Launch HN: AgentHub (YC W24) – A no-code automation platform
We’re Rahul and Max, co-founders of AgentHub.dev (https://www.agenthub.dev/). We automate repetitive workflows for businesses using LLM-powered automations. Our platform lets you build and host these automations to emulate employee workflows in a scalable way. Here’s a demo video: https://www.youtube.com/watch?v=BD9aoyKPOjs
We started 9 months ago while lurking in the Auto-GPT discord and seeing thousands of non-technical users struggle to clone the repo or set up their environments. We were excited by the concepts of Agents so we built and deployed a (very ugly) web app within a few days so anyone could experiment. We started to see people literally begging the Agents to complete simple tasks and giving up due to cost/frustration. Seeing the type of relatively simple work people were trying to automate with AI was the catalyst for what we ended up building.
We decided to make a drag-and-drop automation builder so these users could piece together their ideal automations instead of begging the agent to do that same task and failing. V1 was a borderline un-usable series of drop down menus but evolved into the canvas based workflow builder it is now.
It’s somewhat similar in concept to Zapier or Make.com except we’re aiming to automate much more complex work end to end instead of just speeding up simple tasks. We originally described it as Zapier on crack but as it's gotten more complex, some people compare it to existing RPA platforms like UI Path. We like to call it an 'LLM-based Intelligent Automation Platform'.
Our biggest challenge from the very beginning has been balancing usability and complexity. We wanted anyone to be able to understand it while still being powerful enough for people to get creative. Building the framework has been an extremely iterative process of users getting confused (for good reason) and us tweaking our approach. We still have a ways to go in terms of usability but are proud of where it’s at. Eager to hear your feedback!
Here are 3 template automations we built to give people a starting point. I think the real beauty of the platform is how personalized the automations users create are but these general templates give a nice idea of how it works.
https://www.agenthub.dev/templates/hr_hiring/linkedin_profil... https://www.agenthub.dev/templates/media_news/autonomous_twi... https://www.agenthub.dev/templates/sales_crm/automated_sales...
These templates are on the simpler side. Our power users nest automations, trigger them via webhook and have them running at a pretty surprising scale. The highest we’ve seen was last Friday with a single user running 5k automations within a few hours. The unofficial record before that for most automations runs was one of our users who discovered infinite-recursion by accident, but that doesn't count.
We have two main types of users at the moment, people automating their existing businesses work and people using the no-code builder to build new ideas. The first was our original intention, letting any semi technical person in a company spot inefficiency and quickly get a solution deployed to address it. The second and more unexpected type of user has been non-technical founders spotting problems and being able to build APIs to serve niches they’ve found without needing to code.
It’s called AgentHub because I bought the domain for 10 dollars on day 2 of building when I thought we’d be a hub to host and share agents and never both...
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[ 4.8 ms ] story [ 153 ms ] threadWe've slowly been baking more and more logic into the AI nodes to make them easier to use. Adding categorizer and scorers instead of forcing people to define their own functions was a game changer. Definitely the direction we want to head in, thanks for the suggestion.
The other built a cascading prompt engineering pipeline that iteratively tries to improve on it's output in a series of nested steps. They're the ones hitting 5k runs per day because they've nested their automations so many layers deep.
This way of measuring things is kind of falling apart because people can nest automations and loop them to run many times on many values. One 'run' of a heavily nested automation could actually lead to hundreds of runs do to nesting.
My co-founder and I have debated this at length and the only way we see to solve this is to add a credit based system and stop caring about runs altogether. Each node would have a credit cost and each plan would have monthly credit alotment. If you can think of a better way we're very open to suggestions!
Can I ask how your runs are executed? I'm assuming tracking usage is probably trivial, if you're running each process in individual sandboxes.
Runs are basically dynamically generated scripts. Our backend parses the automation definition from the DAG on the frontend, fetches the definitions of each node and stitches it all together to run in a sandbox env. It started off quite simple in the early days but it's become quite an monstrous system with dynamic variables, nesting, looping, credential access and error handling.
