Sales, Marketing, HR, Recruiting and all other teams. Anyway, the specific tools can be different, but their functionality is very similar.

Every remote company already sits on top of the data that could be analyzed and used for providing useful insights at any time. And with our desire to automate everything (software is eating the world, right?), I would ask the question: why do you even need people to access the company information? The two things already mentioned are that not all information is analyzed with the tools currently available, and there is no convenient user-friendly interface to access the data in place.

And if my understanding of the current AI developments is right, we’ve come to the point when we might have solutions for the two problems. And if this is the case, it could potentially disrupt the way modern companies are managed and work in general!

Lets see what I mean here.

People

The biggest part of a typical company information not readily available in some BigQuery-like storage is people. That’s why products like CultureAmp exist. They provide tools to understand how employees see their work, are they happy or not, do they share the company vision, if they plan to look for another job soon etc.

And actually, I think our technical capabilities are enough to see such information already without even asking people explicitly. If all the communications are done using software tools, a company could analyze the data from chats and provide a lot of useful hints, statistics etc.

You will always know.

The tool providers could even consider privacy aspects, and let’s say never share the actual messages from particular people, but still give hints like “the average sentiment towards company values for Sales Team has changed from neutral to negative, take a look!”. The data is here, the tools are here, so what’s stopping us?

A small caveat

While we’re used for our text messages and emails to be stored and then analyzed, there is still verbal communication happening (people’s favorite Zoom meetings). If a company decides to analyze the recordings, it probably might have some issues with privacy protection, as people want to have their small talks without being recorded. The solution? Add a switch “Working conversation” - “Personal conversation”. “Working conversation” is enabled by default, and everyone knows the data will be analyzed. If you want to have some personal talk, no problem, just switch to “Personal conversation”!

And to help people not to forget to enable “Working conversation” mode, our evil video conferencing app could use some small nudges like “Your personal conversation is happening for 10 minutes already. Maybe you started talking about work, but forgot to switch the mode (wink)?”. They could also show some stats like “Average person in our company has 30 minutes of personal talks, and 2 hours of work-related discussions. This week your stats are 60 minutes of personal talk and 1.5 hours of work discussions on average. Please ask your manager to take a look and help you to be more effective (smile).”

Helping you and your colleague to have efficient and result-oriented call.

Interface

Having all the information stored and ready to be requested, we need an interface. ChatGPT and similar products provide you such possibility! It can understand and answer your questions regarding a set of text data, and even provide ad hoc analysis! See for example ChatPdf. Going forward, you won’t need any predefined dashboards that limit your imagination! With the tools like GPT Code Interpreter1, you will see any data insights about your company you could ever dreamt of!

Now Q1, Q2 and Q3 are answered instantly based on the data from Sales Team. Only more complex Q4 requires a person to answer it.

Yes, the tools are not yet as good at answering the questions as humans, but they are readily available at any moment, you don’t need to schedule a call or wait for a person to answer after the weekend. And if these new tools have all the information about the company available, they often can be faster. They will be almost as good as people at many tasks, and it’s interesting to see if this will be enough to completely change the way you see your company as a CEO.

Future

I do not know where we will end up. But as the technology is quickly becoming better, we will see very interesting changes soon regardless of whether we want it or not.

This time I chose Twitter’s Chirp Developer Challenge. The choice was obvious, as most other events happening at that time were related to crypto something, which is not very interesting for me. And unlike crypto, Twitter is the thing I enjoy. So it was natural to do something with their API when having a chance.

So, I registered a developer account, and started building.

The idea behind the project was very simple: enhance Twitter profile page. The problems solved with these enhancements are:

1. The existing page does not show all the available data that can help users to understand if they want to follow someone or not. Some users try to describe what they tweet about in description or in a pinned tweet. But not everyone does this though.

2. Sometimes, it happens that you follow a user, but it turns out they mostly tweet in a language you don't know. A few latest tweets shown on the profile page do not necessarily match the most used language.

3. Sometimes you follow a user because you liked a tweet or two, but later it turns out they write about the topics you are generally not interested in.

4. It would also be nice if the profile page contained some fun and catchy stuff, just for the sake of it:).

And together with @kirraaaaa we created the project: https://devpost.com/software/twitter-profile

The short demo video of that first version is here:

The page showed a general profile info, like number of followers or location. It also included the data about “topics” (actually these are hashtags) and followers, as well as the most used tweet languages. One of the distinct features were “badges” given for some particular achievements. I also had an idea to analyze the “mood” of the tweets and tell whether a user is calm or mad. This was not implemented, as sentiment analysis APIs are quite expensive.

This app just queried the Twitter API and returned the user data available at the moment. This was a good solution, as it allowed to view the most recent data for any user. But at the same time, it was not so good solution, as it used the App limits of the Twitter API, and so would never work if many users started opening its pages.

I have submitted it for the judgement, and then continued working on the project in a separate repo to make it possible to run it for many people. This is how https://cvitter.com appeared. This updated version asks users to login with Twitter, and then uses their quota to retrieve data, and then stores it in DB. Now we can’t see a profile for any user unless they have created their page, but on the other hand, it is now possible to have as many CVitter profiles as possible.

From the technical side, I tried using Azure CosmosDB and Functions on Back end, and Vue.js on Front end. It was an interesting experience, but probably a bit of an overkill for such small project. I guess some generic Asp.Net MVC app would work even better, but then I wouldn't have a chance to try something new:).

If you want to see some profiles, check these:

• https://cvitter.com/lwoleksii

• https://cvitter.com/kirraaaaa

• https://cvitter.com/nasa

• https://cvitter.com/spacex

Or better create yours and post in comments!

Evil little bastard! That’s why I don’t clean you properly!

