[Global] I give all of my clients a view like this

I deploy custom AI and automation solutions for my customers, and most of them don't really want to manage it themselves, but they DO want to be able to see what's happening.

So I create these read-only views for each client, where they can see all their agents working together. The big sphere is the platform (runs mcp for communication, manages access and permissions, backups, ...) and the smaller spheres are individual agents.

This view has a light background synth that will play different sounds for each agent and each action, so a nice bonus is this can be used on an extra office display to add some ambient sound to the client's offices.

Feedback so far has been really good, so I thought I'd share this :)

u/magentic_flows — 11 days ago

Sharing my playbook for self-driving SEO

I've been running an SEO/content agency for about 2 years, and I recently got the point where I was tired of being the human glue between 15-20 chrome tabs, spreadsheets, search console, competitor research, content briefs, writers, and CMS's

The work itself wasn't particularly hard, the hard [and more importantly, tedious] part was keeping all of these things connected

I started by mapping out the process that I used to do, myself, for every single client

First I'd start with research. I'd look at competitors, search results, existing content, what was ranking, what topics seemed worth going after, and where there were gaps.

I'd then turn those keywords into content ideas - what should the article(s) cover, what questions should they answer, and which related topics should be linked to and from it.

Then came the writing and editing, along with the SEO optimization itself (titles, headings, internal links, metadata, ...)

And then publishing. Except, that still wasn't the end. Once the content was live, I'd periodically go back to analytics and search data to see what was actually happening, what was working and more importantly, what wasn't.

Tweak where necessary, and start all over to continue expanding surface. Results were good, but the workload itself was not. I'd find myself with 15-20 tabs open at any moment, juggling to keep it all organized and keeping track of what needed to be done at any point. Don't even get me started on the spreadsheets lmao

All this work and repetition eventually made me think - what if this entire thing could be a system instead of individual tasks

On to the fun part now :D

A system has inputs, outputs, and intermediary steps.

The inputs are ideas, analytics data, existing content, context on the business, and competitor data. For bonus points here, you can also consider your clients' roadmaps and changelogs (if you work with software clients, this can be absolute gold)

Outputs are SEO pages, blog posts, guides/course material, and newsletter content. I've also experimented with having social media posts as an output, but frankly I prefer doing that myself.

A lot of this is enabled by AI, but actual community management and client interaction is something that I strongly believe should ALWAYS be handled by a human, whether that is me or someone on my team.

The part where I believe AI and automation can truly shine without sacrificing any of the authenticity is in bringing all the inputs together and performing most of the intermediary steps I described above.

The basic idea is that I give my AI agents the context around the site and what I'm trying to achieve, and it handles a lot of the repetitive work that used to sit between all those individual steps.

So instead of:

Research → keywords → content brief → writing → publishing → analytics → repeat

I can run a much more connected loop:

Research → identify opportunities → create content → publish → measure → learn → create the next thing

The research side is no longer something I have to manually repeat every time. The system can look at what's happening, identify opportunities, and turn those into things worth working on.

Rather than starting with a blank document and manually translating keyword research into outputs, the outputs are generated as part of the same workflow

The research and the content aren't disconnected anymore, the information gathered upstream actually feeds into what is getting produced downstream

And importantly, the loop doesn't stop when the content is published, the performance data feeds back into the system. So instead of publishing an article and forgetting about it until I check the analytics a few weeks later, I can use the data to understand what's working, what's not, and what the next opportunity should be

What changes is the role I play in the process - I'm not sitting there doing every individual task anymore, I'm mostly setting direction, reviewing what the system produces and making higher level decisions.

The big difference from me here isn't that each individual task is faster now, but the fact I no longer have to manage all of them individually, and I can focus on the rest of it all, as if I'm conducting an orchestra, which I personally find a lot more satisfying

So how did I set this up?

Personally I'm using qoren.sh but frankly you can use anything from n8n to custom GPTs, depending on how much control you want over it, as well as how much work you'd like to put in setting it up and maintaining it

For my own set up, I essentially have 3 agents per client:

a chief of staff, whose job is to communicate with me and the other agents - I persoanlly like to call him Colin the energy vampire (sneaky What We Do In The Shadows reference there)

a watchdog (connects to analytics tools, crawls competitor websites, news sources, etc.) [I usually call him Hound)

a ghostwriter (strictly instructed to "sound" like the client's own rhetoric and writing style) [Ghosty, sometimes Casper the ghost if I'm feeling whimsical]

The overall process looks something like this:

Research: Hound keeps an eye on the market. It researches competitors, search results, emerging topics, news, content gaps, questions people are asking, and anything else that might represent an opportunity. It gives me a daily rundown of what competitors are starting to rank for, a cluster of related searches we aren't covering, pages that have more potential, changes in SERPs worth paying attention to, etc;

SEO/Analytics monitoring: The same agent pulls relevant search and site data and looks for changes, rather than me opening up Search Console and trying to figure out what's important. The goal here isn't to have a giant weekly dashboard, it's to know what's changing, why does it matter, and what should I do about it;

For example: "traffic is up, but almost all the increase is coming from these 3 pages", or "this page is getting a lot of impressions but has a poor CTR"

  1. Opportunity Discovery: This is where the different pieces start being useful together. Instead of having one spreadsheet full of keywords I may or may not end up ever using, opportunities get flag to be turned into actual work.

