For years, I was trapped in a cycle of ambitious beginnings and disappointing endings. My GitHub repository had become a digital graveyard of half-completed projects—enthusiastic starts abandoned at the first sign of a significant challenge. But over the past few months, something remarkable has happened: I’m actually finishing what I start, and the catalyst wasn’t a new productivity system or time management technique. It was AI.

A Little Background

Before diving into my productivity transformation, it helps to understand where I’m coming from. I’m a chemist by training, working in a government position while also collaborating on research projects at the local university. I don’t have a formal IT or software development background, but I’ve been increasingly drawn to data science projects that intersect with my professional work.

Over the past few months, I’ve been on a journey to find the perfect code editor that balances excellent developer experience with the productivity boost of AI assistance. This exploration came after I had already spent almost two years using VS Code, which I adopted after ditching Emacs and Neovim in search of a more modern editing experience. My latest search led me through several modern editors, primarily those in the VSCodium family, with some interesting detours along the way. Here’s my experience and what I’ve learned.

Anthropic recently published a fascinating paper with an unusual title: “On the Biology of a Large Language Model.” But what does biology have to do with AI? As it turns out, quite a lot. The researchers are essentially performing a digital dissection of Claude’s “brain” to understand how it thinks—and finding surprising parallels to biological systems along the way.

In this post, I’ll break down this complex research into digestible parts, explaining how scientists are starting to understand what’s happening inside these AI systems when they answer our questions or write poetry.

The Brazilian National Institute of Industrial Property (INPI) is embarking on a significant transformation of its patent services. A recent presentation detailed plans to replace the current web search system with a comprehensive, unified platform designed to streamline the entire patent process. This initiative promises to enhance efficiency, reduce user errors, and improve the overall experience for patent applicants and stakeholders.

Current Challenges in the Brazilian Patent System

Currently, the INPI’s patent system relies on several disconnected systems. These fragmented systems handle various stages, including application submission, GRU generation (payment slips), process consultation, filing submissions and requirement compliance, and internal examination stages (formality, technical aspects, nullity, appeals, etc.). This lack of integration often leads to duplicated effort and user confusion due to unfamiliar interfaces, complex instructions, and technical jargon in official communications.

We’ve all been there: headphones on, music pumping, fingers flying across the keyboard, lost in the “flow” with your favorite AI agent. This, my friends, is vibe coding. It’s when you’re in the zone, seemingly effortlessly producing code.

It’s the idea that you can create great software simply by immersing yourself in the feeling of coding, trusting your intuition and riding the wave of inspiration. But lately, I’ve realized that for me, at least, the vibe is…off. It’s like I’m watching an AI agent code for me, occasionally chiming in with a suggestion or a correction, but often just observing the code unfold without fully grasping the intricacies of what’s happening can lead to wasting my time later.

So, I was watching this video the other day, and it got me thinking… you know, about how everything’s changing with AI. It seems like the old ways of doing things in software are just not cutting it anymore.

Remember how companies used to try and, like, trap you in their ecosystem? Make it impossible to leave? That’s software lock-in, and honestly, I think AI is making that a thing of the past. I could be wrong, but it doesn’t make sense anymore to pay for yearly plans anymore for most of the things that are appearing in AI. I mean, every week we have something new in the pipeline.

I needed an easy and cheap option to integrate my vault with artificial intelligence. The easiest option could be to pay for subscriptions, which would be a high cost for me, since I am would not use the service that often to justify. Another option would be to pay for a Cloud GPU service to run big queries that would be unfeasible to run locally. This option seemed too cumbersome for my case. Eventually I discovered OpenRouter, which seems to be the easiest to solution because I can access multiple models at a single place and also have a API that I can connect to other services.

For years, I was trapped in a cycle of ambitious beginnings and disappointing endings. My GitHub repository had become a digital graveyard of half-completed projects—enthusiastic starts abandoned at the first sign of a significant challenge. But over the past few months, something remarkable has happened: I’m actually finishing what I start, and the catalyst wasn’t a new productivity system or time management technique. It was AI.

A Little Background

Before diving into my productivity transformation, it helps to understand where I’m coming from. I’m a chemist by training, working in a government position while also collaborating on research projects at the local university. I don’t have a formal IT or software development background, but I’ve been increasingly drawn to data science projects that intersect with my professional work.

Over the past few months, I’ve been on a journey to find the perfect code editor that balances excellent developer experience with the productivity boost of AI assistance. This exploration came after I had already spent almost two years using VS Code, which I adopted after ditching Emacs and Neovim in search of a more modern editing experience. My latest search led me through several modern editors, primarily those in the VSCodium family, with some interesting detours along the way. Here’s my experience and what I’ve learned.

For years, I was trapped in a cycle of ambitious beginnings and disappointing endings. My GitHub repository had become a digital graveyard of half-completed projects—enthusiastic starts abandoned at the first sign of a significant challenge. But over the past few months, something remarkable has happened: I’m actually finishing what I start, and the catalyst wasn’t a new productivity system or time management technique. It was AI.

A Little Background

Before diving into my productivity transformation, it helps to understand where I’m coming from. I’m a chemist by training, working in a government position while also collaborating on research projects at the local university. I don’t have a formal IT or software development background, but I’ve been increasingly drawn to data science projects that intersect with my professional work.

Over the past few months, I’ve been on a journey to find the perfect code editor that balances excellent developer experience with the productivity boost of AI assistance. This exploration came after I had already spent almost two years using VS Code, which I adopted after ditching Emacs and Neovim in search of a more modern editing experience. My latest search led me through several modern editors, primarily those in the VSCodium family, with some interesting detours along the way. Here’s my experience and what I’ve learned.

We’ve all been there: headphones on, music pumping, fingers flying across the keyboard, lost in the “flow” with your favorite AI agent. This, my friends, is vibe coding. It’s when you’re in the zone, seemingly effortlessly producing code.

It’s the idea that you can create great software simply by immersing yourself in the feeling of coding, trusting your intuition and riding the wave of inspiration. But lately, I’ve realized that for me, at least, the vibe is…off. It’s like I’m watching an AI agent code for me, occasionally chiming in with a suggestion or a correction, but often just observing the code unfold without fully grasping the intricacies of what’s happening can lead to wasting my time later.

For years, I was trapped in a cycle of ambitious beginnings and disappointing endings. My GitHub repository had become a digital graveyard of half-completed projects—enthusiastic starts abandoned at the first sign of a significant challenge. But over the past few months, something remarkable has happened: I’m actually finishing what I start, and the catalyst wasn’t a new productivity system or time management technique. It was AI.

