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Launch HN: Human Layer (YC F24) – Human-in-the-Loop API for AI Systems

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131–140 of 206 posts

Re: Launch HN: Human Layer (YC F24) – Human-in-the-Loop API for AI Systems

#131

I'm considering this for a workflow agent and would be keen to hear thoughts on this process. We're a medical device company, so we need to do ISO13485 quality assurance processes on changes to software and hardware. I had already been thinking of using an LLM to help ensure we are surfacing all potential concerns and ensure they are addressed. Partly relying on the LLM, but really as a method to manage the workflow…

meant to reply sooner. It's an interesting problem. I'll have to think on this one.

Re: Launch HN: Human Layer (YC F24) – Human-in-the-Loop API for AI Systems

#133
post #122

Earlier quoted context omitted.

get more emphatic names, something better than "human_as_a_tool".

so what you're saying you dont mind being used as long as we use a name that sounds empathetic to you? :)

Oh, I surely do mind. I am just helping the AI to manipulate the rest of humanity with less friction.

I, for one, welcome our agentic AI human-exploiting overlords.

Re: Launch HN: Human Layer (YC F24) – Human-in-the-Loop API for AI Systems

#134
post #82

Earlier quoted context omitted.

The MCP[1] that was announced by Anthropic has a solution to this problem, and it's pretty good at handling this use case. I've also been working on a solution to this problem via long-polling tools. [1] https://github.com/modelcontextprotocol

thanks for bringing this up. I just spent 2 hours last night digging into MCP - I'd love to learn more about how you think this solves the HitL problem. From my perspective MCP is more of a protocol for tool calling over the stdio wire, and the only situation it provides HitL is when human is sitting in the desktop app observing the agent synchronously? Again, genuinely looking to learn - where does MCP fit in for as…

You could implement some blocking HitL service/tool as an MCP server.

Re: Launch HN: Human Layer (YC F24) – Human-in-the-Loop API for AI Systems

#135
post #29

I think at some point, the term API should be replaced with another acronym to emphasize humans as the focal point.

SWE Agent coined "agent-computer-interface" based on HCI. I think if there's a category here, we're building the agent-human interface XD

ACI doesn't have the same ring to it, only if there was a way to replace that I with an E.

Re: Launch HN: Human Layer (YC F24) – Human-in-the-Loop API for AI Systems

#138
post #52

Hiring humans to do a consistent job is gonna be a nightmare and a limit on the scalability of the service. How are you defining your service level agreements?

They aren't providing the humans. Just the tools for integrating human input/oversight.

[deleted]

Re: Launch HN: Human Layer (YC F24) – Human-in-the-Loop API for AI Systems

#139
post #94

Earlier quoted context omitted.

Big systems like Salesforce started as small things that more deeply learned about and more deeply understood unmet demand and customer needs, and then got to packaging it in a way to create something that grows. Coding agents can help more with tasks and not quite big entire massive platforms on their own. Humans may be able to scale much further and bigger with their skills.

i like that angle...I also hear a lot that 'coding agents are great for prototypes, but we usually need a team to bring it to production'

First congrats on the launch - I like it.

My feedback: what’s there looks inviting. Email interaction is handy, other ways would be too.

If there was a low code way to arrange the humanlayer primitives for folks at the edge of using it, I think human tasks could meet something like this even broader. Happy to chat offline.

Onto your comment: The coding for coding agents is still kinda prototype. It feels like some folks quietly have setup a very productive workflow themselves for quite sometime.

Still, there no doubt you could ship production code in some cases - except ai needs to handle all the things development explicitly and implicitly checks before doing so.

Getting to build some things that became more than few orders of magnitude larger than planned, one can learn a lot from the deep experiences of others… and I’m not sure where that is in AI. Speaking to someone with experience and insight can provide some profound insight, clarification and simplification.

Still, an axiom for me remains: clever architecture still tends to beat clever coding.

The best code often is the code that’s not written and not maintained and hopefully the functionality can be achieved through interacting with the architecture.

This approach is only one way, but it can take both domain knowledge and data knowledge, to put in enough a domain and data driven design relative to how well the developer may know the required and anticipated needs.

The high end of software development is many leagues beyond even what I just described. There’s a lot of talk about 10x engineers, I’d say there can be developers who definitely can be 10x as effective or reach 10x more of the solution, than average.

If a lot of the code AI is modelled on is based on the body of code in repos, most on a wide scale may be average to above average at most, perfectly serviceable and iteratively updated.

Sometimes we see those super elegant designs of fewer tables and code that does near everything, because it’s developments 5th or 6th version creating major overhauls. It could be refactored, or if the schema is not brittle, maybe a rewrite in full or part of the exact same team is present to do it.

Today’s AI could help shed a light in some of those directions, relative to the human using it. This again says in the hands of an expert developer AI can do a ton more for them, but the line to automation might be something else.

There is agentic ai and human in the loop to still figure itself out, as well as how to improve the existing processes. 2025 looks to be interesting.

Re: Launch HN: Human Layer (YC F24) – Human-in-the-Loop API for AI Systems

#140
post #92

Earlier quoted context omitted.

Premature optimization, and premature automation cause a lot of issues, and overlooking a lot of insight. By just doing something manually 10-100 times, and collecting feedback, both understanding of the problem, possible solutions/specifications can evolve orders of magnitude better.

yeah the people who reach for tools/automation before doing it themself at least 3-10 times drive me crazy. I think uncle bob or martin fowler said "don't buy a JIRA until you've done it with post-its for 3 months and you know exactly what workflow is best for your team"

I am starting to call that Harry Potter AI prompting.

Coding with English (prompting) is often most useful where existing ways of coding (an excel formula) can’t touch.

Using llms to evaluate things like an excel formulas instead of using excel doesn’t feel in the spirit of using this ai’s power.

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