A potential keyword/content opportunity gets evaluated against things like search intent, existing coverage, competition, relevance to the business, and what we have already published. Instead of "here's 100 keywords" I get something like "here's 5 things to work on next, and why". The "why" part is probably the most important, because it allows me to evaluate whether we're starting from a solid base or we're focusing on something that doesn't feel right.

  1. Content Briefs: Once an opportunity is selected, it gets passed on to the ghostwriter to draft the content piece. Importantly, it doesn't get an instruction like "like an article about X". It has research, intent, relevant pages, topics to cover, internal links to consider, and the context around the overall strategy and what we're trying to achieve

  2. Writing: As described previously, I've set up an agent specifically for this, whose ONLY responsibility is to get inputs and transform them into drafts from the briefs it receives. It never creates random blog posts it "just thought of". Every content piece is produced downstream of an actual insight, based on real data, and this agent doesn't need to worry about where it came from or what it means - it gets spoon fed exactly what it needs to know

  3. Review: This is where I come in; The chief of staff relays drafts to me, receives feedback and a final decision on whether it is a go or not. If articles need tweaking, those get tossed back to the ghostwriter with the feedback - the chief of staff agent never writes anything himself, it just relays information back and forth and orchestrates the work;

  4. Publishing: At first, I was doing manual copy-paste from qoren into a CMS, but I recently started automating this part too. This will heavily depend on which CMS you're using, but most support either an MCP server or an API you can call. This was scary for me, which is why I didn't do it for a long time. Giving the publishing reigns to an AI system is not something I was comfortable with until I had a solid system behind it, so I'd advise only doing this part once you're very confident the overall workflow suits yours and your clients' standards;

  5. The feedback loop: This is probably the most important part. After the articles get published, we wait for the actual data. The Hound agent gets informed when new articles get pushed out, and it knows to start collecting information on them on a daily basis. Maybe the article starts ranking for unexpected terms. Maybe it's getting impressions but not clicks. Maybe it completely flops.

All this information gets processed and becomes input for the next iteration.

This was the real unlock for me - I didn't automate writing blog posts; I automated the feedback loop around the content. I still make the important decisions, review everything, and decide where I actually want the strategy to go. The agents to the repetitive research, analysis, preparation and execution.

The underlying model driving it all in the background is Qwen 3.8 2.4T, via openrouter - this is the most affordable model I was able to find success with. Cheaper models don't deliver good enough results. Sonnet/Opus/GPT 5.6 are also good if you're less cost sensitive, but something like Fable/Astra is overkill for this, from my experience.

Cost wise, it runs under $200/month per client - $69 of those are for qoren and the rest is for inference. At first I was using their BYOK option, but I prefer managing the cost in a single place, so I started just using the managed keys and adding credits within qoren itself - it does have a small markup on LLM costs but personally I find that to be worth it not having to manage yet another tool or api key

One could argue the cost will go slightly above that, if we factor in my hourly cost for the review cycles and time spent reading articles and providing feedback, but that's become around 45-60 minutes a week, so it's mostly negligible

Anyway that's the playbook I'm going for right now. It's still evolving and I've got some ideas on where to take it next, but for now I'm just happy I got some of my time back to actually focus on what I enjoy doing - building the relationships, thinking about strategy, and focusing on what matters instead of the mind numbing repetitiveness that I was often faced with.

If you got this far, thank you for reading, and please do feel free to share what has been working for you, I'm always curious to learn about workflows and systems, and I'm especially curious on where you keep the human in the loop (that is, if you are using AI at all)

reddit.com
u/magentic_flows — 1 month ago

My playbook for self-driving SEO

I've been running an SEO/content agency for about 2 years, and I recently got the point where I was tired of being the human glue between 15-20 chrome tabs, spreadsheets, search console, competitor research, content briefs, writers, and CMS's

The work itself wasn't particularly hard, the hard [and more importantly, tedious] part was keeping all of these things connected

I started by mapping out the process that I used to do, myself, for every single client

First I'd start with research. I'd look at competitors, search results, existing content, what was ranking, what topics seemed worth going after, and where there were gaps.

I'd then turn those keywords into content ideas - what should the article(s) cover, what questions should they answer, and which related topics should be linked to and from it.

Then came the writing and editing, along with the SEO optimization itself (titles, headings, internal links, metadata, ...)

And then publishing. Except, that still wasn't the end. Once the content was live, I'd periodically go back to analytics and search data to see what was actually happening, what was working and more importantly, what wasn't.

Tweak where necessary, and start all over to continue expanding surface. Results were good, but the workload itself was not. I'd find myself with 15-20 tabs open at any moment, juggling to keep it all organized and keeping track of what needed to be done at any point. Don't even get me started on the spreadsheets lmao

All this work and repetition eventually made me think - what if this entire thing could be a system instead of individual tasks

On to the fun part now :D

A system has inputs, outputs, and intermediary steps.

The inputs are ideas, analytics data, existing content, context on the business, and competitor data. For bonus points here, you can also consider your clients' roadmaps and changelogs (if you work with software clients, this can be absolute gold)

Outputs are SEO pages, blog posts, guides/course material, and newsletter content. I've also experimented with having social media posts as an output, but frankly I prefer doing that myself.