A Little Background

Before diving into my productivity transformation, it helps to understand where I’m coming from. I’m a chemist by training, working in a government position while also collaborating on research projects at the local university. I don’t have a formal IT or software development background, but I’ve been increasingly drawn to data science projects that intersect with my professional work.

For years, I was trapped in a cycle of ambitious beginnings and disappointing endings. My GitHub repository had become a digital graveyard of half-completed projects—enthusiastic starts abandoned at the first sign of a significant challenge. But over the past few months, something remarkable has happened: I’m actually finishing what I start, and the catalyst wasn’t a new productivity system or time management technique. It was AI.

A Little Background

Before diving into my productivity transformation, it helps to understand where I’m coming from. I’m a chemist by training, working in a government position while also collaborating on research projects at the local university. I don’t have a formal IT or software development background, but I’ve been increasingly drawn to data science projects that intersect with my professional work.

For years, I was trapped in a cycle of ambitious beginnings and disappointing endings. My GitHub repository had become a digital graveyard of half-completed projects—enthusiastic starts abandoned at the first sign of a significant challenge. But over the past few months, something remarkable has happened: I’m actually finishing what I start, and the catalyst wasn’t a new productivity system or time management technique. It was AI.

A Little Background

Before diving into my productivity transformation, it helps to understand where I’m coming from. I’m a chemist by training, working in a government position while also collaborating on research projects at the local university. I don’t have a formal IT or software development background, but I’ve been increasingly drawn to data science projects that intersect with my professional work.

Over the past few months, I’ve been on a journey to find the perfect code editor that balances excellent developer experience with the productivity boost of AI assistance. This exploration came after I had already spent almost two years using VS Code, which I adopted after ditching Emacs and Neovim in search of a more modern editing experience. My latest search led me through several modern editors, primarily those in the VSCodium family, with some interesting detours along the way. Here’s my experience and what I’ve learned.

For years, I was trapped in a cycle of ambitious beginnings and disappointing endings. My GitHub repository had become a digital graveyard of half-completed projects—enthusiastic starts abandoned at the first sign of a significant challenge. But over the past few months, something remarkable has happened: I’m actually finishing what I start, and the catalyst wasn’t a new productivity system or time management technique. It was AI.

A Little Background

Before diving into my productivity transformation, it helps to understand where I’m coming from. I’m a chemist by training, working in a government position while also collaborating on research projects at the local university. I don’t have a formal IT or software development background, but I’ve been increasingly drawn to data science projects that intersect with my professional work.

Over the past few months, I’ve been on a journey to find the perfect code editor that balances excellent developer experience with the productivity boost of AI assistance. This exploration came after I had already spent almost two years using VS Code, which I adopted after ditching Emacs and Neovim in search of a more modern editing experience. My latest search led me through several modern editors, primarily those in the VSCodium family, with some interesting detours along the way. Here’s my experience and what I’ve learned.

Over the past few months, I’ve been on a journey to find the perfect code editor that balances excellent developer experience with the productivity boost of AI assistance. This exploration came after I had already spent almost two years using VS Code, which I adopted after ditching Emacs and Neovim in search of a more modern editing experience. My latest search led me through several modern editors, primarily those in the VSCodium family, with some interesting detours along the way. Here’s my experience and what I’ve learned.

Over the past few months, I’ve been on a journey to find the perfect code editor that balances excellent developer experience with the productivity boost of AI assistance. This exploration came after I had already spent almost two years using VS Code, which I adopted after ditching Emacs and Neovim in search of a more modern editing experience. My latest search led me through several modern editors, primarily those in the VSCodium family, with some interesting detours along the way. Here’s my experience and what I’ve learned.

I’ve been using GitButler for about two weeks now, and it’s already transformed how I interact with Git. As someone who regularly juggles multiple feature branches and context switches between tasks, I was looking for a tool that could simplify my Git workflow. GitButler caught my attention with its promise of virtual branches and simplified collaboration features.

My interest was further piqued after watching presentations by Scott Chacon, one of GitButler’s creators and also a co-founder of GitHub. His deep knowledge of Git is evident in talks like this one, and it shows in how GitButler has managed to create an almost frictionless Git experience.

I’ve been using GitButler for about two weeks now, and it’s already transformed how I interact with Git. As someone who regularly juggles multiple feature branches and context switches between tasks, I was looking for a tool that could simplify my Git workflow. GitButler caught my attention with its promise of virtual branches and simplified collaboration features.

My interest was further piqued after watching presentations by Scott Chacon, one of GitButler’s creators and also a co-founder of GitHub. His deep knowledge of Git is evident in talks like this one, and it shows in how GitButler has managed to create an almost frictionless Git experience.

I’ve been using GitButler for about two weeks now, and it’s already transformed how I interact with Git. As someone who regularly juggles multiple feature branches and context switches between tasks, I was looking for a tool that could simplify my Git workflow. GitButler caught my attention with its promise of virtual branches and simplified collaboration features.

My interest was further piqued after watching presentations by Scott Chacon, one of GitButler’s creators and also a co-founder of GitHub. His deep knowledge of Git is evident in talks like this one, and it shows in how GitButler has managed to create an almost frictionless Git experience.

I’ve been using GitButler for about two weeks now, and it’s already transformed how I interact with Git. As someone who regularly juggles multiple feature branches and context switches between tasks, I was looking for a tool that could simplify my Git workflow. GitButler caught my attention with its promise of virtual branches and simplified collaboration features.

My interest was further piqued after watching presentations by Scott Chacon, one of GitButler’s creators and also a co-founder of GitHub. His deep knowledge of Git is evident in talks like this one, and it shows in how GitButler has managed to create an almost frictionless Git experience.

I’ve been using GitButler for about two weeks now, and it’s already transformed how I interact with Git. As someone who regularly juggles multiple feature branches and context switches between tasks, I was looking for a tool that could simplify my Git workflow. GitButler caught my attention with its promise of virtual branches and simplified collaboration features.

My interest was further piqued after watching presentations by Scott Chacon, one of GitButler’s creators and also a co-founder of GitHub. His deep knowledge of Git is evident in talks like this one, and it shows in how GitButler has managed to create an almost frictionless Git experience.

I’ve been using GitButler for about two weeks now, and it’s already transformed how I interact with Git. As someone who regularly juggles multiple feature branches and context switches between tasks, I was looking for a tool that could simplify my Git workflow. GitButler caught my attention with its promise of virtual branches and simplified collaboration features.

My interest was further piqued after watching presentations by Scott Chacon, one of GitButler’s creators and also a co-founder of GitHub. His deep knowledge of Git is evident in talks like this one, and it shows in how GitButler has managed to create an almost frictionless Git experience.

