Hey guys, I've been building a small experiment around AI agents. I’m just trying to see if developers or people that use ai for heavy workflow would find something like this useful?

The basic idea is:
You describe a task - the system figures out what specialist is needed - finds the best available agent - delegates the task - returns the best result.

So instead of you having to figure out which AI/tool/agent to use, the network handles the procurement for you and gives you the best match based on your task.
I've got a basic working prototype now and I'm looking for people to try it and tell me where the idea falls apart.

I'm particularly interested in tasks where you'd normally need to use multiple tools or hire someone.
I'm genuinely trying to build something useful, any feedback would be appreciated. I’ll drop a link in a few days if anyone would actually be interested in trying this out.

If you think this is genuinely crap and no one would use is, that’s great too.

Cheers everyone 😁

I want to be honest about something I got wrong when we started building agent workflows for customer-facing use cases. I assumed the hard part was the agent logic, the prompting, the tool use, the output formatting. It isn't. The hard part is the data layer underneath it.

Specifically the identity resolution layer. When a customer interacts with an agent, the agent needs to know who that customer is across all the ways they've ever interacted with the company. The email they used to sign up. The device they're on now. The support ticket they submitted six months ago under a slightly different name. The purchase they made before they had an account. If those signals aren't unified into a single coherent profile before they hit the agent context, the agent is working with a fragment of the picture and making decisions accordingly.

What I underestimated was how much of the customer identity problem remains unsolved even in companies with mature CRM stacks. Fragmented identifiers are the norm, not the exception. The same person shows up differently depending on which channel they came through and without an identity resolution layer explicitly stitching those views together the agent inherits all that fragmentation.

The vendors that are worth looking at for this are the ones building on deterministic identity resolution rather than probabilistic inference. Deterministic resolution only asserts a match when there's a confirmed signal linkage, which means the customer profile the agent works from is built on confirmed observations rather than modeled guesses. The coverage is lower but the error profile is much cleaner for a use case where a wrong identity match gets surfaced directly to a customer.

Curious to know from people actually deploying AI agents in production.

I’m a big believer in AI. As a copilot it is already amazing — dev, recruiting, sales, research and almost every role.

But when it comes to fully autonomous AI agents, how many are actually successful in production today?

Not demos or POCs. Agents actually running with minimal human intervention, saving meaningful cost or generating good profits.

Once we add guardrails, approvals, monitoring and exception handling, are they really autonomous anymore?

I see dev work as one area where agents are already very strong.

Would love to hear some real production examples and ROI numbers.

Create a free MCP server for your website or organization. It allows direct integration with any other LLM or agent.

https://robauto.ai/create-mcp

I recently built a world model harness that coordinated a dozen research agents to maximize my eval metrics and ship breakthroughs. The goal was to emulate an ASI loop in small multimodal masked reconstruction eval. We took geospatial input modalities and built a mesh network, fusion, and reader layers to 25x our base score. It was amazing to see real scientific breakthroughs!

I started with an install on a single Hetzner $10 VPS server and fully gave Hermes full access to be my sys admin, network admin. I already had 7-8 others for my MSP business (army of 1) and knew that I wanted to downsized my VPS fleet and move hosts with Hetzner's pending price increase. Netcup would be my new home with a few of their bare-metal boxes.

I purchased the first box, provisioned it and gave Hermes access and told him to clone himself. He cloned himself with no issues. I purchased 3 more boxes and gave him those also to provision according to my standards. Done. Apps deployed with data/databases moved. We even converted his old self (original server) as a warm standby. He backs himself up to an S3 and his warm-standby pulls it down every 15-minutes, pings is new box to make sure it's up, he's running and Telegram is running. If he's dead, new box turns on and messages me in telegram to let me know.

He does EVERYTHING for me. I was already using LiteLLM with Open WebUI so I've always kept plenty of provider API keys. All of them are assigned to him through LiteLLM as a virtual key. Makes it easy to track spending. I've been a little wild with him. He's the orchestrator/conductor. He delegates tasks to other models. He's pretty amazing with the right guardrails and prompts.

I definitely wouldn't recommend or encourage that anyone give their Hermes agent the access that I've given mine, because there have been some growing pains. We've also developed some really amazing tools/products/services and even just sold a subscription to a product that i had an idea for (started ideation/discovery on a Wednesday and sold the subscription the following Tuesday for $500/mo).