A lot of this is enabled by AI, but actual community management and client interaction is something that I strongly believe should ALWAYS be handled by a human, whether that is me or someone on my team.

The part where I believe AI and automation can truly shine without sacrificing any of the authenticity is in bringing all the inputs together and performing most of the intermediary steps I described above.

The basic idea is that I give my AI agents the context around the site and what I'm trying to achieve, and it handles a lot of the repetitive work that used to sit between all those individual steps.

So instead of:

Research → keywords → content brief → writing → publishing → analytics → repeat

I can run a much more connected loop:

Research → identify opportunities → create content → publish → measure → learn → create the next thing

The research side is no longer something I have to manually repeat every time. The system can look at what's happening, identify opportunities, and turn those into things worth working on.

Rather than starting with a blank document and manually translating keyword research into outputs, the outputs are generated as part of the same workflow

The research and the content aren't disconnected anymore, the information gathered upstream actually feeds into what is getting produced downstream

And importantly, the loop doesn't stop when the content is published, the performance data feeds back into the system. So instead of publishing an article and forgetting about it until I check the analytics a few weeks later, I can use the data to understand what's working, what's not, and what the next opportunity should be

What changes is the role I play in the process - I'm not sitting there doing every individual task anymore, I'm mostly setting direction, reviewing what the system produces and making higher level decisions.

The big difference from me here isn't that each individual task is faster now, but the fact I no longer have to manage all of them individually, and I can focus on the rest of it all, as if I'm conducting an orchestra, which I personally find a lot more satisfying

So how did I set this up?

Personally I'm using qoren.sh but frankly you can use anything from n8n to custom GPTs, depending on how much control you want over it, as well as how much work you'd like to put in setting it up and maintaining it

For my own set up, I essentially have 3 agents per client:

a chief of staff, whose job is to communicate with me and the other agents - I persoanlly like to call him Colin the energy vampire (sneaky What We Do In The Shadows reference there)

a watchdog (connects to analytics tools, crawls competitor websites, news sources, etc.) [I usually call him Hound)

a ghostwriter (strictly instructed to "sound" like the client's own rhetoric and writing style) [Ghosty, sometimes Casper the ghost if I'm feeling whimsical]

The overall process looks something like this:

Research: Hound keeps an eye on the market. It researches competitors, search results, emerging topics, news, content gaps, questions people are asking, and anything else that might represent an opportunity. It gives me a daily rundown of what competitors are starting to rank for, a cluster of related searches we aren't covering, pages that have more potential, changes in SERPs worth paying attention to, etc;

SEO/Analytics monitoring: The same agent pulls relevant search and site data and looks for changes, rather than me opening up Search Console and trying to figure out what's important. The goal here isn't to have a giant weekly dashboard, it's to know what's changing, why does it matter, and what should I do about it;

For example: "traffic is up, but almost all the increase is coming from these 3 pages", or "this page is getting a lot of impressions but has a poor CTR"

  1. Opportunity Discovery: This is where the different pieces start being useful together. Instead of having one spreadsheet full of keywords I may or may not end up ever using, opportunities get flag to be turned into actual work.

A potential keyword/content opportunity gets evaluated against things like search intent, existing coverage, competition, relevance to the business, and what we have already published. Instead of "here's 100 keywords" I get something like "here's 5 things to work on next, and why". The "why" part is probably the most important, because it allows me to evaluate whether we're starting from a solid base or we're focusing on something that doesn't feel right.

  1. Content Briefs: Once an opportunity is selected, it gets passed on to the ghostwriter to draft the content piece. Importantly, it doesn't get an instruction like "like an article about X". It has research, intent, relevant pages, topics to cover, internal links to consider, and the context around the overall strategy and what we're trying to achieve

  2. Writing: As described previously, I've set up an agent specifically for this, whose ONLY responsibility is to get inputs and transform them into drafts from the briefs it receives. It never creates random blog posts it "just thought of". Every content piece is produced downstream of an actual insight, based on real data, and this agent doesn't need to worry about where it came from or what it means - it gets spoon fed exactly what it needs to know

  3. Review: This is where I come in; The chief of staff relays drafts to me, receives feedback and a final decision on whether it is a go or not. If articles need tweaking, those get tossed back to the ghostwriter with the feedback - the chief of staff agent never writes anything himself, it just relays information back and forth and orchestrates the work;

  4. Publishing: At first, I was doing manual copy-paste from qoren into a CMS, but I recently started automating this part too. This will heavily depend on which CMS you're using, but most support either an MCP server or an API you can call. This was scary for me, which is why I didn't do it for a long time. Giving the publishing reigns to an AI system is not something I was comfortable with until I had a solid system behind it, so I'd advise only doing this part once you're very confident the overall workflow suits yours and your clients' standards;

  5. The feedback loop: This is probably the most important part. After the articles get published, we wait for the actual data. The Hound agent gets informed when new articles get pushed out, and it knows to start collecting information on them on a daily basis. Maybe the article starts ranking for unexpected terms. Maybe it's getting impressions but not clicks. Maybe it completely flops.

All this information gets processed and becomes input for the next iteration.