Anthropic recently published a fascinating paper with an unusual title: “On the Biology of a Large Language Model.” But what does biology have to do with AI? As it turns out, quite a lot. The researchers are essentially performing a digital dissection of Claude’s “brain” to understand how it thinks—and finding surprising parallels to biological systems along the way.

In this post, I’ll break down this complex research into digestible parts, explaining how scientists are starting to understand what’s happening inside these AI systems when they answer our questions or write poetry.

Anthropic recently published a fascinating paper with an unusual title: “On the Biology of a Large Language Model.” But what does biology have to do with AI? As it turns out, quite a lot. The researchers are essentially performing a digital dissection of Claude’s “brain” to understand how it thinks—and finding surprising parallels to biological systems along the way.

In this post, I’ll break down this complex research into digestible parts, explaining how scientists are starting to understand what’s happening inside these AI systems when they answer our questions or write poetry.

We’ve all been there: headphones on, music pumping, fingers flying across the keyboard, lost in the “flow” with your favorite AI agent. This, my friends, is vibe coding. It’s when you’re in the zone, seemingly effortlessly producing code.

It’s the idea that you can create great software simply by immersing yourself in the feeling of coding, trusting your intuition and riding the wave of inspiration. But lately, I’ve realized that for me, at least, the vibe is…off. It’s like I’m watching an AI agent code for me, occasionally chiming in with a suggestion or a correction, but often just observing the code unfold without fully grasping the intricacies of what’s happening can lead to wasting my time later.

Anthropic recently published a fascinating paper with an unusual title: “On the Biology of a Large Language Model.” But what does biology have to do with AI? As it turns out, quite a lot. The researchers are essentially performing a digital dissection of Claude’s “brain” to understand how it thinks—and finding surprising parallels to biological systems along the way.

In this post, I’ll break down this complex research into digestible parts, explaining how scientists are starting to understand what’s happening inside these AI systems when they answer our questions or write poetry.

Anthropic recently published a fascinating paper with an unusual title: “On the Biology of a Large Language Model.” But what does biology have to do with AI? As it turns out, quite a lot. The researchers are essentially performing a digital dissection of Claude’s “brain” to understand how it thinks—and finding surprising parallels to biological systems along the way.

In this post, I’ll break down this complex research into digestible parts, explaining how scientists are starting to understand what’s happening inside these AI systems when they answer our questions or write poetry.

Anthropic recently published a fascinating paper with an unusual title: “On the Biology of a Large Language Model.” But what does biology have to do with AI? As it turns out, quite a lot. The researchers are essentially performing a digital dissection of Claude’s “brain” to understand how it thinks—and finding surprising parallels to biological systems along the way.

In this post, I’ll break down this complex research into digestible parts, explaining how scientists are starting to understand what’s happening inside these AI systems when they answer our questions or write poetry.

The Brazilian National Institute of Industrial Property (INPI) is embarking on a significant transformation of its patent services. A recent presentation detailed plans to replace the current web search system with a comprehensive, unified platform designed to streamline the entire patent process. This initiative promises to enhance efficiency, reduce user errors, and improve the overall experience for patent applicants and stakeholders.

Current Challenges in the Brazilian Patent System

Currently, the INPI’s patent system relies on several disconnected systems. These fragmented systems handle various stages, including application submission, GRU generation (payment slips), process consultation, filing submissions and requirement compliance, and internal examination stages (formality, technical aspects, nullity, appeals, etc.). This lack of integration often leads to duplicated effort and user confusion due to unfamiliar interfaces, complex instructions, and technical jargon in official communications.

The Brazilian National Institute of Industrial Property (INPI) is embarking on a significant transformation of its patent services. A recent presentation detailed plans to replace the current web search system with a comprehensive, unified platform designed to streamline the entire patent process. This initiative promises to enhance efficiency, reduce user errors, and improve the overall experience for patent applicants and stakeholders.

Current Challenges in the Brazilian Patent System

Currently, the INPI’s patent system relies on several disconnected systems. These fragmented systems handle various stages, including application submission, GRU generation (payment slips), process consultation, filing submissions and requirement compliance, and internal examination stages (formality, technical aspects, nullity, appeals, etc.). This lack of integration often leads to duplicated effort and user confusion due to unfamiliar interfaces, complex instructions, and technical jargon in official communications.

The Brazilian National Institute of Industrial Property (INPI) is embarking on a significant transformation of its patent services. A recent presentation detailed plans to replace the current web search system with a comprehensive, unified platform designed to streamline the entire patent process. This initiative promises to enhance efficiency, reduce user errors, and improve the overall experience for patent applicants and stakeholders.

Current Challenges in the Brazilian Patent System

Currently, the INPI’s patent system relies on several disconnected systems. These fragmented systems handle various stages, including application submission, GRU generation (payment slips), process consultation, filing submissions and requirement compliance, and internal examination stages (formality, technical aspects, nullity, appeals, etc.). This lack of integration often leads to duplicated effort and user confusion due to unfamiliar interfaces, complex instructions, and technical jargon in official communications.

The Brazilian National Institute of Industrial Property (INPI) is embarking on a significant transformation of its patent services. A recent presentation detailed plans to replace the current web search system with a comprehensive, unified platform designed to streamline the entire patent process. This initiative promises to enhance efficiency, reduce user errors, and improve the overall experience for patent applicants and stakeholders.

Current Challenges in the Brazilian Patent System

Currently, the INPI’s patent system relies on several disconnected systems. These fragmented systems handle various stages, including application submission, GRU generation (payment slips), process consultation, filing submissions and requirement compliance, and internal examination stages (formality, technical aspects, nullity, appeals, etc.). This lack of integration often leads to duplicated effort and user confusion due to unfamiliar interfaces, complex instructions, and technical jargon in official communications.

The Brazilian National Institute of Industrial Property (INPI) is embarking on a significant transformation of its patent services. A recent presentation detailed plans to replace the current web search system with a comprehensive, unified platform designed to streamline the entire patent process. This initiative promises to enhance efficiency, reduce user errors, and improve the overall experience for patent applicants and stakeholders.

Current Challenges in the Brazilian Patent System

Currently, the INPI’s patent system relies on several disconnected systems. These fragmented systems handle various stages, including application submission, GRU generation (payment slips), process consultation, filing submissions and requirement compliance, and internal examination stages (formality, technical aspects, nullity, appeals, etc.). This lack of integration often leads to duplicated effort and user confusion due to unfamiliar interfaces, complex instructions, and technical jargon in official communications.

