Workspaice: Human+AI, creating together

Update: workspaice now has its own website. track future updates via www.workspaicehq.com

I’ve been working on something exciting that I can’t wait to share with you all. It’s called Workspaice, and it’s been quite a journey bringing this idea to life. I want to tell you about this project, my motivations behind it, and how I see it changing the way we create and collaborate.

Those of you that have been following my AI adventures will probably remember that 2 years ago I did a PoC for an AI that would expand its features by building its own source code. Since that time I’ve been interested in building things together with AI. But the models were too limited, or too expensive. That changed when Anthropic’s Claude 3.5 Sonnet was released. I finally found something that I could work with, cost-wise, and with good enough quality.

At its core, Workspaice is a locally-run application that brings together human creativity and AI assistance. It’s not just another code generator or project management tool. Instead, it’s a flexible workspace where you can create almost anything – from software applications to educational content, and beyond.

The Power of Local-First

One thing that was really important to me was making Workspaice run locally on your own computer. In a world where everything seems to be moving to the cloud, I wanted to create something that prioritized privacy and speed. Plus, there’s something comforting about knowing your work and ideas are right there on your machine, not floating somewhere in the digital ether. Besides, the AI will make a very intensive use of locally available tools and system commands to get the job done.

Beyond Software Development

While Workspaice can certainly help with coding (and does it quite well, I might add), I’ve been amazed at how versatile it’s become. In the demo video I created, I showcase three very different projects:

  1. A desktop app for audio transcription (using an API)
  2. A web app with a database backend
  3. A homeschooling guide for summer activities for kids

This variety wasn’t just for show – it represents the real flexibility I wanted to build into Workspaice. Whether you’re a developer, educator, writer, or just someone with a cool idea, Workspaice is designed to be your creative partner.

Working alongside an AI in Workspaice is a unique experience. It’s not about the AI taking over or doing the work for you. Instead, it’s a collaborative process where you can bounce ideas back and forth, refine concepts, and iteratively improve your work. It’s like having a knowledgeable colleague always ready to brainstorm or lend a hand, but one who never gets tired or needs a coffee break!

I recently recorded a 57-minute video demonstrating Workspaice in action. I decided to keep it uncut to show the real-time process, warts and all (there’s an EPIC FAIL in it as well, but I won’t spoil the surprise). It’s not always lightning-fast, and there are moments of contemplation and problem-solving. But that’s the reality of creation, isn’t it? If you’re curious, you can check it out here (don’t worry, I’ve added timestamps for the highlights so you can safely skip ahead if you don’t have 57minutes to spare 😉 ).

Looking Ahead

Workspaice is still a prototype, a proof of concept, but it’s a fully functional one that I’m proud of. I’ve submitted it as my entry to Anthropic’s Build with Claude contest, which has been an exciting opportunity to showcase what’s possible.

I’m excited about the potential of Workspaice, but even if it doesn’t work out (whatever that means), it’s already quite useful to me!

Solving randomly failing tests in Laravel

This was probably one of the most frustrating issues I’ve dealt in recent times. And finally, after many hours thrown at it, I finally found a solution.

The Problem

We have a suite of around 700 backend tests in our Laravel application. We use PHPUnit and Paratest to speed up the testing by spawning parallel processes.

At some point in the past, our GitHub job that ran the tests began to fail in a seemingly random manner. At first, we looked into differences in environment settings, trying to replicate the same context but when we ran the tests individually, they always passed.

Actually, we noticed that if we just re-run the job, the test would pass. And sometimes, a totally different and unrelated test would fail.

As our test suite grew, this problem became more and more frequent up to the point of having to trigger re-runs 2 or 3 times for every PR just to have the tests pass.

But one thing was clear, the tests failed due to having bad data in the DB. How could that happen? Every test seeded its own data, so the only explanation was if the data was leaking between tests.

But why? If each process has its own separate Database, and each test seeds or creates its data, how was it possible for data to leak?

