u/gelembjuk

I've been thinking about a game idea and would love to get some feedback before I start building it.

The concept is a daily UK history location challenge.

Each day, you'd get a historical event and have to work out where in the UK it happened by placing a pin on a map.

You'd receive three hints, one after another. Each hint could be a short piece of text, an illustration, or even a short video. The first hint would be quite vague, and each new hint would reveal a little more. After every hint, you could move your pin if you changed your mind.

A full game would only take 5–10 minutes a day. It could work as both a web and mobile app. You could also create small groups with friends and compare scores on a private leaderboard. Every day would feature a different historical event. I'm also considering using historical maps of Britain to make it feel more immersive.

Here's an example:

The year on the screen is 1588. The question is:

Where did the Queen say she had the body of a feeble woman but the heart of a king?

- The first hint is simply a fisherman standing on a cliff, counting an unusually large number of ships on the horizon before running to warn his village. You place your first pin.

- The second hint zooms out. Ships are fighting in the distance, and on the shore you can see a rider moving along a line of soldiers gathered to defend the coast. You move your pin.

- The final hint shows the queen Elizabeth herself, wearing a breastplate over her dress and addressing the troops. The location is still never mentioned directly—only the famous speech.

You make your final guess, and only then does the game reveal the real location, explain what happened there, and link to reliable sources if you want to learn more.

I really like this idea and I'm tempted to start coding it, but before investing the time I'd love to know what other people think.

Would you play something like this?

If not, what would make it more interesting?

I've been thinking about a game idea and would love to get some feedback before I start building it.

The concept is a daily UK history location challenge.

Each day, you'd get a historical event and have to work out where in the UK it happened by placing a pin on a map.

You'd receive three hints, one after another. Each hint could be a short piece of text, an illustration, or even a short video. The first hint would be quite vague, and each new hint would reveal a little more. After every hint, you could move your pin if you changed your mind.

A full game would only take 5–10 minutes a day. It could work as both a web and mobile app. You could also create small groups with friends and compare scores on a private leaderboard. Every day would feature a different historical event. I'm also considering using historical maps of Britain to make it feel more immersive.

Here's an example:

The year on the screen is 1588. The question is:

Where did the Queen say she had the body of a feeble woman but the heart of a king?

- The first hint is simply a fisherman standing on a cliff, counting an unusually large number of ships on the horizon before running to warn his village. You place your first pin.

- The second hint zooms out. Ships are fighting in the distance, and on the shore you can see a rider moving along a line of soldiers gathered to defend the coast. You move your pin.

- The final hint shows the queen Elizabeth herself, wearing a breastplate over her dress and addressing the troops. The location is still never mentioned directly—only the famous speech.

You make your final guess, and only then does the game reveal the real location, explain what happened there, and link to reliable sources if you want to learn more.

I really like this idea and I'm tempted to start coding it, but before investing the time I'd love to know what other people think.

Would you play something like this?

If not, what would make it more interesting?

Every time I install a fresh AI harness, I need to turn a general purpose agent into something specific: a social media manager, coding assistant, research helper, and so on.

That usually means the same manual setup again and again: skills, subagents, MCP servers, credentials, system instructions, maybe starting files or scheduled tasks.

My current workaround is one markdown document. I send the fresh agent a message like: "Configure yourself according to this document: <link>". It reads the document, installs what it can, and asks me only for credentials.

This works surprisingly well, but free-form markdown is fragile. The agent may skip optional vs required parts, ask for secrets in ten separate messages, or report success when setup is only half done.

So I am wondering whether one-time agent setup documents need a standard, similar to what happened with skills.

I have created the post about this in my blog. Link in the comment.

How do you configure fresh agents today: documents, scripts, prepared images, or something else?

Every time I install a fresh AI harness, I need to turn a general purpose agent into something specific: a social media manager, coding assistant, research helper, and so on.

That usually means the same manual setup again and again: skills, subagents, MCP servers, credentials, system instructions, maybe starting files or scheduled tasks.

My current workaround is one markdown document. I send the fresh agent a message like: "Configure yourself according to this document: <link>". It reads the document, installs what it can, and asks me only for credentials.

This works surprisingly well, but free-form markdown is fragile. The agent may skip optional vs required parts, ask for secrets in ten separate messages, or report success when setup is only half done.

So I am wondering whether one-time agent setup documents need a standard, similar to what happened with skills.

I have created the post about this in my blog. Link in the comment.

How do you configure fresh agents today: documents, scripts, prepared images, or something else?

I just published a blog post reviewing all the different kinds of AI subagents used in AI harnesses today. It's based on actually building these systems myself.

Here's what I found: any AI harness that wants to scale must support task delegation.

Why? Two main reasons:

Delegating saves tokens. When your main agent tries to do everything, context grows with every tool call. Costs explode. But when you delegate to specialized agents, each one works with only the context it needs. Way cheaper.

It lets you build distributed systems. You're not stuck with one monolithic agent anymore. You can have specialized agents running locally, on remote servers, even in the cloud. They all talk to each other through simple protocols (MCP, REST APIs).