The Brazilian National Institute of Industrial Property (INPI) is embarking on a significant transformation of its patent services. A recent presentation detailed plans to replace the current web search system with a comprehensive, unified platform designed to streamline the entire patent process. This initiative promises to enhance efficiency, reduce user errors, and improve the overall experience for patent applicants and stakeholders.

Current Challenges in the Brazilian Patent System

Currently, the INPI’s patent system relies on several disconnected systems. These fragmented systems handle various stages, including application submission, GRU generation (payment slips), process consultation, filing submissions and requirement compliance, and internal examination stages (formality, technical aspects, nullity, appeals, etc.). This lack of integration often leads to duplicated effort and user confusion due to unfamiliar interfaces, complex instructions, and technical jargon in official communications.

So, I was watching this video the other day, and it got me thinking… you know, about how everything’s changing with AI. It seems like the old ways of doing things in software are just not cutting it anymore.

Remember how companies used to try and, like, trap you in their ecosystem? Make it impossible to leave? That’s software lock-in, and honestly, I think AI is making that a thing of the past. I could be wrong, but it doesn’t make sense anymore to pay for yearly plans anymore for most of the things that are appearing in AI. I mean, every week we have something new in the pipeline.

I needed an easy and cheap option to integrate my vault with artificial intelligence. The easiest option could be to pay for subscriptions, which would be a high cost for me, since I am would not use the service that often to justify. Another option would be to pay for a Cloud GPU service to run big queries that would be unfeasible to run locally. This option seemed too cumbersome for my case. Eventually I discovered OpenRouter, which seems to be the easiest to solution because I can access multiple models at a single place and also have a API that I can connect to other services.

We’ve all been there: headphones on, music pumping, fingers flying across the keyboard, lost in the “flow” with your favorite AI agent. This, my friends, is vibe coding. It’s when you’re in the zone, seemingly effortlessly producing code.

It’s the idea that you can create great software simply by immersing yourself in the feeling of coding, trusting your intuition and riding the wave of inspiration. But lately, I’ve realized that for me, at least, the vibe is…off. It’s like I’m watching an AI agent code for me, occasionally chiming in with a suggestion or a correction, but often just observing the code unfold without fully grasping the intricacies of what’s happening can lead to wasting my time later.

So, I was watching this video the other day, and it got me thinking… you know, about how everything’s changing with AI. It seems like the old ways of doing things in software are just not cutting it anymore.

Remember how companies used to try and, like, trap you in their ecosystem? Make it impossible to leave? That’s software lock-in, and honestly, I think AI is making that a thing of the past. I could be wrong, but it doesn’t make sense anymore to pay for yearly plans anymore for most of the things that are appearing in AI. I mean, every week we have something new in the pipeline.

This article details a troubleshooting process for a Proxmox cluster authentication failure that prevented users from logging into the web interface. The root cause was identified as a missing /etc/pve/access.cfg file, crucial for user authentication, likely due to corosync communication issues. The problem was resolved by restarting the pve-cluster service, forcing quorum, manually creating a minimal access.cfg file, and restarting the pveproxy service. Preventative measures include regular cluster health checks, automated configuration file backups, ensuring proper shutdown procedures, maintaining network stability, monitoring storage health, applying Proxmox updates, and careful permissions management.

A really simple script for those that, for some odd reason, decided to run the Open WebUI server from inside a LXC.

The problem

I really like the interface in Proxmox and i prefer it than dealing with Portainer for some services that are more accessed. This is the case for Open WebUI, which I use daily.

The problem I faced was the update process of the service, which I knew little about. So I need to understand how the service works under the hood. In Proxmox we can use the Proxmox VE Community Scripts which are really handy, but they don’t have much documentation on how the scripts work. Because of this, the user has to go to the service documentation and learn how it works. For Open WebUI, the documentation is directed to the installetions using Docker.

The problem

This week I have been searching for solutions to use domains with my applications running in containers in my MacBook Pro server. Yes, I have converted my MacBook Pro into a server, at least for now. The first solution was to use a Pi-Hole as a local DNS and it works fine, but the problem is that I have to specify ports to get into the applications and it gets annonying. The solution seemed simple enough, create a Nginx Proxy Manager (NPM) container, use it to point to the containers in the local network and this should solve the issue. Well, that’s what I thought.

The MacBook Pro 9,2 is a model of the MacBook Pro that was released in June 2012. It has a 13.3-inch display, a 2.5 GHz or 2.9 GHz dual-core Intel Core i5 or i7 processor, 4 GB or 8 GB of RAM, and a 500 GB or 750 GB hard drive.

My MacBook was bought around 2013 or 2014, don’t remember exactly. It was bought new, with 4GB of RAM and 500 GB hard drive. At the time I already had that MacBook black, which I got around 2006 and was really becoming slow. Around 2010, or 2011, I got an iMac which was my main computer and I used less and less the notebook. So, this year it marks 10 years that I am with this MacBook and it is really a nice computer even today.

The last months have been very exciting to me. The most exciting and difficult part by far is having my newborn son, whom is almost 3 months old. The other exciting part is that I finally understood that if I really like technology I should really invest in it.

Investing more in my formation in technology right now could come as odd for most people because I already have a Masters in chemistry and a specialization in intellectual property and also happen to work in the field that I have specialized in. The main problem for me is not that I don’t like what I do but that sensation that I feel about this not being scalable enough, mainly because of the difficulty that I encountered after first leaving the university and because after so much hard work on specializing not having enough return on the investment.

This article details a troubleshooting process for a Proxmox cluster authentication failure that prevented users from logging into the web interface. The root cause was identified as a missing /etc/pve/access.cfg file, crucial for user authentication, likely due to corosync communication issues. The problem was resolved by restarting the pve-cluster service, forcing quorum, manually creating a minimal access.cfg file, and restarting the pveproxy service. Preventative measures include regular cluster health checks, automated configuration file backups, ensuring proper shutdown procedures, maintaining network stability, monitoring storage health, applying Proxmox updates, and careful permissions management.

A really simple script for those that, for some odd reason, decided to run the Open WebUI server from inside a LXC.

The problem

I really like the interface in Proxmox and i prefer it than dealing with Portainer for some services that are more accessed. This is the case for Open WebUI, which I use daily.

The problem I faced was the update process of the service, which I knew little about. So I need to understand how the service works under the hood. In Proxmox we can use the Proxmox VE Community Scripts which are really handy, but they don’t have much documentation on how the scripts work. Because of this, the user has to go to the service documentation and learn how it works. For Open WebUI, the documentation is directed to the installetions using Docker.