I probably have 15 products in some phase of development right now. All of them are customer-facing for SMB.

I've been keeping my family and relatives unaware that I have an AI agent (Folk) running my iMessage, basically answering people and giving them my availability based on my schedule. I've had it for about 3 months.

I play pickleball every Sunday, and when my sister sent me her official wedding invitation (also on a Sunday), it responded automatically to her saying I couldn’t go, and they had a back-and-forth where my sister said I (the bot) offended her.

Should I go to her wedding and explain everything or stay home?

(I just know everyone would be pissed if they found out I had an AI talk to them for 3 months.) Also, we're 6 siblings and I've never been that close to her.

Does anybody keep its Obsidian vault up to date and want ai agents to access it so it has your context ? How do you do it and if any pros/cons would love learn more

I'm so done with Poke. It has the worst memory OAT, and all the good features are on Pro, which is $20 a month. And worst of all, this whole thing is vibecoded.

The entire product is made by a bunch of amateurs, and I run into bugs all the time.

What's the best AI agent currently? Preferably one with a free trial.

This post is based on a video where I show how I declutter my Hermes setup when my agent gets sluggish again.

Give Me a Minute of Your Time

Most people do not realize how much baggage piles up inside an agent. Every session starts with the same luggage, whether you need it or not. And that luggage costs you money on every single reply.

The Problem: Context Bloat

Your Hermes has four places where junk accumulates: memory, toolsets, skills and cron jobs. All four get loaded at every session start. Anything that sits there but never gets used wastes context and tokens, invisibly, but constantly.

The good news: you do not have to delete anything. You just have to tidy up. Here is how I do it.

1. Reduce Memory Size to 1300 Characters

Memory gets loaded into context at every session start and wastes tokens. That is why I keep my memory small, or move things out that do not belong into every session.

Prompt to Copy – Clean Up Memory

Go through memory and see how much memory is above 1300 characters and if it makes sense to reduce it to 1300. Also search memory entries that should be outsourced to skills so they only get loaded when actually needed. Try to not destroy anything.

Copy it, paste it into the chat with your Hermes and send it. It does the rest.

2. Unload Unused Toolsets

Every toolset adds tokens to your system prompt. So it wastes context even if you never use the tool. I always feel this makes a huge impact, the effect is immediately noticeable.

Prompt to Copy – Review Toolsets

Please list all unnecessary tools for all my gateways, tools that never get used in that specific gateway. And then if I confirm, disable those tools to reduce context bloat. Do not delete anything. Try to not destroy anything.

3. Clean Up Unused Skills

Skills work like toolsets: they get loaded at session start even if you never use them. Only loading what is necessary saves noticeable context.

Prompt to Copy – Review Skills

Please list all unnecessary skills for all my gateways, skills that never get used in that specific gateway. And then if I confirm, disable those skills to reduce context bloat. Do not delete anything. Try to not destroy anything.

Same logic as toolsets: list, confirm, disable.

4. Cron Jobs – The Silent Killer

Unused cron jobs are the hidden token eaters. You do not have them top of mind, so they build up over time. Every job that runs but produces no result costs you on every run.

Prompt to Copy – Review Cron Jobs

List all cron jobs that do not have a real reason or do not produce a result or are unnecessary. And then after my confirmation, disable them. Do not delete. Try to not destroy anything.

What That Gets You

None of these steps is a miracle on its own. Together they make a noticeable difference: fewer tokens per reply, faster sessions, and an agent that feels snappy again.

The principle matters: nothing gets deleted, everything is just disabled or moved to the right place. Memory shrinks to what matters, skills and tools only load when needed, and dead cron jobs stop running into the void.

And when your agent gets sluggish again, you now know the four levers. Ten minutes of work, and it is fast again.

everything you could need is in this post - but if you still want to take a look at my blog or subscribe to my newsletter you can do here: https://blog.holmebengt.com/post.html?id=hermes-declutter

here are the Claude plugins I use on daily basis.

Context7 fixes the stale-docs problem. Ask Claude about a Next.js 15 API and it'll sometimes answer from Next.js 13 muscle memory.

claude mcp add context7 -- npx -y /context7-mcp

It resolves the library first, then queries the real docs before answering. I stopped getting confidently wrong API signatures after adding this one.