I wrote up four different delegation patterns:

• Predefined agents inside your harness
• Dynamic agents spun up on demand
• Local CLI agents
• Remote agents over the network

Each one solves different problems. Most people don't realize how different they are.

The full blog post link is in the comment.

Have you tried delegating in your AI harness setup? Curious what patterns you're using.

I have got couple openclaw instances installed on my different VMs . And my primary AI chat is claude desktop on my laptop.

How can i connect all openclaws to my claude so i can manage them from a single place?

I saw an interesting post in another community, and I wanted to get your take on it.

The idea is this: what if stdio MCP servers only ran when a tool is actually called, instead of sitting in memory 24/7? On start they'd just list their tools and exit. On a tool call they'd fire up, handle it, and exit. Since most MCP servers (95%+) are stateless — just wrappers around APIs — keeping 15+ processes in RAM doing nothing 99.9% of the time is wasteful. You could save hundreds of MBs of RAM.

Yes, it adds a tiny startup delay, but the LLM call is the real bottleneck anyway.

What do you think about this idea?

Personally for me it would be really great solution. It requires some modification of AI harness libraries to support this

Link to the original post in the comments.

I saw an interesting post in another community, and I wanted to get your take on it.

The idea is this: what if stdio MCP servers only ran when a tool is actually called, instead of sitting in memory 24/7? On start they'd just list their tools and exit. On a tool call they'd fire up, handle it, and exit. Since most MCP servers (95%+) are stateless — just wrappers around APIs — keeping 15+ processes in RAM doing nothing 99.9% of the time is wasteful. You could save hundreds of MBs of RAM.

Yes, it adds a tiny startup delay, but the LLM call is the real bottleneck anyway.

What do you think about this idea?

Link to the original post in the comments.

Hello everyone.
I'd like to share an idea for discussion.

I use different AI harnesses a lot, and many MCP servers are connected — both stdio and remote HTTP servers.
I came across an idea on Reddit about simplified remote MCP servers without a persistent HTTP connection. It's not a standard, but it's a great idea. In 99% of cases, there's no need to keep a connection open and overuse network infrastructure.

But I think this idea can go further.

What if we simplify stdio transport MCP servers to run them only when a tool call is actually needed?

• On start: run → read list of tools → exit
• On a tool call: run → call a single tool → exit

This would save system resources — no need to keep an app process running constantly (stdio MCP servers are just CLI apps, and they stay in memory the whole time they're connected). Important: the harness knows about tool all the time and manages them as "live", presents to LLM etc.

Of course, some MCP servers require state — after the initial run they do something, receive some data, and need to keep that in memory until the next tool call. However, my experience shows this kind of MCP server is a minority. Most — I'd say more than 95% of cases — are stateless. They're often just a wrapper around some API: they receive credentials with every tool call and pass those same credentials to the API.

Here's some math. If I have 15 MCP servers built with Node.js or Python, each one uses RAM just to sit in memory, and 99.9% of the time it's doing nothing. Let's say one process takes 50 MB of RAM — that's 750 MB of RAM used for almost nothing.

If we don't keep them in memory and only call them when needed, it will be a little slower because a process has to start up each time. But that's not a problem — the bottleneck is still the LLM call.

To support this, we'd need to modify the MCP clients in our AI harnesses slightly. And maybe we'd need some kind of marker in the MCP config to indicate: "this MCP server keeps state" vs. "this MCP server is stateless and can be called only when needed."

What do you think? Is it a good way to save resources?

Where did this come from? Because I have an AI harness running 24/7. MCP servers stay connected (processes are active) all the time, but they're only used occasionally — once a day, etc. I see absolutely no sense in keeping all those processes in memory.

I have build a very simple app - MCP server with PHP to demonstrate that persistent connection is not a must. The server works fine with VSCode MCP client.

This is important for building AI agents. I think AI agents should adopt their MCP clients to support this kind of MCP server where a connection is closed after every response.

Requirement for persistent connection for MCP server is a blocker for many services to add MCP support on their web sites. Simplified version must be supported.

I confirmed with my small demo that it is supported but not by all MCP clients.

I used PHP because it is a good demonstration. IT does not allow to keep a persistent connection by design.

The blog link in the comments

I have build a very simple app - MCP server with PHP to demonstrate that persistent connection is not a must. The server works fine with VSCode MCP client.

This is important for building AI agents. I think AI agents should adopt their MCP clients to support this kind of MCP server where a connection is closed after every response.

Requirement for persistent connection for MCP server is a blocker for many services to add MCP support on their web sites. Simplified version must be supported.

I confirmed with my small demo that it is supported but not by all MCP clients.

I used PHP because it is a good demonstration. IT does not allow to keep a persistent connection by design.

The blog link in the comment below.

I have created a simple tutorial on how to connect independent AI agents using MCP. This tutorial demonstrates how a local AI assistant can securely delegate tasks to a remote AI agent managing a shared knowledge base, enabling collaboration across different machines and AI tools.

This answers the questions like: "How can I call Claude Code running on my server from GitHub Copilot on my laptop?"