This article details a troubleshooting process for a Proxmox cluster authentication failure that prevented users from logging into the web interface. The root cause was identified as a missing /etc/pve/access.cfg file, crucial for user authentication, likely due to corosync communication issues. The problem was resolved by restarting the pve-cluster service, forcing quorum, manually creating a minimal access.cfg file, and restarting the pveproxy service. Preventative measures include regular cluster health checks, automated configuration file backups, ensuring proper shutdown procedures, maintaining network stability, monitoring storage health, applying Proxmox updates, and careful permissions management.

This article details a troubleshooting process for a Proxmox cluster authentication failure that prevented users from logging into the web interface. The root cause was identified as a missing /etc/pve/access.cfg file, crucial for user authentication, likely due to corosync communication issues. The problem was resolved by restarting the pve-cluster service, forcing quorum, manually creating a minimal access.cfg file, and restarting the pveproxy service. Preventative measures include regular cluster health checks, automated configuration file backups, ensuring proper shutdown procedures, maintaining network stability, monitoring storage health, applying Proxmox updates, and careful permissions management.

This is a quick fix to a problem I experienced with Open WebUI, which was that custom models were not showing in the models list. There was nothing in the documentation or in the issues pointing to a solution. I decided to open a new issue 4 days ago and today the user @dcolley gave the missing information and it worked.

For some reason, custom models are not working when you use Direct Connections. In my case, I use OpenRouter to use LLMs, so I thought the way to setup the API was from the Direct Connections menu. It turns out that you can setup the OpenRouter API from the Connections page, specifically in the OpenAI API section. And this is the solution, replicate your configuration for the API inside the OpenAI section.

This is a quick fix to a problem I experienced with Open WebUI, which was that custom models were not showing in the models list. There was nothing in the documentation or in the issues pointing to a solution. I decided to open a new issue 4 days ago and today the user @dcolley gave the missing information and it worked.

For some reason, custom models are not working when you use Direct Connections. In my case, I use OpenRouter to use LLMs, so I thought the way to setup the API was from the Direct Connections menu. It turns out that you can setup the OpenRouter API from the Connections page, specifically in the OpenAI API section. And this is the solution, replicate your configuration for the API inside the OpenAI section.

A really simple script for those that, for some odd reason, decided to run the Open WebUI server from inside a LXC.

The problem

I really like the interface in Proxmox and i prefer it than dealing with Portainer for some services that are more accessed. This is the case for Open WebUI, which I use daily.

The problem I faced was the update process of the service, which I knew little about. So I need to understand how the service works under the hood. In Proxmox we can use the Proxmox VE Community Scripts which are really handy, but they don’t have much documentation on how the scripts work. Because of this, the user has to go to the service documentation and learn how it works. For Open WebUI, the documentation is directed to the installetions using Docker.

A really simple script for those that, for some odd reason, decided to run the Open WebUI server from inside a LXC.

The problem

I really like the interface in Proxmox and i prefer it than dealing with Portainer for some services that are more accessed. This is the case for Open WebUI, which I use daily.

The problem I faced was the update process of the service, which I knew little about. So I need to understand how the service works under the hood. In Proxmox we can use the Proxmox VE Community Scripts which are really handy, but they don’t have much documentation on how the scripts work. Because of this, the user has to go to the service documentation and learn how it works. For Open WebUI, the documentation is directed to the installetions using Docker.

The problem

This week I have been searching for solutions to use domains with my applications running in containers in my MacBook Pro server. Yes, I have converted my MacBook Pro into a server, at least for now. The first solution was to use a Pi-Hole as a local DNS and it works fine, but the problem is that I have to specify ports to get into the applications and it gets annonying. The solution seemed simple enough, create a Nginx Proxy Manager (NPM) container, use it to point to the containers in the local network and this should solve the issue. Well, that’s what I thought.

A really simple script for those that, for some odd reason, decided to run the Open WebUI server from inside a LXC.

The problem

I really like the interface in Proxmox and i prefer it than dealing with Portainer for some services that are more accessed. This is the case for Open WebUI, which I use daily.

The problem I faced was the update process of the service, which I knew little about. So I need to understand how the service works under the hood. In Proxmox we can use the Proxmox VE Community Scripts which are really handy, but they don’t have much documentation on how the scripts work. Because of this, the user has to go to the service documentation and learn how it works. For Open WebUI, the documentation is directed to the installetions using Docker.

A really simple script for those that, for some odd reason, decided to run the Open WebUI server from inside a LXC.

The problem

I really like the interface in Proxmox and i prefer it than dealing with Portainer for some services that are more accessed. This is the case for Open WebUI, which I use daily.

The problem I faced was the update process of the service, which I knew little about. So I need to understand how the service works under the hood. In Proxmox we can use the Proxmox VE Community Scripts which are really handy, but they don’t have much documentation on how the scripts work. Because of this, the user has to go to the service documentation and learn how it works. For Open WebUI, the documentation is directed to the installetions using Docker.

I needed an easy and cheap option to integrate my vault with artificial intelligence. The easiest option could be to pay for subscriptions, which would be a high cost for me, since I am would not use the service that often to justify. Another option would be to pay for a Cloud GPU service to run big queries that would be unfeasible to run locally. This option seemed too cumbersome for my case. Eventually I discovered OpenRouter, which seems to be the easiest to solution because I can access multiple models at a single place and also have a API that I can connect to other services.

I needed an easy and cheap option to integrate my vault with artificial intelligence. The easiest option could be to pay for subscriptions, which would be a high cost for me, since I am would not use the service that often to justify. Another option would be to pay for a Cloud GPU service to run big queries that would be unfeasible to run locally. This option seemed too cumbersome for my case. Eventually I discovered OpenRouter, which seems to be the easiest to solution because I can access multiple models at a single place and also have a API that I can connect to other services.

It surprised me how easy it was to build a local solution with Ollama.

Introduction

This itch to have a private solution for AI came to me after I saw that OpenAI changed their settings on the playground section and does not allow for free users to test the models. With that I went to check Gemini but it was the same thing. Both of them are costing $20/month and for me it isn’t worth it at the moment. Because of that I went looking for private ones, since I had already seen people doing running AI solution locally. Coupled with the fact that I got a new M2 MacBook Air, I decided to test the limits.

The problem

This week I have been searching for solutions to use domains with my applications running in containers in my MacBook Pro server. Yes, I have converted my MacBook Pro into a server, at least for now. The first solution was to use a Pi-Hole as a local DNS and it works fine, but the problem is that I have to specify ports to get into the applications and it gets annonying. The solution seemed simple enough, create a Nginx Proxy Manager (NPM) container, use it to point to the containers in the local network and this should solve the issue. Well, that’s what I thought.