This was the real unlock for me - I didn't automate writing blog posts; I automated the feedback loop around the content. I still make the important decisions, review everything, and decide where I actually want the strategy to go. The agents to the repetitive research, analysis, preparation and execution.

The underlying model driving it all in the background is Qwen 3.8 2.4T, via openrouter - this is the most affordable model I was able to find success with. Cheaper models don't deliver good enough results. Sonnet/Opus/GPT 5.6 are also good if you're less cost sensitive, but something like Fable/Astra is overkill for this, from my experience.

Cost wise, it runs under $200/month per client - $69 of those are for qoren and the rest is for inference. At first I was using their BYOK option, but I prefer managing the cost in a single place, so I started just using the managed keys and adding credits within qoren itself - it does have a small markup on LLM costs but personally I find that to be worth it not having to manage yet another tool or api key

One could argue the cost will go slightly above that, if we factor in my hourly cost for the review cycles and time spent reading articles and providing feedback, but that's become around 45-60 minutes a week, so it's mostly negligible

Anyway that's the playbook I'm going for right now. It's still evolving and I've got some ideas on where to take it next, but for now I'm just happy I got some of my time back to actually focus on what I enjoy doing - building the relationships, thinking about strategy, and focusing on what matters instead of the mind numbing repetitiveness that I was often faced with.

If you got this far, thank you for reading, and please do feel free to share what has been working for you, I'm always curious to learn about workflows and systems, and I'm especially curious on where you keep the human in the loop (that is, if you are using AI at all)

reddit.com
u/magentic_flows — 1 month ago

My playbook for self-driving SEO

I've been running an SEO/content agency for about 2 years, and I recently got the point where I was tired of being the human glue between 15-20 chrome tabs, spreadsheets, search console, competitor research, content briefs, writers, and CMS's

The work itself wasn't particularly hard, the hard [and more importantly, tedious] part was keeping all of these things connected

I started by mapping out the process that I used to do, myself, for every single client

First I'd start with research. I'd look at competitors, search results, existing content, what was ranking, what topics seemed worth going after, and where there were gaps.

I'd then turn those keywords into content ideas - what should the article(s) cover, what questions should they answer, and which related topics should be linked to and from it.

Then came the writing and editing, along with the SEO optimization itself (titles, headings, internal links, metadata, ...)

And then publishing. Except, that still wasn't the end. Once the content was live, I'd periodically go back to analytics and search data to see what was actually happening, what was working and more importantly, what wasn't.

Tweak where necessary, and start all over to continue expanding surface. Results were good, but the workload itself was not. I'd find myself with 15-20 tabs open at any moment, juggling to keep it all organized and keeping track of what needed to be done at any point. Don't even get me started on the spreadsheets lmao

All this work and repetition eventually made me think - what if this entire thing could be a system instead of individual tasks

On to the fun part now :D

A system has inputs, outputs, and intermediary steps.

The inputs are ideas, analytics data, existing content, context on the business, and competitor data. For bonus points here, you can also consider your clients' roadmaps and changelogs (if you work with software clients, this can be absolute gold)

Outputs are SEO pages, blog posts, guides/course material, and newsletter content. I've also experimented with having social media posts as an output, but frankly I prefer doing that myself.

A lot of this is enabled by AI, but actual community management and client interaction is something that I strongly believe should ALWAYS be handled by a human, whether that is me or someone on my team.

The part where I believe AI and automation can truly shine without sacrificing any of the authenticity is in bringing all the inputs together and performing most of the intermediary steps I described above.

The basic idea is that I give my AI agents the context around the site and what I'm trying to achieve, and it handles a lot of the repetitive work that used to sit between all those individual steps.

So instead of:

Research → keywords → content brief → writing → publishing → analytics → repeat

I can run a much more connected loop:

Research → identify opportunities → create content → publish → measure → learn → create the next thing

The research side is no longer something I have to manually repeat every time. The system can look at what's happening, identify opportunities, and turn those into things worth working on.

Rather than starting with a blank document and manually translating keyword research into outputs, the outputs are generated as part of the same workflow

The research and the content aren't disconnected anymore, the information gathered upstream actually feeds into what is getting produced downstream

And importantly, the loop doesn't stop when the content is published, the performance data feeds back into the system. So instead of publishing an article and forgetting about it until I check the analytics a few weeks later, I can use the data to understand what's working, what's not, and what the next opportunity should be

What changes is the role I play in the process - I'm not sitting there doing every individual task anymore, I'm mostly setting direction, reviewing what the system produces and making higher level decisions.

The big difference from me here isn't that each individual task is faster now, but the fact I no longer have to manage all of them individually, and I can focus on the rest of it all, as if I'm conducting an orchestra, which I personally find a lot more satisfying

So how did I set this up?

