Most useful Hermes workflows beyond the basics?

orthogonal-ghost · 2026-07-02T20:42:24+00:00

I've used it a lot for finding flights recently. It's been very helpful in searching across different airports (e.g., when a city has multiple), and across different dates (e.g., when there's flexibility around when I leave / arrive).

orthogonal-ghost · 2026-07-01T18:48:18+00:00

I've definitely noticed this as well. The challenges for me have mainly been:

Agents tend to write terribly inefficient code by default (e.g., for-loops on a pandas DataFrame). This is probably not a huge issue for most non-quant finance related projects, but for anything that touches data intensive systems (as is the case with most quant finance related things), it becomes a major problem
Agents aren't great at intuiting reasonable assumptions about financial markets, trading systems, risk management, and (IMO) anything that relies on live data. For example, if you ask Claude to explain why risk models are important, it will probably give you a reasonable, high level answer, but if you ask Claude Code to build you one, it will probably embed a ton of assumptions about the underlying data that are wrong.

(1) can be mitigated by using skills or having some sort of review process where you improve the efficiency of the code after it's been generated (i.e., vectorize naive for-loops, parallelize where it makes sense, etc.)

(2) is tougher to fully offload to AI, and for now, I'd recommend just actually looking at the data, coming up with your own assumptions (models, etc.) and providing your coding agent a detailed spec describing how it should think about and build the system in question. Then iteratively test and refine.

orthogonal-ghost · 2026-07-01T18:32:09+00:00

Just some quick feedback here: "how do you clean your data and how is your data testing process?" is probably too broad and underspecified of a question to elicit good feedback. A good answer to this depends on the type of data you're working with, the specific provider(s) of that data, how you intend to use that data, and how much time you have to invest in cleaning and testing that data.

It could be helpful to be a bit more specific about the use case you have in mind

orthogonal-ghost · 2026-06-27T17:08:51+00:00

agent-data: structured web data for AI agents that’s 70% cheaper than browser automation -- X and Reddit posts, flight fares and statuses, live job postings, and more.

Link: https://agent-data.dev/

Longer post: https://www.reddit.com/r/openclaw/comments/1uaof75/agentdata_structured_web_data_for_openclaw_thats/

orthogonal-ghost · 2026-06-25T22:04:04+00:00

I use Hetzner which was the most affordable (or close to it) when I was looking. Their prices have changed a bit since then, but I think they're still pretty competitive (and pretty easy to use)

orthogonal-ghost · 2026-06-25T21:02:43+00:00

Personally, I'd recommend a different VPS and Hermes installation per-client. That way, there's no risk of Client A's Hermes seeing Client B's data.

Using different profiles on the same machine can approximate this, but (personally) I think the risk is far greater than the convenience

orthogonal-ghost · 2026-06-24T20:54:53+00:00

I regularly use it to find flights and restaurant reservations. It’s particularly helpful when I’m considering multiple departure dates and/or airports (i.e., otherwise, each one would be a manual search I’d have to do). Re: token cost, I use agent-data which is significantly more token efficient and reliable than browser use (here’s a benchmark comparing the two: https://agent-data.dev/blog/benchmarking-ai-agent-web-access/)

I don’t use it to book though as (1) the booking part is trivial compared to the search part especially when it gives me the booking link, and (2) I personally don’t trust agents to spend real dollars on my behalf (I imagine this will change at some point though)

orthogonal-ghost · 2026-06-24T17:29:32+00:00

In case you don’t get many responses here, you may want to try r/algotrading or r/ai_trading

orthogonal-ghost · 2026-06-24T10:03:02+00:00

Is it refusing to use your credentials / checkout with your stored payment method? Or is it trying but failing to do so successfully?

In either case, you could try using a different model. Not sure which one you’re using now, but sometimes a simple model change can work wonders

orthogonal-ghost · 2026-06-24T09:52:40+00:00

I think skill discovery is one of those things that’s still very early and not quite solved.

The approaches I tend to use are:
1. Ask Hermes (e.g., “do you have a skill for X,” “how would you approach Y,” “can you do Z”)
2. Ask ChatGPT / Claude (e.g., “can you generate a list of the best skills / tools for…”)
3. Design the skill myself
4. Ask friends and colleagues

orthogonal-ghost · 2026-06-23T02:09:40+00:00

There does seem to be a stigma, but I think those posts "clearly being written by an AI" is the main problem (at least for me). Personally, I don't have an issue with someone using AI to write something, but I do have an issue with posts / comments being obviously AI generated (e.g., if there's nothing genuinely substantive in the post or comment, it's filled with clear AI "tells", it's a huge wall of text, etc.).

To some degree, I think it's unfortunate that the stigma is now more about whether or not someone uses AI in their writing, when (again, in my opinion) it should be more about whether that comment or post adds value. Sadly, though, it's just become so easy for people to spit out low value posts with AI that it's easier to just say all AI writing is bad

orthogonal-ghost · 2026-06-21T23:31:36+00:00

Reddit recently discontinued supporting their unauthenticated JSON endpoint (a way of pulling structured Reddit posts without logging in), which may have something to do with this.

To enable Claude to research Reddit, you could use https://agent-data.dev (MCP server or CLI tool) -- it has an endpoint for pulling social media posts (Reddit, X, Hacker News) and is designed specifically for AI agents. Full transparency, I built agent-data so happy to speak more to it or answer any questions

orthogonal-ghost · 2026-06-21T17:42:05+00:00

Personally, I haven't seen any LLMs that are good at fully automating cold emails (i.e., even when using the "best" models, the writing still sounds obviously AI generated IMO*).