The last months have been very exciting to me. The most exciting and difficult part by far is having my newborn son, whom is almost 3 months old. The other exciting part is that I finally understood that if I really like technology I should really invest in it.

Investing more in my formation in technology right now could come as odd for most people because I already have a Masters in chemistry and a specialization in intellectual property and also happen to work in the field that I have specialized in. The main problem for me is not that I don’t like what I do but that sensation that I feel about this not being scalable enough, mainly because of the difficulty that I encountered after first leaving the university and because after so much hard work on specializing not having enough return on the investment.

The problem

This week I have been searching for solutions to use domains with my applications running in containers in my MacBook Pro server. Yes, I have converted my MacBook Pro into a server, at least for now. The first solution was to use a Pi-Hole as a local DNS and it works fine, but the problem is that I have to specify ports to get into the applications and it gets annonying. The solution seemed simple enough, create a Nginx Proxy Manager (NPM) container, use it to point to the containers in the local network and this should solve the issue. Well, that’s what I thought.

The problem

This week I have been searching for solutions to use domains with my applications running in containers in my MacBook Pro server. Yes, I have converted my MacBook Pro into a server, at least for now. The first solution was to use a Pi-Hole as a local DNS and it works fine, but the problem is that I have to specify ports to get into the applications and it gets annonying. The solution seemed simple enough, create a Nginx Proxy Manager (NPM) container, use it to point to the containers in the local network and this should solve the issue. Well, that’s what I thought.

The problem

This week I have been searching for solutions to use domains with my applications running in containers in my MacBook Pro server. Yes, I have converted my MacBook Pro into a server, at least for now. The first solution was to use a Pi-Hole as a local DNS and it works fine, but the problem is that I have to specify ports to get into the applications and it gets annonying. The solution seemed simple enough, create a Nginx Proxy Manager (NPM) container, use it to point to the containers in the local network and this should solve the issue. Well, that’s what I thought.

The problem

This week I have been searching for solutions to use domains with my applications running in containers in my MacBook Pro server. Yes, I have converted my MacBook Pro into a server, at least for now. The first solution was to use a Pi-Hole as a local DNS and it works fine, but the problem is that I have to specify ports to get into the applications and it gets annonying. The solution seemed simple enough, create a Nginx Proxy Manager (NPM) container, use it to point to the containers in the local network and this should solve the issue. Well, that’s what I thought.

The problem

This week I have been searching for solutions to use domains with my applications running in containers in my MacBook Pro server. Yes, I have converted my MacBook Pro into a server, at least for now. The first solution was to use a Pi-Hole as a local DNS and it works fine, but the problem is that I have to specify ports to get into the applications and it gets annonying. The solution seemed simple enough, create a Nginx Proxy Manager (NPM) container, use it to point to the containers in the local network and this should solve the issue. Well, that’s what I thought.

I have been using the ananke theme since the inception of this blog. But recently I started to have all sorts of problems because of my lack of understading of how the contents folder is linked to the layouts folder and to the themes/ananke folder.

/contents

So in the ananke theme you have the choice to have more than one language for your website. In my case I only need to use the english folder, which is in contents/en/ folder. Inside the contents folder, every section needs to have a _index.md file indicating that it is the main page. Every section can be represented by a folder with content inside and _index.md file as the head of the section. In my case, my posts are at contents/en/posts/. So, the contents/en/ has a _index.md folder as well as the contents/en/posts/ folder.

I have been using the ananke theme since the inception of this blog. But recently I started to have all sorts of problems because of my lack of understading of how the contents folder is linked to the layouts folder and to the themes/ananke folder.

/contents

So in the ananke theme you have the choice to have more than one language for your website. In my case I only need to use the english folder, which is in contents/en/ folder. Inside the contents folder, every section needs to have a _index.md file indicating that it is the main page. Every section can be represented by a folder with content inside and _index.md file as the head of the section. In my case, my posts are at contents/en/posts/. So, the contents/en/ has a _index.md folder as well as the contents/en/posts/ folder.

I have been using the ananke theme since the inception of this blog. But recently I started to have all sorts of problems because of my lack of understading of how the contents folder is linked to the layouts folder and to the themes/ananke folder.

/contents

So in the ananke theme you have the choice to have more than one language for your website. In my case I only need to use the english folder, which is in contents/en/ folder. Inside the contents folder, every section needs to have a _index.md file indicating that it is the main page. Every section can be represented by a folder with content inside and _index.md file as the head of the section. In my case, my posts are at contents/en/posts/. So, the contents/en/ has a _index.md folder as well as the contents/en/posts/ folder.

It surprised me how easy it was to build a local solution with Ollama.

Introduction

This itch to have a private solution for AI came to me after I saw that OpenAI changed their settings on the playground section and does not allow for free users to test the models. With that I went to check Gemini but it was the same thing. Both of them are costing $20/month and for me it isn’t worth it at the moment. Because of that I went looking for private ones, since I had already seen people doing running AI solution locally. Coupled with the fact that I got a new M2 MacBook Air, I decided to test the limits.

I watched the presentation by hu.ma.ne founder earlier in the week at TED in May, and I thought the device, the Ai Pin, was really different from what we have, read smartphones. What is the use of something without a screen? Then I remembered that people used to have Pagers, but even then, Pagers had a screen with the number to call back. But I digress.

What really made me think was watching their launch video yesterday. We already know by now that not all the information used was accurate. There were less nuts that what the AI said and the eclipse in 2024 will be better viewed thrown North America, rather than Australia. But apart from the AI hallucinations that everybody has already experienced using any AI assistant, the point of the device for me has been made.

It surprised me how easy it was to build a local solution with Ollama.

Introduction

This itch to have a private solution for AI came to me after I saw that OpenAI changed their settings on the playground section and does not allow for free users to test the models. With that I went to check Gemini but it was the same thing. Both of them are costing $20/month and for me it isn’t worth it at the moment. Because of that I went looking for private ones, since I had already seen people doing running AI solution locally. Coupled with the fact that I got a new M2 MacBook Air, I decided to test the limits.

It surprised me how easy it was to build a local solution with Ollama.

Introduction

This itch to have a private solution for AI came to me after I saw that OpenAI changed their settings on the playground section and does not allow for free users to test the models. With that I went to check Gemini but it was the same thing. Both of them are costing $20/month and for me it isn’t worth it at the moment. Because of that I went looking for private ones, since I had already seen people doing running AI solution locally. Coupled with the fact that I got a new M2 MacBook Air, I decided to test the limits.