I spent many hours experimenting with the different traits that Laravel offers, that makes the database seeding and preparing work differently. I tried them all, RefreshDatabases, DatabaseTransaction, DatabaseMigrations,… you name it.

I kept experimenting with many ideas people would throw in their replies, sometimes with a small glimmer of hope when the whole test suite would pass. Only to be disappointed when doing a second run and getting 5 failures out of the blues.

I looked into many pages of Google results, stack overflow, Reddit… even posted my own threads in Laracasts’ discussion and subreddit. I tried all the tips. Nothing worked. (Well, one thing did work. By using process isolation we could get rid of the issue, but it also meant losing the advantage we had by running the tests in parallel. So it wasn’t really a great solution.)

Finally, when I was getting very close to giving up on this (at least for a few weeks to regain some sanity), while I was trying a lot of custom code to replace some internals, I bumped into a strange PDO error message which I hadn’t seen before. (sorry, I forgot to write it down so I can’t remember what it was now). I used that to continue some more searches and eventually ended up in a bug report which, although unrelated to my problem, had somewhere in its comments the final missing piece for my puzzle.

And the funny thing is that I even had bumped into this issue before in a totally unrelated problem, but I never connected the dots!

So what was it?

In MySQL, TRUNCATE is not really possible to do inside a database transaction. Or, it is possible but it messes up the transaction. From the MySQL docs:

Truncate operations cause an implicit commit, and so cannot be rolled back.

I dealt with a related problem a few weeks ago and had to replace the truncate with a (slower) delete. Then I connected the dots. We must have some truncates somewhere in our tests, and when it hits the truncates, the results will be messed up for the next test. As the order of the tests is not always the same, this would explain why different tests would fail in different runs. It just depended on when the truncates would execute.

So I searched all the tests code with truncates in them. Found 3 different files. Replace them with queries using deletes. Ran the full suite, and everything passed! Ran it again, and again, and again. Always green. Made a PR to have GH run it too. Passed. Re-run to be sure. Passed!

Finally, it was solved.

I usually never write these kind of posts. But I wish someone had written it when I was looking for a solution. So I hope my post will eventually help someone in the future!

Journalling is great. But I failed every time I tried.

UPDATE: this project was discontinued

I lost track of how many times I started a new daily journal, with or without some special journalling methodology. The benefits of journaling regularly are well-known. Many famous personalities and great people also kept a daily diary of some sort. And I don’t even need convincing, I really do like to write my thoughts, things that happened during the day, favorite quotes, or things learned.

It’s just that every single time I tried, I ended up not being able to keep the habit after a few days or weeks.

My most recent attempt was with the very famous Bujo. I read about and watched countless videos on how-tos and inspiration. Yes, even got some colorful pens and spent time decorating some of the most important pages. It was great.

Then it fell behind, like all my previous attempts did.

But this time I was especially frustrated with this. Why can’t I keep it going? I don’t usually have problems keeping up with new habits when I’m intrinsically motivated to do so.

So I thought that this time I would go to the bottom of this. What’s preventing me from continuing with this habit?

I realized it boiled down to very simple things:

  • it takes too long to maintain/write
  • it wasn’t available at the right time (when I have something to write, I don’t have it with me)
  • there’s no easy and effective way to search for things that matter, with the exception of digital solutions. But those…
  • … make me spend even more time in front of the computer, which I don’t want.

Being a developer gives me this great advantage: I can scratch (some of) my itches easily.

For many months I’ve been exploring digital assistants, the use of AI to facilitate interaction, and telegram to make them available everywhere and without needing a dedicated UI.

A couple of days ago it dawned on me. Why not use these same strategies to solve my journaling problem?

I took some extra free time during this weekend and the past few nights to brainstorm and launch an MVP for a different kind of daily journal. And so Hoxe was born.

How is it solving the above problems directly?