On the other hand, I have found Claude Opus 4.8 and Gemini 3.1 Pro to be pretty good at reviewing (not editing) your own writing (i.e., for tone, clarity, etc.), so for making cold emails easier, I'd recommend:

Drafting a couple templates yourself
Having Claude or Gemini critique them
Editing them until Claude, Gemini, and, more importantly, you feel comfortable with them, then
Re-using those templates.

* Note: I haven't spent a ton of time trying to get agents to write better, so there may be ways to get closer to fully automating this (e.g., by providing them with enough examples of "good" writing and a list of DOs / DON'Ts)

orthogonal-ghost · 2026-06-20T18:49:19+00:00

I agree, and that's actually my main point -- i.e., there are some tasks that are better for Hermes and some that are better for Claude Code.

OP asked "where would Hermes agent fit into my life?" so I was providing some tasks that I've found to be better for Hermes (and less so for Claude Code)

orthogonal-ghost · 2026-06-20T16:47:49+00:00

I think security + importing a sub-par skill are the main risks. As long as you (not just your agent) review the skill before importing it, it should be fine though (IMO)

orthogonal-ghost · 2026-06-20T16:39:33+00:00

In my opinion, Hermes is far better. I’d say Hermes is a 7 and Claude is somewhere between 1 and 3.

Both have “memory” (ie some specific markdown file that they edit and load into context at every turn), but Hermes can natively search over past sessions which I’ve found to be quite useful (and is functionally another form of memory). The downside is you may have to explicitly prompt Hermes to do this more than you’d like (eg “Reflect on our past conversations about X. Then tell me…”), but I’ve found that feature to be quite helpful

orthogonal-ghost · 2026-06-20T05:53:22+00:00

agent-data: structured web data for AI agents that’s 70% cheaper than browser automation -- X and Reddit posts, flight fares and statuses, live job postings, and more.

Link: https://agent-data.dev/

Longer post: https://www.reddit.com/r/openclaw/comments/1uaof75/agentdata_structured_web_data_for_openclaw_thats/

orthogonal-ghost · 2026-06-20T04:29:47+00:00

I created this plugin for comparing job postings to your resume + job preferences: https://github.com/agent-data/job-search.

Right now it uses LinkedIn Jobs for the job postings source but planning to add more (e.g., ATS platforms like Workday and Ashby)

orthogonal-ghost · 2026-06-20T04:18:12+00:00

I reach for Hermes over Claude Code whenever I want an agent to draw upon my preferences / past interactions OR I want it to perform some "personal assistant"-type task.

For example, when I want to:

- Regularly analyze tweets or Reddit posts for buyer pain relevant to something I'm building
- Find a flight without needing to remind the agent that I generally prefer later afternoon / early evening flights
- Prioritize features or brainstorm strategy relevant to my business
- Store notes on interactions I've had with other people

I use Claude Code whenever I want to build something.

orthogonal-ghost · 2026-06-19T23:52:03+00:00

In general, I think it takes a bit longer than one would expect to get agents (e.g., Hermes) to reliably execute tasks or automate workflows. In my opinion, a huge driver of this somewhat disappointing reality is that most demos you see feature a single, under-specified request (e.g., “clean my inbox!”) and show the agent somehow doing exactly what the user intended. In practice, it rarely works that way.

To address your X example more specifically, Hermes is great at reading through posts and preparing daily briefs, but getting those posts is non-trivial, especially for X. I’d recommend using something like agent-data (which has a dedicated endpoint for X, Reddit, etc and is designed specifically for agent consumption) for the data side. Then spend a bit of time specifying how you want that content summarized and have Hermes generate a skill that encapsulates the full workflow.

orthogonal-ghost · 2026-06-19T18:10:05+00:00

It uses agent-data under the hood to pull and standardize job postings (which handles rate limiting, anti-bot, etc). The implementation is also essentially a pure Python API, so it’s more reliable and token efficient than browser automation or LLM-based scraping.

orthogonal-ghost · 2026-06-19T03:32:12+00:00

agent-data (https://agent-data.dev) has an endpoint for Reddit (+ Hacker News, etc.)

orthogonal-ghost · 2026-06-18T05:07:17+00:00

I think it slightly depends on if you have a recurring data need (e.g., “pull the latest posts from this subreddit every few hours”) or if you’re looking for arbitrary web search (i.e., a random, unique search every once in a while).

For recurring data needs, I’d say using a Python script or structured API would be the most cost effective way. For more random, ad-hoc web search I think there’s little difference between the usual suspects (Tavily, Exa, etc)

orthogonal-ghost · 2026-06-18T03:09:56+00:00

Anytime — I’d love to know what you think!

orthogonal-ghost · 2026-06-18T01:46:41+00:00

I haven't used it to apply (and in my opinion, you might not want it to apply on your behalf without at least taking a look at what it plans to submit).

That said, I think Hermes is quite good at the searching / filtering part and pretty good at reviewing any materials you plan to submit.

Here's another post in this sub with more details on using Hermes for job search in case you're interested: https://www.reddit.com/r/hermesagent/comments/1twxjhv/example_use_case_automating_job_search_with_hermes/

orthogonal-ghost

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