It surprised me how easy it was to build a local solution with Ollama.

Introduction

This itch to have a private solution for AI came to me after I saw that OpenAI changed their settings on the playground section and does not allow for free users to test the models. With that I went to check Gemini but it was the same thing. Both of them are costing $20/month and for me it isn’t worth it at the moment. Because of that I went looking for private ones, since I had already seen people doing running AI solution locally. Coupled with the fact that I got a new M2 MacBook Air, I decided to test the limits.

It surprised me how easy it was to build a local solution with Ollama.

Introduction

This itch to have a private solution for AI came to me after I saw that OpenAI changed their settings on the playground section and does not allow for free users to test the models. With that I went to check Gemini but it was the same thing. Both of them are costing $20/month and for me it isn’t worth it at the moment. Because of that I went looking for private ones, since I had already seen people doing running AI solution locally. Coupled with the fact that I got a new M2 MacBook Air, I decided to test the limits.

It surprised me how easy it was to build a local solution with Ollama.

Introduction

This itch to have a private solution for AI came to me after I saw that OpenAI changed their settings on the playground section and does not allow for free users to test the models. With that I went to check Gemini but it was the same thing. Both of them are costing $20/month and for me it isn’t worth it at the moment. Because of that I went looking for private ones, since I had already seen people doing running AI solution locally. Coupled with the fact that I got a new M2 MacBook Air, I decided to test the limits.

The MacBook Pro 9,2 is a model of the MacBook Pro that was released in June 2012. It has a 13.3-inch display, a 2.5 GHz or 2.9 GHz dual-core Intel Core i5 or i7 processor, 4 GB or 8 GB of RAM, and a 500 GB or 750 GB hard drive.

My MacBook was bought around 2013 or 2014, don’t remember exactly. It was bought new, with 4GB of RAM and 500 GB hard drive. At the time I already had that MacBook black, which I got around 2006 and was really becoming slow. Around 2010, or 2011, I got an iMac which was my main computer and I used less and less the notebook. So, this year it marks 10 years that I am with this MacBook and it is really a nice computer even today.

The MacBook Pro 9,2 is a model of the MacBook Pro that was released in June 2012. It has a 13.3-inch display, a 2.5 GHz or 2.9 GHz dual-core Intel Core i5 or i7 processor, 4 GB or 8 GB of RAM, and a 500 GB or 750 GB hard drive.

My MacBook was bought around 2013 or 2014, don’t remember exactly. It was bought new, with 4GB of RAM and 500 GB hard drive. At the time I already had that MacBook black, which I got around 2006 and was really becoming slow. Around 2010, or 2011, I got an iMac which was my main computer and I used less and less the notebook. So, this year it marks 10 years that I am with this MacBook and it is really a nice computer even today.

The MacBook Pro 9,2 is a model of the MacBook Pro that was released in June 2012. It has a 13.3-inch display, a 2.5 GHz or 2.9 GHz dual-core Intel Core i5 or i7 processor, 4 GB or 8 GB of RAM, and a 500 GB or 750 GB hard drive.

My MacBook was bought around 2013 or 2014, don’t remember exactly. It was bought new, with 4GB of RAM and 500 GB hard drive. At the time I already had that MacBook black, which I got around 2006 and was really becoming slow. Around 2010, or 2011, I got an iMac which was my main computer and I used less and less the notebook. So, this year it marks 10 years that I am with this MacBook and it is really a nice computer even today.

The MacBook Pro 9,2 is a model of the MacBook Pro that was released in June 2012. It has a 13.3-inch display, a 2.5 GHz or 2.9 GHz dual-core Intel Core i5 or i7 processor, 4 GB or 8 GB of RAM, and a 500 GB or 750 GB hard drive.

My MacBook was bought around 2013 or 2014, don’t remember exactly. It was bought new, with 4GB of RAM and 500 GB hard drive. At the time I already had that MacBook black, which I got around 2006 and was really becoming slow. Around 2010, or 2011, I got an iMac which was my main computer and I used less and less the notebook. So, this year it marks 10 years that I am with this MacBook and it is really a nice computer even today.

The MacBook Pro 9,2 is a model of the MacBook Pro that was released in June 2012. It has a 13.3-inch display, a 2.5 GHz or 2.9 GHz dual-core Intel Core i5 or i7 processor, 4 GB or 8 GB of RAM, and a 500 GB or 750 GB hard drive.

My MacBook was bought around 2013 or 2014, don’t remember exactly. It was bought new, with 4GB of RAM and 500 GB hard drive. At the time I already had that MacBook black, which I got around 2006 and was really becoming slow. Around 2010, or 2011, I got an iMac which was my main computer and I used less and less the notebook. So, this year it marks 10 years that I am with this MacBook and it is really a nice computer even today.

The MacBook Pro 9,2 is a model of the MacBook Pro that was released in June 2012. It has a 13.3-inch display, a 2.5 GHz or 2.9 GHz dual-core Intel Core i5 or i7 processor, 4 GB or 8 GB of RAM, and a 500 GB or 750 GB hard drive.

My MacBook was bought around 2013 or 2014, don’t remember exactly. It was bought new, with 4GB of RAM and 500 GB hard drive. At the time I already had that MacBook black, which I got around 2006 and was really becoming slow. Around 2010, or 2011, I got an iMac which was my main computer and I used less and less the notebook. So, this year it marks 10 years that I am with this MacBook and it is really a nice computer even today.

The MacBook Pro 9,2 is a model of the MacBook Pro that was released in June 2012. It has a 13.3-inch display, a 2.5 GHz or 2.9 GHz dual-core Intel Core i5 or i7 processor, 4 GB or 8 GB of RAM, and a 500 GB or 750 GB hard drive.

My MacBook was bought around 2013 or 2014, don’t remember exactly. It was bought new, with 4GB of RAM and 500 GB hard drive. At the time I already had that MacBook black, which I got around 2006 and was really becoming slow. Around 2010, or 2011, I got an iMac which was my main computer and I used less and less the notebook. So, this year it marks 10 years that I am with this MacBook and it is really a nice computer even today.

The last months have been very exciting to me. The most exciting and difficult part by far is having my newborn son, whom is almost 3 months old. The other exciting part is that I finally understood that if I really like technology I should really invest in it.

Investing more in my formation in technology right now could come as odd for most people because I already have a Masters in chemistry and a specialization in intellectual property and also happen to work in the field that I have specialized in. The main problem for me is not that I don’t like what I do but that sensation that I feel about this not being scalable enough, mainly because of the difficulty that I encountered after first leaving the university and because after so much hard work on specializing not having enough return on the investment.