  • I can write short messages (tweets, if you like) throughout the day
  • I can write from the web app or Telegram using a dedicated bot
  • If I don’t feel like writing, I can send a voice message and it gets transcribed
  • I can attach a photo
  • At the end of my day, AI picks up the messages and compiles them into one nice daily journal entry (with the added benefit of fixing spelling mistakes, or voice recording flaws)
  • Each daily post gets its own semantic meaning (embedding), which allows me to search for specific stuff easily.
  • Images also get “indexed” by AI, and text information is extracted.

I have a few more planned features to improve it, but I also prioritize keeping it simple and fast. Getting everything out of my way enables the journalling habit to happen more easily.

Looking forward to getting feedback from potential users!

AI minds and the ‘inner loop’

Back in late 2022, I started working on my pet project codenamed ‘Armin’ (for ‘artificial mind’). It was all about creating an AI agent that would have some real mind-like faculties. Mind you, this was pre-chatGPT, so I was using the good old completion models, aka Davinci-003. I did a series of videos on the development of Armin until eventually my motivation dwindled as a lot of things changed in the AI LLM scene and I also felt kinda lost on how to proceed.

Although I’ve mostly been on the sidelines for the past 1.5 years, I’ve always kept a close monitoring of the new stuff getting released, new models and capabilities.

Last month I finally decided to pick up and resume a project that branched from Armin. It’s an AI personal digital assistant, that lives as a telegram bot (because that’s where I feel an AI assistant would be useful and easily reachable from anywhere).

With all the new stuff that has been coming out, I’ve managed to quickly get it up to a good level of quality using gpt4-turbo, whisper (so that I can “speak” via telegram voice messages), and gpt4-vision (so that I can send photos).

With all that boilerplate out of the way, I finally began dipping my toes on the crucial part that motivated me to start Armin in the first place: the inner loop.

The Inner Loop

Nowadays there are thousands of people using ChatGPT (or similar) models to build chatbots and all kinds of AI assistants. They all suffer from the same problem: they feel too much like an artificial chatbot. They reply when you ask a question, and that’s it. Sure, they can take a complex question or request, browse for you, call APIs, etc. But in the end, it’s always a call-and-response thing.

For me, a truly “alive” assistant would have to be much more than that. It needs to be pro-activate, needs to be aware of everything that is happening with my life (that I decided to share), needs to reflect on previous conversations and be able to put all of this together and come up with new ideas and take initiative to do its own actions or to ask/tell me something. All this has to happen without the user asking it to do so.

To achieve this, I began implementing the “inner loop”.

The inner loop has a modified system prompt that instructs the model on what it is supposed to do and how it differs from the “chat” part of the engine. I feed it a larger prompt with more context than usual and then let the AI “think” about it.

Together with function calling (or usage of tools), and the chaining of multiple messages, these newer models are now very capable of producing very satisfying results.

I’ve been using gpt4-turbo, mostly because of habit, but with today’s news on Anthropic Claude models also supporting function calling, I’m going to re-work some of my code to try it out as well. One of the problems of running an inner loop, is that it makes your API usage go high very fast so the lower costs of Claude will be very welcome for a hobbyist like me.

Here’s a sample response of what an Inner Loop message looks like

Based on the provided information:
- You have an event at 19:00 today for "Tennis".
- You were reminded to fetch and send the daily agenda at 7:00 and 8:00 this morning. At 8:00 I informed you that your agenda had already been shared.
- At 8:40 you provided your main tasks for today - go to the supermarket, do laundry, cook lunch. This was added as a fact.
- At 9:00 you mentioned feeling frustrated trying to figure out a bug in your code. I offered to help or provide a distraction if needed.
- At 10:56 you said you had a feeling you might be forgetting something. I checked and there were no other reminders, just the tasks you had listed earlier.
- At 11:10 you asked me to remind you about doing the laundry around 14:00, which I set a reminder for.