Why does this happen, and how to find a proper toaster that works like it should work? By “proper”, I mean that when putting the same bread with the same darkness control setting level, I always get the same result of toastiness (and tastiness, as the browser grammar checker constantly trying to hint me).

We can define such toasters as “pure functioning”.

According to Wikipedia:

In computer programming, a pure function is a function that has the following properties:

1. the function return values are identical for identical arguments (no variation with local static variables, non-local variables, mutable reference arguments or input streams), and

2. the function application has no side effects (no mutation of local static variables, non-local variables, mutable reference arguments or input/output streams).

So, an ideal toaster for me would be a pure-functioning one.

The humans have flown to the Moon, dived to the Marian trench, and now we are only 30 years away from nuclear fusion1! I can expect that spending several hundred dollars on a device from a well-respected brand will buy me that, right?

It looks like unfortunately, the answer is no. Here (and here with some more details) you can read that there are three types of toasters now: timer toasters, capacitor toasters, and bimetallic strip ones. Though the timer toasters are the most expensive (never thought a timer is an expensive part), they still do not guarantee the final result.

Having run into the toaster issue, I started to think about other home devices we use. Some of them can be called pure-functioning. I love using them: microwave, dishwasher, washing machine. I suppose that this property is one of the things that makes their use pleasant and non-stressful. Others are not pure-functioning, but we have workarounds for dealing with this disadvantage. I can name a stovetop or an oven as such. Thermometers allow us to make sure our oven has reached the needed temperature and we can start cooking. Frying pans have special “thermo spots”. Though not precise, they still give us some kind of a hint. And of course, there are pieces of equipment which we don’t even have workarounds.

It seems that the closer to being pure-functioning the device is, the more I like it. Maybe it’s because I’m a software dev, and not a normal human. But maybe this characteristic is the one that can make people’s lives better when added to all appliances we use. Let’s hope for the future researchers and inventors to come up with some clever solutions. And I personally hope they will fix our toasters first.

That was Flutter Puzzle Hack from Google. I found it interesting as it offered to create something in Flutter, and this “something” was a game.

The goal was to create a Sliding puzzle game variation. The hosts also prepared a code example with a standard puzzle implementation which was a good place to start.

Thinking about possible game variations, I decided to create a game where you need to “do something” to move each puzzle part. The examples I’ve seen were games/apps where you have to scream (yes, just scream) or look at the screen in order to make something happen. You can check these examples:

https://www.pcgamer.com/heres-a-game-you-control-by-screaming/

https://play.google.com/store/apps/details?id=com.ketchapp.screamhero&hl=en_US&gl=US

But instead of doing just one thing, I thought it would be more fun to ask gamer to do more: sometimes click on element with a right mouse button instead of left one, answer a question or two, click on a button in confirmation modal, and even solve a captcha.

The game turned out to be pretty irritating, as in order to solve the puzzle, you need to move elements a lot. That’s why I called it (Irritating) Slide Puzzle, and I guess it pretty much reflects the player feelings regarding the game. Unfortunately, I wasn’t able to add some voice commands, but this looks like a nice possible addition.

The idea of asking player to do something in order to make next move looks very promising to me. Maybe we can ask player to walk some distance, or take an interesting photo, or get a kudos from her friends in a social network. I hope we will have some fun examples of such approach somewhere in the future.

While waiting, feel free to try the game here: https://irritating-slide-puzzle.web.app, and also I recommend you to check different puzzle implementations created for the hackathon. There are many original ideas: https://flutterhack.devpost.com/project-gallery.

[the pic from official Lego.com webpage]

I like Lego, and also like everything about space, so naturally the gift was accepted with much gratitude from me. Then we spent several evenings slowly assembling it together, while living in my parent’s home after escaping from bombarded Kyiv. This was a nice experience to work on the rocket together.

[the result:)]

Later this Spring, we bought another set. Now, it was a McLaren F1 2022 car: https://www.lego.com/en-us/product/mclaren-formula-1-race-car-42141

We are fans of Formula 1 and particularly McLaren team, so we had been waiting for this car from the moment it was presented.

[the pic from official Lego.com webpage]

The set quickly went out of stock in Western online stores, but probably because of the war, people in Ukraine were busy with other things than Legos, and it was quite easy to buy it here. We started assembling the car together again and… unfortunately, it was not as fun as Saturn V.

Why? Because most pages with instructions contained only one part, which could be conveniently assembled by one person. In each of the 4 big steps of the whole construction process we also had to open several bags with lots of parts simultaneously. They took a lot of space, too much space together with the car which is quite big itself. So we developed a sequence, in which one person assembled the detail, and another helped with finding some parts for it in those big piles of Lego pieces. Then this other person put the new detail to the car.

With Saturn V we could usually build two details at the same time. The whole rocket basically consists of identical four-component sets put on top of one another. So we could work together, help each other with building details if needed, and then put the assembled parts in place.

Thus, I came to a question: why there is no specific label on the Lego sets being sold, like «good for two (three, four) persons» like we have for video games? It would be very useful, and probably not very difficult to define for the company.

I have even found a few posts on Reddit where people asked about sets suitable for building together:

https://www.reddit.com/r/lego/comments/31zse4/lego_sets_that_two_people_can_build/

https://www.reddit.com/r/lego/comments/nur1b8/what_is_a_good_set_for_a_couple_to_do_together/

Though it looks like some of the sets recommended just have completely separate components, with separate manuals even. I think that building together something like the mentioned Apollo Saturn rocket (with one manual) is more fun.

So, I hope that someone from Lego company will think about this niche and create more multiplayer Lego sets for us, and also explicitly labels such sets as the ones which could be built together!