Personally I'm using qoren.sh but frankly you can use anything from n8n to custom GPTs, depending on how much control you want over it, as well as how much work you'd like to put in setting it up and maintaining it

For my own set up, I essentially have 3 agents per client:

a chief of staff, whose job is to communicate with me and the other agents - I persoanlly like to call him Colin the energy vampire (sneaky What We Do In The Shadows reference there)

a watchdog (connects to analytics tools, crawls competitor websites, news sources, etc.) [I usually call him Hound)

a ghostwriter (strictly instructed to "sound" like the client's own rhetoric and writing style) [Ghosty, sometimes Casper the ghost if I'm feeling whimsical]

The overall process looks something like this:

Research: Hound keeps an eye on the market. It researches competitors, search results, emerging topics, news, content gaps, questions people are asking, and anything else that might represent an opportunity. It gives me a daily rundown of what competitors are starting to rank for, a cluster of related searches we aren't covering, pages that have more potential, changes in SERPs worth paying attention to, etc;

SEO/Analytics monitoring: The same agent pulls relevant search and site data and looks for changes, rather than me opening up Search Console and trying to figure out what's important. The goal here isn't to have a giant weekly dashboard, it's to know what's changing, why does it matter, and what should I do about it;

For example: "traffic is up, but almost all the increase is coming from these 3 pages", or "this page is getting a lot of impressions but has a poor CTR"

  1. Opportunity Discovery: This is where the different pieces start being useful together. Instead of having one spreadsheet full of keywords I may or may not end up ever using, opportunities get flag to be turned into actual work.

A potential keyword/content opportunity gets evaluated against things like search intent, existing coverage, competition, relevance to the business, and what we have already published. Instead of "here's 100 keywords" I get something like "here's 5 things to work on next, and why". The "why" part is probably the most important, because it allows me to evaluate whether we're starting from a solid base or we're focusing on something that doesn't feel right.

  1. Content Briefs: Once an opportunity is selected, it gets passed on to the ghostwriter to draft the content piece. Importantly, it doesn't get an instruction like "like an article about X". It has research, intent, relevant pages, topics to cover, internal links to consider, and the context around the overall strategy and what we're trying to achieve

  2. Writing: As described previously, I've set up an agent specifically for this, whose ONLY responsibility is to get inputs and transform them into drafts from the briefs it receives. It never creates random blog posts it "just thought of". Every content piece is produced downstream of an actual insight, based on real data, and this agent doesn't need to worry about where it came from or what it means - it gets spoon fed exactly what it needs to know

  3. Review: This is where I come in; The chief of staff relays drafts to me, receives feedback and a final decision on whether it is a go or not. If articles need tweaking, those get tossed back to the ghostwriter with the feedback - the chief of staff agent never writes anything himself, it just relays information back and forth and orchestrates the work;

  4. Publishing: At first, I was doing manual copy-paste from qoren into a CMS, but I recently started automating this part too. This will heavily depend on which CMS you're using, but most support either an MCP server or an API you can call. This was scary for me, which is why I didn't do it for a long time. Giving the publishing reigns to an AI system is not something I was comfortable with until I had a solid system behind it, so I'd advise only doing this part once you're very confident the overall workflow suits yours and your clients' standards;

  5. The feedback loop: This is probably the most important part. After the articles get published, we wait for the actual data. The Hound agent gets informed when new articles get pushed out, and it knows to start collecting information on them on a daily basis. Maybe the article starts ranking for unexpected terms. Maybe it's getting impressions but not clicks. Maybe it completely flops.

All this information gets processed and becomes input for the next iteration.

This was the real unlock for me - I didn't automate writing blog posts; I automated the feedback loop around the content. I still make the important decisions, review everything, and decide where I actually want the strategy to go. The agents to the repetitive research, analysis, preparation and execution.

The underlying model driving it all in the background is Qwen 3.8 2.4T, via openrouter - this is the most affordable model I was able to find success with. Cheaper models don't deliver good enough results. Sonnet/Opus/GPT 5.6 are also good if you're less cost sensitive, but something like Fable/Astra is overkill for this, from my experience.

Cost wise, it runs under $200/month per client - $69 of those are for qoren and the rest is for inference. At first I was using their BYOK option, but I prefer managing the cost in a single place, so I started just using the managed keys and adding credits within qoren itself - it does have a small markup on LLM costs but personally I find that to be worth it not having to manage yet another tool or api key

One could argue the cost will go slightly above that, if we factor in my hourly cost for the review cycles and time spent reading articles and providing feedback, but that's become around 45-60 minutes a week, so it's mostly negligible

Anyway that's the playbook I'm going for right now. It's still evolving and I've got some ideas on where to take it next, but for now I'm just happy I got some of my time back to actually focus on what I enjoy doing - building the relationships, thinking about strategy, and focusing on what matters instead of the mind numbing repetitiveness that I was often faced with.

If you got this far, thank you for reading, and please do feel free to share what has been working for you, I'm always curious to learn about workflows and systems, and I'm especially curious on where you keep the human in the loop (that is, if you are using AI at all)

reddit.com
u/magentic_flows — 1 month ago

Criei um escritório 3D para os meus agentes de IA

Há cerca de uma semana publiquei aqui sobre a plataforma que estou a construir para fazer com que correr agentes IA com OpenClaw/Hermes seja muito mais fácil, e hoje queria partilhar um update que me deixa muito orgulhoso.

Rapidamente fica aborrecido olhar para um dashboard sem ver nada a acontecer, e fica difícil perceber o que os agentes estão a fazer a cada momento. Por isso decidi criar um escritório 3D onde consigo visualizar e interagir com todos os agentes, e perceber exatamente o estado de cada um sem ter de ir a 4 páginas diferentes

É personalizável e mostra tudo em tempo real. Permite "falar" com cada agente, e até permite que os agentes falem entre si.