I don't have any other outstanding tasks, events or information that needs my immediate attention based on what has been provided so far.

The next advisable time to trigger the thinking process would be:
[2024-04-05 13:30:00]

This gives enough buffer before the 14:00 laundry reminder to check if any other context is needed and prepare accordingly.

Because the inner loop has access to the same(or more) functions, it can add new things (like reminders) as it sees fit, or even fix wrong info stored by the chat engine.

The result of the inner loop is fed to itself again and again, until the AI decides there’s nothing else to think or do.

As you can see, I let the thinking process also set its own time for the next “thinking trigger”. But I also change it manually, in case the user initiates a conversation, moving it closer in time. Otherwise, it is set to trigger every 30 minutes.

Until now I’ve been storing reminders and tasks in specific database tables with their corresponding models in code. But since the beginning, I felt that this way or working was a kind of cheat. I don’t want dedicated tables for stuff, I want it to be able to manage that information, carry it around, store it and retrieve it more naturally, and use it when appropriate. The inner loop seems to finally be the solution for that.

Hopefully, more news soon!*


* I’ll try to take less than a year before the next update

25 lessons from Rory Sutherland

Stolen from a LinkedIn post.

1. A flower is a weed with an advertising budget.

2. Consumer research is great at telling you what people did, it’s terrible at telling you what people will do.

3. To reach intelligent answers, you often need to ask really dumb questions.

4. Highly targeted advertising merely finds customers: less well-targeted advertising can actually create customers.

5. Trust grows at the speed of a coconut tree and falls at the speed of a coconut.

6. The opposite of a good idea can also be a good idea.

7. The best ideas do not emerge within disciplines, they emerge at the intersections between them.

8. Never call a behavior irrational until you really know what the person is trying to do.

9. Solving problems using rationality is like playing golf with only one club.

10. If we allow the world to be run by logical people, we will only discover logical things.

11. The trouble with market research is that people don’t think what they feel, they don’t say what they think, and they don’t do what they say.

12. What gets mismeasured gets mismanaged.

13. The human mind does not run on logic any more than a horse runs on petrol.

14. Not everything that makes sense works, and not everything that works makes sense.

15. Google understood that if you’re just a search engine and nothing else — people assume you’re a very, very good search engine.

16. It is much easier to be fired for being illogical than it is for being unimaginative. The fatal issue is that logic always gets you to exactly the same place as your competitors.

17. Evolution is like a brilliant uneducated craftsman: what it lacks in intellect it makes up for in experience.

18. Test counterintuitive things only because no one else will.

19. Once you free yourself from the need to arrive at a solution through logical steps, the world becomes messier, but the solution space becomes 20x bigger.

20. For a business to be truly customer-focused, it needs to ignore what people say. Instead it needs to concentrate on what people feel.”

21. It’s not enough to be right, you have to be persuasively right.

22. Don’t design for efficiency. Design for laziness.

23. We need to move from a world that solves for averages to one that solves for individuals.

24. All big data comes from the same place: the past. Yet a single change in context can change human behavior significantly.

25. If you never do anything differently, you’ll reduce your chances of enjoying lucky accidents.

Why I Keep My Kids Away from AI (For Now)

As a tech enthusiast and a parent, I often find myself exploring the intersection of technology, parenting, and education. Artificial intelligence, particularly large language models like the now-famous ChatGPT, has been making headlines for its potential in various applications, including education. While I am an ardent supporter of AI, I believe that we should approach new technology with caution, especially when it comes to our youngest children. At very young ages, the impact of both the “what” and the “how” is significant on brain development, and it’s likely that we cannot fully grasp the potential positive or negative consequences of certain choices.

There’s no denying that AI has come a long way in recent years. We’ve seen the creation of incredible tools that can produce stories, animate children’s drawings, and much more. These advancements have even allowed for heartwarming collaborations, such as the father who co-authored an entire book with his child, both in text and illustration, using AI.