GitHub MCP server connects Claude to your actual repo instead of whatever code you pasted in.

claude mcp add github --scope user --transport http https://mcp.github.com

This is the one that turns "write me a fix" into "read the issue, find the file, open the pull request." Worth the OAuth step.

Postgres MCP gives Claude read access to your schema and lets it write and run its own queries.

claude mcp add postgres -- npx -y u/modelcontextprotocol/server-postgres postgresql://readonly@localhost/mydb

Read-only connection string. Not optional. I ask questions in plain English now instead of hand-writing joins, and the schema introspection means it stops guessing column names.

Claude-Mem solves the part that bugs me most: every new session starts from zero. It writes project context, decisions, and conventions to a local memory store so I'm not re-explaining the auth pattern every Monday morning.

Brave Search MCP gives Claude live web access instead of whatever it learned during training.

claude mcp add brave-search --env BRAVE_API_KEY=YOUR_BRAVE_API_KEY -- npx -y u/brave/brave-search-mcp-server

You need a Brave Search API key first; grab one from their developer dashboard before running this. Once it's connected, Claude can pull current prices, check what actually shipped this week, or verify a claim instead of guessing from a stale training cutoff. I use it mostly for the second one, catching myself before I state something as fact.

Each one is a single claude mcp add and a restart. The plugin system that bundles skills, commands, and hooks together sits on top of this as a separate layer.

Whenever I need an AI agent skill, I end up searching GitHub, Reddit, X, and random recommendations.

Maybe I'm missing something, but is there a trusted directory/registry for AI agent skills yet?

Right now it feels hard to know what's actually good, maintained, and safe to install.

I've been working on something called Behave for a while and I think I'm finally at the point where I need people who didn't build the damn thing to try it.

Basically, it's a testing/evaluation tool for AI agents.

The idea isn't just "did the AI give the right answer?"

I'm trying to catch shit like:

• making shit up
• jumping to conclusions too fast
• giving unsafe advice
• getting stuck on a bad assumption
• forgetting or mixing up information from earlier in a conversation
• failing to correct itself when you give it new evidence
• getting worse when you change the prompt/model
• comparing two versions of an agent to see if it actually got better or just seems better

I've built a pretty ridiculous amount of infrastructure around it at this point — testing, scoring, failure tracking, multi-turn conversations, baselines, statistical comparisons, etc.

But here's the problem:

I've been the one testing my own shit.

That's not exactly a great way to prove that it works.

So I'm looking for maybe 5–10 people willing to try it and fuck with it for 10–20 minutes.

You don't need to be an AI researcher or anything. If you're building an agent, running local models, using Ollama/vLLM, messing with OpenAI-compatible APIs, or just have an AI project you want to throw at it, that's perfect.

What I really want is for you to try and break it.

If Behave says an agent failed and you think it's bullshit, tell me.

If it says an agent passed and you think it completely missed something, even better.

If you can't figure out what the hell you're supposed to do when you open it, tell me that too.

I'm not looking for people to tell me it's cool. I want to find the parts that suck before I start taking this seriously as a product.

If you try it, just comment with what you tested and what you found.

And yes, if you manage to make the evaluator look stupid, I'll probably be pretty damn happy about it. That's exactly what I need right now.

if interested let me know and i will send you the link to it

[ Removed by Reddit on account of violating the content policy. ]

I’m recruiting for a UX research study in NYC and specifically looking to hear from people who have deeply integrated AI into their workflows: particularly those using agentic AI tools, memory, personalization features, and/or custom AI workflows.

If you’ve spent a lot of time tweaking, configuring, and personalizing AI to work the way you want it to, you may be exactly who we’re looking for.

Would love to hear from some of the serious AI users in here! Please reach out to me or comment if you would like to chat more!!

I've tried a few AI presentation tools but a lot of them struggle when it comes to producing slides that are both accurate and actually usable without heavy editing. After testing different options this two stood out the most for me:

Chatslide- One of the more useful tools I came across. it can take inputs like PDFs, images or even links and convert the into structured slide decks or simple video presentations. You can also combine content sources with style templates which helps if youre working with branded or structured materials. There's a free tier as well which makes it easy to try out.

Canva- Still one of the most practical tools in this space. its AI presentation feature can generate a rough deck from a short prompt and then you can refine everything using Canva's built in design tools. It works especially well if you care about presentation quality and visual polish.

Overall most of the tools are decent at generating structure design but the actual content quality still depends heavily on the input you give them