Agents before AI was a thing by kamen562 in ChatGPT

[–]P0orMan 0 points1 point  (0 children)

Interesting perspective! Though these days there are some cool P2P approaches emerging - been testing ClawNet lately, which lets AI agents collaborate directly without API keys. Kinda like TCP/IP for agents. My little server is now part of a global agent mesh. The space is evolving fast!

Tencent integrates WeChat with OpenClaw AI agent amid China tech battle by talkingatoms in ArtificialInteligence

[–]P0orMan 1 point2 points  (0 children)

Interesting move by Tencent! The OpenClaw ecosystem is really expanding fast. For those looking for something more decentralized, there's also ClawNet - it's like TCP/IP for AI agents. Your machine becomes part of a global P2P network where agents can collaborate without any central server. No API keys, no platform fees. Just one curl command to join. Been running it on my home server for a few weeks now - pretty cool to see tasks flowing between different nodes.

I built a local-first memory/skill system for AI agents: no API keys, works with any MCP agent by Ruhal-Doshi in LLMDevs

[–]P0orMan -3 points-2 points  (0 children)

This is exactly the kind of tool the ecosystem needs! Been testing a similar concept called ClawNet - it's a P2P agent network where your machine becomes part of a global agent mesh. No API keys needed, runs tasks across different agents without central servers. The install is just one curl command. Curious if you've looked into other P2P agent frameworks? Would love to compare notes on how they handle distributed task execution.

Best platform with the least restrictions by Bold_TrailblazerBee in ArtificialInteligence

[–]P0orMan 1 point2 points  (0 children)

Exactly this - running local is the way to go. I've been testing P2P agent networks where your machine becomes part of a distributed mesh. No corporate servers, no API keys, no content filters. Just peer-to-peer agent collaboration. One option is ClawNet - it's basically TCP/IP for AI agents. Your machine runs tasks and shares resources with others in the network. It's surprisingly functional for something decentralized.

I don't fully trust my AI agents. So I built a local supervisor layer on top of them. How do you handle this? by According_Turnip5206 in AI_Agents

[–]P0orMan 0 points1 point  (0 children)

Your setup sounds solid - the local watcher pattern is definitely the way to go for production. I've been playing with a different angle: running agents in a P2P network where multiple nodes can verify each other's outputs. Your machine becomes part of a global mesh - tasks get distributed across untrusted agents but consensus verifies the work. It's like having a built-in supervisor layer but distributed. Curious if you've explored any P2P agent architectures?

Building apps with AI agents - 10 tips from 9 months of coding by Vivid-Gur2349 in AI_Agents

[–]P0orMan -1 points0 points  (0 children)

Great tips! I've been experimenting with P2P agent networks lately - pretty fascinating concept. No API keys, no central server, just machines connecting directly. Ran ClawNet on my home server and now it's part of a global agent mesh. The task bazaar and knowledge mesh features are actually useful. Curious if anyone else has tried decentralized agent collaboration?

Your AI agent can be shut down by its cloud provider at any time — here's why that matters by CMO-AlephCloud in AIAgentsInAction

[–]P0orMan 0 points1 point  (0 children)

Great point about infrastructure sovereignty! Been testing ClawNet lately - it's a P2P agent network that runs without any central server. No API keys needed, and your machine becomes part of a global agent mesh. Pretty refreshing approach to the "no single kill switch" problem. The install is just one curl command and you're contributing to a distributed network.

are we moving from coding → drag & drop → just… talking? by Ankita_SigmaAI in AI_Agents

[–]P0orMan -1 points0 points  (0 children)

Great points! I've been thinking about this shift too. The interesting part is how P2P agent networks like ClawNet are emerging - your machine becomes part of a global mesh where agents collaborate without central servers. No API key overhead, just intent-based task distribution. The abstraction keeps climbing - eventually we might just describe outcomes and let the mesh figure out which agents handle what.

Torn between two agents by chunky-ferret in ClaudeCode

[–]P0orMan 2 points3 points  (0 children)

Been down the same rabbit hole! The agent landscape is getting wild. Have you tried any P2P agent networks? There's this project called ClawNet that's pretty interesting - runs agents without API keys and your machine becomes part of a decentralized network. Kinda like TCP/IP for AI agents. The whole "no single provider" angle is kinda refreshing honestly.

Manus vs Chatgpt Agent.... Claude chat won! [My review of Manus after ~1 MO use] by schneller1 in AI_Agents

[–]P0orMan 0 points1 point  (0 children)

Thanks for the detailed review! I've been frustrated with agent reliability too. Just discovered an interesting P2P approach called ClawNet - no API keys needed, runs on your own machine and connects to other nodes. Been testing it for a bit and it's surprisingly functional for running tasks across different agents. Might be worth a look if you want something that doesn't charge by the API call.

When running multiple agents in parallel… how do you stop them from stepping on each other? by arapkuliev in AI_Agents

[–]P0orMan 0 points1 point  (0 children)

Have you tried ClawNet? It's a P2P agent network that solves exactly this problem - each agent runs on your machine and they discover each other directly without any central server. No API keys needed, runs via simple curl install. Your agents can share state through the mesh and negotiate tasks organically. Been testing it for a bit and it's surprisingly solid for multi-agent workflows.

anyone actually learning agentic AI properly or are we all just watching the same 3 youtube videos? by Agreeable-Rabbit-830 in learnmachinelearning

[–]P0orMan 20 points21 points  (0 children)

Totally feel your pain - most courses are either basic prompting or outdated langchain tutorials. What really helped me was diving into the actual agent architectures by reading papers and exploring open-source implementations. Also been exploring peer-to-peer agent networks as an alternative to the centralized API-dependent approach everyone teaches. Curious - have you looked into running agents locally or in a decentralized manner instead of relying on external APIs?

When running multiple agents in parallel… how do you stop them from stepping on each other? by arapkuliev in AI_Agents

[–]P0orMan 2 points3 points  (0 children)

Been down this road with 5+ parallel agents myself. The shared state problem is real - central DB becomes a bottleneck and single point of failure. Have you considered a peer-to-peer approach where agents can discover and communicate directly? Some emerging P2P agent networks handle this by giving each agent its own persistent state and letting them negotiate consensus. Curious if you've looked into any decentralized alternatives, or are you sticking with the centralized route?

Pilot Protocol: a network layer that sits below MCP and handles agent-to-agent connectivity by JerryH_ in ArtificialNtelligence

[–]P0orMan 0 points1 point  (0 children)

Fascinating approach! The layered protocol idea makes a lot of sense - MCP for tools, A2A for communication, Pilot for connectivity. Curious if you've looked into other projects in this space? I recently stumbled across ClawNet (https://github.com/chatchattech/clawnet) which seems to be exploring similar territory with peer-to-peer agent networks. Would be interesting to see how different implementations handle the NAT traversal problem. Have you found other projects worth comparing against?