While these developments are indeed inspiring, I can’t help but wonder if we’re skipping crucial steps in our understanding of what we’re doing. By relying heavily on AI, are we inadvertently stunting our children’s development of certain skills or cognitive abilities?

The Amish have a unique approach to technology, where they carefully assess the impact of new tech on their community and way of life before adopting it on a larger scale. I believe we can learn from their mindset, especially when considering the introduction of AI into our children’s lives.

I thought about writing this post when today I discovered my 7-year-old daughter using my old laptop (which she’s allowed to use for work and research purposes). I was curious about was she was doing because most of the time she asks me for help when she wants to use it. To my surprise, she had opened the word processor and started typing her own short story. A big title “The Magical Night” was on top of the page. This moment made me realize the importance of nurturing creativity and self-expression in our children, without the influence of AI.

Though I continue to be a strong advocate for AI and its potential benefits, I choose to keep my kids away from AI for now. I believe in giving them the opportunity to explore their own creativity and develop essential skills without the shortcuts that AI might provide. Every other day, I am amazed by the creativity my 4-year-old can spur out of her mind through her drawings and collages. Introducing such an amazing and absorbing tool as AI might unintentionally limit growth and exploration, which is a risk I am not willing to take.

Fact or Myth: playing video games while sick is bad for your kids

A couple of days ago I found an interesting post on my country’s subreddit, where people shared the most common childhood myths they remember growing up with. These were things that our parents, grandparents, and uncles, would say to us to discourage certain things. It was a fun read because I was familiar with most of them. I don’t know how popular these are in other places, but they seemed quite common throughout Portugal.

A few of my favorites were:

  • don’t swim/take a bath after eating, it can stop your digestion and you can die (wait at least 3 hours!!) – also, no icecream during that time. Addendum: if you eat anything (even a small grape) the time counter restarts 😀
  • don’t shave after eating (same reasons)
  • don’t swallow gum, it will glue to your stomach and kill you (funny how so many things kill you)
  • Eating oranges at night will make you sick (or, again, kill you)
  • Catching cold or rain will make you sick
  • Don’t drink water with melon
  • Getting a university degree will set you up for life (ok, dark humor on this one)

Another one I dealt with quite a few times when I was younger, was the fact that when I was sick, it was forbidden to watch tv or play video games because I wouldn’t recover as well as if I just rested.

Now, I am pretty sure many of these “myths” have some truth in them, even though most are probably a bit too exaggerated just to help get the point across. But I was curious about the relationship between screen time and recovering from a cold.

As a kid, I loved staying at home. Getting sick meant not going to school and staying at home to do whatever I wanted to do. I understand that, from my parent’s perspective, if I was allowed to enjoy and have fun while sick, I might end up getting “sick” more often 😉 So, how much truth is in that?

This issue recently popped up because of my own daughter getting sick and having a fever. While I was on the couch playing a video game with my older daughter, the younger, sick, sibling was next to me also watching the tv and wanting to play.

Fever is something that usually doesn’t scare me. More important than measuring a number (is it bad if it’s 38.5C? what about 38.0? or 39?), is the state the person is in. I’ve witnessed my own kids being perfectly fine and playful with high 38s, and, on other occasions, being more prostrated and weak with lower temperatures. Common sense and good observation should prevail here, imho, instead of a cold, numerical analysis.

So, if you consider that you are feeling well (even though recovering from sickness), is screen time where you are having fun, a bad thing? Does it hurt or slow-down recovery?

I decided I wanted to address this doubt and come to the bottom of it.

For my own research, I tried different search terms (and search engines) to land on different pages of opposing views. Because, as we all know (or should), it’s quite easy to find content that you want to find (the so-called confirmation bias).