I thought it was cool because it was similar to ChatGPTs cursor and was the only non static thing i was capable of building in terms of react components :)
Never considered the IP clash with Zapier until much later. Will definitely consider that with the rebrand.
Couple of questions:
- Are you also looking into doing RPA with your agents, e.g form filling? I see huge potential for LLMs in that space.
- Are you using AgentGPT or similar under the hood? Will the OS repo benefit from your success?
- Are you focusing on a specific ICP/use case to sell to and optimize for? That's usually a challenge for horizontal solutions.
- We know the founders at AgentGPT, they're from Vancouver Canada as well! But no we don't actually use any Agentic frameworks at all. There is no autonomy in AgentHub automations. Rigid automations like we provide were the only way we could find reliable and cost effective value for our early users.
- Yea your spot on, showing people what this can do is our single biggest challenge. We tried the approach of making tons of templates but for a template to be good it has to be general but when automations are general, they seem useless. We've narrowed in on a few ICPs but even then it's hard to know which is the right one to go after. Right now we're just throwing things at the wall, seeing what sticks and tending to our power users.
Here's an example of an automation that scrapes job postings to generate cover letters. The web scraping node here is the part reading the web page. https://www.agenthub.dev/pipeline?agent_id=cLsmah3zRHunw9SaL...
Thanks for calling that out. I'll fix this within the next 24 hours.
Upload list of links to webpage > extract info with AI > output.
It's a different approach in terms of UX though. More like a really smart spreadsheet.
It seems like its prioritization is just an assumption you may have to pivot from.
We really shouldn't be even mentioning the OpenAI calls in pricing since we equate Gemini-pro calls and perplexity-70b to GPT-3.5. We need to come up with new categories for the AI calls included in pricing that make more sense.
We also notice that the bigger our users get, the more they want to consider open source models and fine tuning. Open AI will be removed from the pricing description in the next few weeks once we come up with a better way of equating AI costs between models with a credit based system.
Do you think you'll find yourself widening to more traditional integration and automation use cases? Such as syncing contacts between Monday and Hubspot?
Since day 1 our approach has been to build exclusively based on what our users ask for however that user profile has changed with our pricing. Since our prices have recently been set kind of high, the types of users making requests are more aimed at business use cases and scaled builds rather than streamlining of work. We see requests for use cases like that less often as a result.
Not sure if that's supposed to be clickable, but doesn't seem to be on mobile either
I tried to be fancy and render automations completely dynamically on that templates preview page. Upside is when i change a template automation everything auto updates. Downside is it's rendering a pretty complex object for a simple preview. Gotta address some of that to reduce lag. Sorry about that!
We had the core node logic open source at one point, but closed it because we weren't seeing many contributions and it was less overhead once we started implementing things like node versioning, integrations, credentials, etc.
We still do deploy on-prem for enterprises that need it secure on their own cloud, and will link into open-sourcing a self-hosted version in the futur efor sure!
- Rahul
We noticed a few things though. 1. People who were most excited about no code did not want to contribute code to the project. 2. We were 95% open source because we were dealing with credentials and sensitive info on our hosted servers. This 5% of obfuscation was enough to make contributing annoying since you didn't totally understand how some pieces fit together. 3. We were adding new features and redesigning aspects of the system so often that it felt simpler to close it and accelerate. Features like node versioning and secure credential storage made it all quite difficult to maintain in an open way.
I do still love the idea though. Having people contribute their own integrations would be an absolute dream.
It is not specific to AI, but there are multiple nodes for ChatGPT etc. In the current project I build up a prompt using `template` nodes that include the `payload` from previous nodes in a chain. Although there are other ways of doing it. Then that is connected to the chatgpt node.
Lots of variations on the theme of english pronounciation tend to elide or at least soften trailing consonants.