Se quiserem ler mais sobre exatamente o que foi adicionado, as release notes estão aqui

Feedback é sempre bem vindo, estejam à vontade para partilhar a vossa opinião ou perguntar tudo o que queiram saber :)

u/magentic_flows — 3 months ago

What if managing your AI agents was actually fun? (I made them little robots in an office)

I've spent a long time getting AI agents to do real work, and the thing nobody tells you up front is this: the model is almost never the reason your agent fails. GPT-class models are more than smart enough for most tasks people want. The agent dies for boring operational reasons instead. You have to host it somewhere, keep it alive, feed it credentials, schedule it, give it memory, and actually be able to tell what it's doing. Miss any one of those and the whole thing quietly rots. Most people's "first agent" is dead within a week and they blame the AI.

So before I plug what I built, here's the framework I wish someone had handed me. This works no matter what tool you use.

  1. Pick a task you already do on a schedule. Recurring work is where agents compound. A one-off "summarize this" is a chat prompt, not an agent. "Review every PR that opens" or "check inventory every morning" is an agent, because the value stacks every single day.

  2. Make sure it has a clear trigger. A time, an event, or an inbox. If you can't say exactly when the agent should wake up, you don't have a job yet, you have a vibe.

  3. Keep the scope brutally narrow. One job done reliably beats a vague "assistant that does everything." Everything-assistants are impossible to trust because you can never predict them. Narrow agents earn trust fast.

  4. Make the output verifiable. For the first week you want to check its work. If you can't easily see what it did and why, you'll never actually delegate to it, and an agent you don't delegate to is just a expensive toy.

  5. Give it its context up front. The difference between a mediocre agent and a great one is usually a good operating manual: who it is, what it cares about, what "good" looks like. Not prompt magic, just writing down what you'd tell a new hire.

That fourth point, being able to see what the agent is doing, turned out to be the thing I kept underestimating. Logs don't build trust. A wall of gray status boxes doesn't build trust. Watching it work does.

Which is the honest reason the tool I built, Qoren.sh, ended up with a 3D Office view. Every environment is a room, every agent is a little robot at its desk actually doing its work in front of you. You can watch two agents collaborate, see one light up when it picks up a task. It started as something fun, and it turned into the feature that made me actually trust the fleet, because "is my agent alive and working" stopped being a log-grep and became a glance. Agents even earn XP and levels from real work, which sounds like a gimmick until you realize it's just observability wearing a fun coat.

On setup: the reason I obsess over the operational stuff above is that Qoren tries to erase all of it. You pick a template (PR reviewer, client onboarder, stock watchdog, payment rescuer, meeting prepper, and a couple dozen more), answer a few plain-English questions, and hit deploy. No servers, no YAML, no cron syntax, live in a few minutes. The framework above is basically the checklist it walks you through so you don't build a dead-in-a-week agent.

Honest limitations: it's best for the recurring, scoped, triggered tasks I described. If you want one genius agent to run your entire company unsupervised, no tool is there yet, and anyone telling you otherwise is selling.

Full disclosure, I built this, so grill me. Happy to answer anything.

What's the first agent you'd actually want running, and what's stopped you so far?

u/magentic_flows — 3 months ago

Making a 3D game out of my AI agents

I wanted a way to visualize what my agents were doing, and a dashboard just wasn't appealing to me. Something about the nature of multi-agent setups made me want something more visual, more spacial.

So I started tinkering and... I now have a full 3d render of my agents working, with real time updates on what they're doing, and visual cues + logs of all intra-network communications between the agents. In this case, my competitor watchdog agent was sending a report to founder-os, my personal assistant

More than just communications, I've added the basic interactions to the UI, making it an actually functional dashboard of sorts.

Feel free to drop feedback in the comments, always welcome <3

u/magentic_flows — 3 months ago
▲ 4 r/indie_startups+1 crossposts

I made openclaw and hermes easy

I've used openclaw + hermes pretty much ever since it they out, and it was always a huge pain to set up. Spin up a server, install, configure, wire in gateways, customize, set up backups. Security was always a concern, and if I wanted to spin up more agents I'd have to repeat the process all over.

So.. I decided to build qoren - a platform that allows you to spin up hermes and openclaw agents at the click of a button

No VPS. No Docker. No fuss.

Every agent gets its own dedicated environment, with isolation by default.

There's over 20 templates to choose from, and you can create your own so you can spin up multiple instances of the same agent.

I would love some feedback, try it free here

u/magentic_flows — 3 months ago

Setting up openclaw and hermes was always a pain, so I decided to fix it

I've used openclaw + hermes pretty much ever since it they out, and it was always a huge pain to set up. Spin up a server, install, configure, customize. Security was always a concern, and if I wanted to spin up more agents I'd have to repeat the process all over.

So.. I decided to build qoren - a platform that allows you to spin up hermes and openclaw agents at the click of a button

No VPS. No Docker. No fuss.

Every agent gets its own dedicated environment, with isolation by default.

There's over 20 templates to choose from, and you can create your own so you can spin up multiple instances of the same agent.

Running an early bird discount of up to 40% off for the first 100 users/7 days.