The MacBook Pro 9,2 is a model of the MacBook Pro that was released in June 2012. It has a 13.3-inch display, a 2.5 GHz or 2.9 GHz dual-core Intel Core i5 or i7 processor, 4 GB or 8 GB of RAM, and a 500 GB or 750 GB hard drive.

My MacBook was bought around 2013 or 2014, don’t remember exactly. It was bought new, with 4GB of RAM and 500 GB hard drive. At the time I already had that MacBook black, which I got around 2006 and was really becoming slow. Around 2010, or 2011, I got an iMac which was my main computer and I used less and less the notebook. So, this year it marks 10 years that I am with this MacBook and it is really a nice computer even today.

The MacBook Pro 9,2 is a model of the MacBook Pro that was released in June 2012. It has a 13.3-inch display, a 2.5 GHz or 2.9 GHz dual-core Intel Core i5 or i7 processor, 4 GB or 8 GB of RAM, and a 500 GB or 750 GB hard drive.

My MacBook was bought around 2013 or 2014, don’t remember exactly. It was bought new, with 4GB of RAM and 500 GB hard drive. At the time I already had that MacBook black, which I got around 2006 and was really becoming slow. Around 2010, or 2011, I got an iMac which was my main computer and I used less and less the notebook. So, this year it marks 10 years that I am with this MacBook and it is really a nice computer even today.

The last months have been very exciting to me. The most exciting and difficult part by far is having my newborn son, whom is almost 3 months old. The other exciting part is that I finally understood that if I really like technology I should really invest in it.

Investing more in my formation in technology right now could come as odd for most people because I already have a Masters in chemistry and a specialization in intellectual property and also happen to work in the field that I have specialized in. The main problem for me is not that I don’t like what I do but that sensation that I feel about this not being scalable enough, mainly because of the difficulty that I encountered after first leaving the university and because after so much hard work on specializing not having enough return on the investment.

I watched the presentation by hu.ma.ne founder earlier in the week at TED in May, and I thought the device, the Ai Pin, was really different from what we have, read smartphones. What is the use of something without a screen? Then I remembered that people used to have Pagers, but even then, Pagers had a screen with the number to call back. But I digress.

What really made me think was watching their launch video yesterday. We already know by now that not all the information used was accurate. There were less nuts that what the AI said and the eclipse in 2024 will be better viewed thrown North America, rather than Australia. But apart from the AI hallucinations that everybody has already experienced using any AI assistant, the point of the device for me has been made.

I watched the presentation by hu.ma.ne founder earlier in the week at TED in May, and I thought the device, the Ai Pin, was really different from what we have, read smartphones. What is the use of something without a screen? Then I remembered that people used to have Pagers, but even then, Pagers had a screen with the number to call back. But I digress.

What really made me think was watching their launch video yesterday. We already know by now that not all the information used was accurate. There were less nuts that what the AI said and the eclipse in 2024 will be better viewed thrown North America, rather than Australia. But apart from the AI hallucinations that everybody has already experienced using any AI assistant, the point of the device for me has been made.

I watched the presentation by hu.ma.ne founder earlier in the week at TED in May, and I thought the device, the Ai Pin, was really different from what we have, read smartphones. What is the use of something without a screen? Then I remembered that people used to have Pagers, but even then, Pagers had a screen with the number to call back. But I digress.

What really made me think was watching their launch video yesterday. We already know by now that not all the information used was accurate. There were less nuts that what the AI said and the eclipse in 2024 will be better viewed thrown North America, rather than Australia. But apart from the AI hallucinations that everybody has already experienced using any AI assistant, the point of the device for me has been made.

Life as a father

My kid is already 7 months old. The time goes too fast. He already dragging himself on the floor and not crying so much anymore. Each day is a new day and now it is getting clearer that life goes on, like I don’t have to give up my hobbies and interests because he demands attention.

It is a totally different experience. I remember the day my wife said the test came out positive. I froze, pale with fear and anxiety. The first day was really strange, every 5 minutes I thought again about it and really couldn’t believe that I was going to be/was a father.

Life as a father

My kid is already 7 months old. The time goes too fast. He already dragging himself on the floor and not crying so much anymore. Each day is a new day and now it is getting clearer that life goes on, like I don’t have to give up my hobbies and interests because he demands attention.

It is a totally different experience. I remember the day my wife said the test came out positive. I froze, pale with fear and anxiety. The first day was really strange, every 5 minutes I thought again about it and really couldn’t believe that I was going to be/was a father.

This is a quick guide for those that are having trouble installing NixOS and getting the No Internet Available error.

Since I’m using the GUI program Virtual Manager, I went into the VM’s configuration.

Select the VM and the Open button on the top bar. You could do this while the VM is running but the changes will only take effect the next time the VM boots up, so it is better to have the VM shutdown.

This is a quick guide for those that are having trouble installing NixOS and getting the No Internet Available error.

Since I’m using the GUI program Virtual Manager, I went into the VM’s configuration.

Select the VM and the Open button on the top bar. You could do this while the VM is running but the changes will only take effect the next time the VM boots up, so it is better to have the VM shutdown.

This is a quick guide for those that are having trouble installing NixOS and getting the No Internet Available error.

Since I’m using the GUI program Virtual Manager, I went into the VM’s configuration.

Select the VM and the Open button on the top bar. You could do this while the VM is running but the changes will only take effect the next time the VM boots up, so it is better to have the VM shutdown.

The last months have been very exciting to me. The most exciting and difficult part by far is having my newborn son, whom is almost 3 months old. The other exciting part is that I finally understood that if I really like technology I should really invest in it.

Investing more in my formation in technology right now could come as odd for most people because I already have a Masters in chemistry and a specialization in intellectual property and also happen to work in the field that I have specialized in. The main problem for me is not that I don’t like what I do but that sensation that I feel about this not being scalable enough, mainly because of the difficulty that I encountered after first leaving the university and because after so much hard work on specializing not having enough return on the investment.

The last months have been very exciting to me. The most exciting and difficult part by far is having my newborn son, whom is almost 3 months old. The other exciting part is that I finally understood that if I really like technology I should really invest in it.

Investing more in my formation in technology right now could come as odd for most people because I already have a Masters in chemistry and a specialization in intellectual property and also happen to work in the field that I have specialized in. The main problem for me is not that I don’t like what I do but that sensation that I feel about this not being scalable enough, mainly because of the difficulty that I encountered after first leaving the university and because after so much hard work on specializing not having enough return on the investment.