(I just read that last sentence out to myself twice, once normally, once making a point of pronouncing them fully, and it makes a sufficient example)
My father told me many years ago that it tended to help being heard at a distance so was very useful for public speaking (in the days before everybody was miked up for the livestream/recording).
I started trying it, and not only did it work for that, I discovered that if presenting to a european audience it helped a -lot- for the second language speakers.
Later I discovered it also worked rather well making my brit accent more comprehensible to americans, and later still that I'm easier to lip read too.
If I say AgentHub out loud to myself normally, I end up softening the 't' enough that I can absolutely see people hearing 'asian-hub' from me as well, but if I make a point of turning on my 'better enunciation' mode the 't' becomes crisp to the point where it's almost a 'tuh' sound and I think the result is much harder to mishear.
So ... I think you may find that whether you keep the name or not, experimenting with the trailing consonant thing may be useful to you as well (I speak pretty quickly) for similar reasons.
Free thought, worth exactly what you paid, but hopefully it'll turn out helpful to somebody reading this :D
> In similar positions, the combination /nt/ may be pronounced as a nasalized flap [ɾ̃], making winter sound similar or identical to winner.
https://en.m.wikipedia.org/wiki/Flapping
Fair point that either could apply to AgentHub mind, I was going from pronouncing it as two words and swallowing the 't' as being likely to cause 'asian hub' to be heard, flapping it gets me something more like 'asian dub.'
(I -think- my accent elides more than it flaps, but given I can range from broad lancashire through to BBC English depending on context 'which accent' is an open question; also I may have completely misunderstood something)
Could you change the settings for the demo video, so that we can easily share it?
More for personal use and not quite as polished but a decent alternative for those looking to play around with the idea locally.
It’s unclear though from the landing page how this is different from Make. All of the examples are things that could be done using the OpenAI node in Make / Zapier / n8n.
All the examples we put out are pretty surface level and approachable because we don't want to alienate with something crazy complex or specific. The real value is in the fact that automations can get extremely complex and it's totally flexible. Our power users have at time 60+ nodes on a canvas with several automations nested in their builds layers deep.
Not sure how to convey that value without people seeing their hyper specific use case and wondering how it's at all relevant to them. If you had any thoughts on how to approach marketing that aspect we'd actually love external input.
And it seems that they are focussing on tasks :
https://www.theinformation.com/articles/openai-shifts-ai-bat...
We thought that was the best feature we'd ever put out but our core users mainly stuck to running automations the standard way.
We're two devs and built all of this for almost no money. We think if we can make something even remotely comparable alone then we can definitely compete in the future if we keep going. This is probably just me being extremely naive but I think we need to be a little bit to try. Very valid point though.
If I were in the market I would not even consider Power Automate, coming from MS.
I'll echo what others have said: I would expect OpenAI to be breathing down your neck, as this seems to overlap a lot with their plans for assistants.
The topic is so broad, though, that there may be a niche for you to carve out along the way regardless. Best of luck!
What are your thoughts on the WYSIWYG interface compared to having someone check in a configuration file for the workflow in their code?
Are the intended users of your product primarily non-developers?
The people who seem to most enjoy and use the platforms are those that really benefit from the non-technical interface. There are other approaches to this that might be more efficient but this was the flavor we landed on. Subject to change though based on user needs!
Having to drag everything is kind of annoying. I would like to have double clicked as an action to add automations to agents as well. The design is nice, but could use some work on smaller in between view ports.
https://www.agenthub.dev/templates/hr_hiring/linkedin_profil...
LLMS are not capable of unbiased scoring, no matter how much you prompt them. Anyone using this would be vulnerable to anti discrimination lawsuits as it is trivially provable that the workflow indeed is biased.
And frankly, this is disgusting tech bro behavior. LLMs are incapable of grading without bias.
https://www.agenthub.dev/templates/education/automated_gradi...
It’s a bit like https://github.com/omnitool-ai/onnitool (plus cloud hosted, minus the extensions) or https://nodered.org but focused on AI.
How do you handle prompt injection (e.g. in a linkedin profile) ?