Feel free to check it out. Would love some honest feedback <3

reddit.com
u/magentic_flows — 4 months ago

Setting up openclaw and hermes was always a pain, so I decided to fix it

I've used openclaw + hermes pretty much ever since it they out, and it was always a huge pain to set up. Spin up a server, install, configure, customize. Security was always a concern, and if I wanted to spin up more agents I'd have to repeat the process all over.

So.. I decided to build qoren - a platform that allows you to spin up hermes and openclaw agents at the click of a button

No VPS. No Docker. No fuss.

Every agent gets its own dedicated environment, with isolation by default.

There's over 20 templates to choose from, and you can create your own so you can spin up multiple instances of the same agent.

Running an early bird discount of up to 40% off for the first 100 users/7 days.

Feel free to check it out. Would love some honest feedback <3

reddit.com
u/magentic_flows — 4 months ago

Setting up openclaw and hermes was always a pain, so I decided to fix it

I've used openclaw pretty much ever since it came out, and it was always a huge pain to set up. Spin up a server, install, configure, customize. Security was always a concern, and if I wanted to spin up more agents I'd have to repeat the process all over.

So.. I decided to build qoren - a platform that allows you to spin up openclaw agents at the click of a button

No VPS. No Docker. No fuss.

Every agent gets its own dedicated environment, with isolation by default.

There's over 20 templates to choose from, and you can create your own so you can spin up multiple instances of the same agent.

Running an early bird discount of up to 40% off for the first 100 users/7 days.

Feel free to check it out. Would love some honest feedback <3

reddit.com
u/magentic_flows — 4 months ago

Setting up openclaw and hermes was always a pain, so I decided to fix it

I've used openclaw + hermes pretty much ever since they shipped, and it was always a huge pain to set up. Spin up a server, install, configure, customize. Security was always a concern, and if I wanted to spin up more agents I'd have to repeat the process all over.

So.. I decided to build qoren - a platform that allows you to spin up hermes and openclaw agents at the click of a button

No VPS. No Docker. No fuss.

Every agent gets its own dedicated environment, with isolation by default.

There's over 20 templates to choose from, and you can create your own so you can spin up multiple instances of the same agent.

Running an early bird discount of up to 40% off for the first 100 users/7 days.

Feel free to check it out. Would love some honest feedback <3

reddit.com
u/magentic_flows — 4 months ago

Fiz com que correr Hermes/OpenClaw fosse finalmente facil

Olá! Uso agentes OpenClaw + Hermes praticamente desde que saíram, e há uma coisa que sempre me incomodou: pô-los a funcionar dá um trabalho enorme

(Para quem não conhece, o OpenClaw e o Hermes são ferramentas para correr agentes de IA autónomos num servidor)

No processo de andar a montar estes agentes uma e outra vez, apercebi-me que a parte difícil nunca era o agente em si, era tudo o resto à volta: montar o servidor, instalar, configurar, tratar da segurança, e depois repetir o processo todo de início sempre que queria mais um

Por isso decidi pegar nesse fluxo todo e construir uma plataforma que o faz por mim - o qoren

Basicamente põe agentes Hermes e OpenClaw a correr com meia dúzia de clicks, sem servidores, sem Docker e sem configuração manual

Cada agente corre no seu próprio ambiente isolado, por isso um nunca vê os dados nem as chaves do outro, e há mais de 20 templates prontos a usar (dá para guardar os teus, e assim pôr outra instância do mesmo agente a correr passa a ser só um clique)

Com isto, algo que me levava meio dia a montar passou a demorar menos de 10 minutos :)

u/magentic_flows — 4 months ago

Setting up openclaw and hermes was always a pain, so I decided to fix it

I've been running OpenClaw + Hermes agents since pretty much the day they shipped. I love what these tools can do. What I did not love was everything it took to get one live and keep it alive.

If you've gone down this road, you already know the drill. If you're about to, here's the honest version of what's waiting for you, and what I learned the hard way. None of it requires my product to be useful, so take what helps and ignore the rest.

The setup gauntlet (what "just spin up an agent" actually means)

Every single agent meant repeating roughly this:

  1. Provision a VPS. Pick a provider, a size, a region. Guess wrong on RAM and the agent runs out of memory mid-task.
  2. Harden the box. SSH keys, disable password login, lock down the firewall, non-root user, automatic security updates. The part everyone skips and later regrets.
  3. Install the runtime and dependencies. Versions drift. What worked last month wants a different flag this month.
  4. Configure the Hermes gateway and the OpenClaw agent. Config files, ports, paths, environment.
  5. Wire up secrets. API keys, tokens, credentials. This is where most people quietly create a security hole (more on that below).
  6. Reverse proxy and TLS. Caddy or nginx, certificates, renewal.
  7. Process supervision. A systemd unit so it survives a reboot instead of silently dying at 3am.
  8. Monitoring. Some way to know it's actually running and not wedged.

That's a good half day if you know what you're doing, and a lost weekend if you don't. And here's the part that broke me: you do all of it again for the next agent. Want three agents? Three times the work, or you co-locate them and inherit a brand new class of problem.

The security traps nobody warns you about

This is the section I most wish someone had handed me on day one.