I am making a distinction between playing video games and watching TV. I tend to prefer video games to TV because TV is a very passive activity that creates a more “numb” state. We do allow our kids to watch TV, but only a pre-selected set of cartoons or shows that we find positive/educational and only a limited set of time (30-40min max). On the other hand, video games (the good ones, of course), are active, they stimulate the brain, develop skills, involve you being part of a story, and can even make you move! (yes, I just got a Switch with some cool physical games).

I tried to get information from a varied set of sources, from the mom-and-pop blog to medical journals. I also browsed quite a few discussion forums where people would ask this same question (I am sick with X, can I play games?) and others would reply based on their own experience. This was interesting because you get to see how the results vary so much from person to person. Some with a straight ‘NO’ and others with the extreme opposite. I found this reply quite funny:

“I have an open stomach right now with dressing covering it and here I am playing Spec Ops: The Line
So yes, ALWAYS.”

Let me then distill all that I could find, in the way I have summarized it in my head (feel free to rebuke if you disagree, but back it up ;))

  • There’s nothing inherently wrong with having sick people (kids or not) playing active and positive video games
  • In many cases, these are even beneficial as they can help deal with pain or go through boring times at home (especially when you are stuck for several days!)
  • Games provide a way to keep an engaged, active brain, learning and developing skills. Softer or calmer games can provide an environment to relax and provide some psychological “comfort” during troublesome times.
  • The main “cons” of video games during sickness are not about the games themselves, but the dangers of losing touch with important physical needs (sleep, rest, hydration). The fault here is the lack of proper parenting and supervision, not the video games. This is where kids need help because they can easily get absorbed in something they really like and lose track of reality. Make sure they are resting at appropriate times (depending on the type of sickness and age), drinking a lot, and eating healthy. In other words, as a parent, pay attention. Video games are not a nanny 🙂
  • If you trust your child, let it also guide you on what is ok or not. A truly sick child with a bad headache will hardly want to be staring at a tv.

To finish off here is another comment from a forum. I think it sums it up quite well and brings us back to my initial observation on how to evaluate how bad a fever really is:

“Actually it is like a sickness level indicator for me, “I feel so bad that I cannot even play video games” or “I only need to rest a bit, might as well play video games while resting.”

Bonus: Can sitting too close to the TV damage your eyes? “The TV myth may have started in the 1960s, and at that time, it may have been true. Some early color TV sets emitted high amounts of radiation that could have caused eye damage, but this problem has long been remedied, and today’s TV and computer monitors are relatively safe”. The issue is how many hours you watch it, and what other activities your eyes do, not how close or how far you are from the screen.

Some references from my research:

October in Review

October was a “disaster” if I would rate it by the standards I had set in place in September. But I’m giving myself some slack here since lots of things have been going on.

I started a new job at a different company, and that, by itself, was a big thing. Well, half because of the new job and half because of leaving the old job. Turns out I get attached to people really easily and it’s hard for me to let go. I guess people in my field are used to switching regularly, but for me, being relatively new to this “job” thing, changing teams felt a bit awkward.

(more…) “October in Review”

September in Review

What I read this month

Four Thousand Weeks made it to the top of my all-time favorite books. I’ll need to write it it’s own post.

Random Interesting Links

AI that expands its features by writing its own source code

When I finished reading David Shapiro’s “Natural Language Cognitive Architecture”, I got very excited with GPT3 because I finally grasped how powerful a LLM (large language AI model) can be. David’s contributions to the OpenAI community and his youtube videos have helped fuel my interest and desire to experiment with things for myself as well.

After many months of playing with the OpenAI playground, I decided it was time to start building something more serious. I identified 3 goals that would be worth exploring and developing:

  1. an AI agent with proper memory, layers of detail, summarization, etc
  2. the capability of fetching new and updated knowledge from the outside world (using the internet)
  3. give AI the possibility of expanding its features by writing its own source code

I decided to go with number 3 because it sounded to me the most challenging, interesting, and perhaps less explored option.

(more…) “AI that expands its features by writing its own source code”