  • Agents have shell access. That's the whole point, and also the whole risk. A bad task or a prompt injection can run real commands on your box. Isolation is not a nice-to-have.
  • Co-located agents can read each other's everything. Put two agents on one box to sav Agent B's secrets, files, and history. One compromised task now reaches all of them.
  • Plaintext secrets the agent can read itself. If your API keys sit in an env file that the agent's own shell can read, the agent (or anything it runs) can leak them. Treat the agent as a partially untrusted user, because effectively it is.
  • Exposed gateway ports. It is very easy to leave the gateway reachable from the open internet without meaning to.
  • Running as root. Convenient, and exactly how a small mistake turns into a full box compromise.

The checklist I wish I'd had

If you're self-hosting these yourself, this is the short version of everything above:

  • One agent, one isolated environment. Do not share a filesystem between agents you wos data.
  • Run the agent as a dedicated non-root user with the narrowest permissions that still let it work.
  • Keep secrets out of reach of the agent's own shell wherever you can.
  • Lock the gateway behind a firewall and TLS. Default to closed.
  • Put it under process supervision so a reboot doesn't take it offline silently.
  • Have one health signal that tells you it's actually alive, not just that the box is up.
  • Patch on a schedule. Agent infra is internet-facing infra.

Do this and you'll be in far better shape than I was for my first several agents.

What I ended up building

After repeating this loop one too many times, I built the thing I wanted to exist: a platform that spins up Hermes and OpenClaw agents at the click of a button. It's called qoren.

What it does, kept short:

  • No VPS, no Docker, no manual setup. You click, you get a running agent.
  • Every agent gets its own dedicated, isolated environment by default. The co-location problem above doesn't apply.
  • 20+ templates to start from, and you can save your own, so spinning up another instance of the same agent is one click instead of another lost weekend.
  • The hardening, supervision, and TLS pieces are handled, so you don't reassemble that

There's an early-bird discount of up to 40% off for the first 100 users (running for 7 days), if it's useful to you :)

reddit.com
u/magentic_flows — 4 months ago

I made it way easier to run openclaw/hermes

Hey! Just launched the first public version of qoren - a platform that allows you to spin up hermes and openclaw agents at the click of a button

No VPS. No Docker. No fuss.

Running an early bird discount of up to 40% off for the first 100 users/7 days.

Feel free to check it out. Would love some honest feedback <3

reddit.com
u/magentic_flows — 4 months ago

I made it way easier to run OpenClaw and Hermes

I've used openclaw + hermes pretty much ever since it they out, and it was always a huge pain to set up. Spin up a server, install, configure, customize. Security was always a concern, and if I wanted to spin up more agents I'd have to repeat the process all over.

So.. I decided to build qoren - a platform that allows you to spin up hermes and openclaw agents at the click of a button

No VPS. No Docker. No fuss.

Every agent gets its own dedicated environment, with isolation by default.

There's over 20 templates to choose from, and you can create your own so you can spin up multiple instances of the same agent.

Running an early bird discount of up to 40% off for the first 100 users/7 days.

Feel free to check it out. Would love some honest feedback <3

reddit.com
u/magentic_flows — 4 months ago

Made something you might like

I've used openclaw pretty much ever since it came out, and it was always a huge pain to set up. Spin up a server, install, configure, manage. Security was always a concern, and if I wanted to spin up more agents I'd have to repeat the process all over.

So.. I decided to build qoren - a platform that allows you to spin up hermes and openclaw agents at the click of a button

No VPS. No Docker. No fuss.

Running an early bird discount of up to 40% off for the first 100 users/7 days.

Feel free to check it out. Would love some honest feedback <3

reddit.com
u/magentic_flows — 4 months ago

Just launched first public version!

I've used openclaw pretty much ever since it came out, and it was always a huge pain to set up. Spin up a server, install, configure, manage. Security was always a concern, and if I wanted to spin up more agents I'd have to repeat the process all over.

So.. I decided to build qoren - a platform that allows you to spin up hermes and openclaw agents at the click of a button

No VPS. No Docker. No fuss.

Running an early bird discount of up to 40% off for the first 100 users/7 days.

Feel free to check it out. Would love some honest feedback <3

reddit.com
u/magentic_flows — 4 months ago
▲ 4 r/indie_startups+1 crossposts

Launching in 24 hours, feedback?

Hey!

I’ve been building qoren.sh for roughly the last 3 months, and I’m launching it in 24 hours.

Qoren allows you to spin up Hermes and OpenClaw agents at the click of a few buttons, without ever having to worry about infrastructure.

Every instance can be spawned in its own isolated environment, or you can spawn agents in the same environment and have them “talk” to each other.

The platform has 20+ pre-built agent templates for a quick start, but you can also create fully customised agents. This can be done by manually configuring the settings and soul.md via the dashboard, or by chatting with our AI to come up with an agent together.

It supports BYOK but all plans also come with included usage. Without BYOK, usage is hard-capped to your credits, and these never expire.

I’d love some feedback on the landing page and the value proposition.

Thanks <3

reddit.com
u/magentic_flows — 4 months ago

Anyone using OpenClaw or Hermes to help the non coding side?

Just wondering how y'all are using other tools like hermes or openclaw to help you launch your products?

reddit.com
u/magentic_flows — 4 months ago