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OpenAI Agents API
111–120 of 202 posts
Re: OpenAI Agents API
#112[flagged]
Re: OpenAI Agents API
#113I think we’re still figuring out the right abstraction for offering agents as a product. - LLMs are a great foundation but building your own harness is a huge undertaking, a deep rabbit hole. - There are harnesses available as open source libraries but that’s still coupled to an environment. Where does the state persist? Like maybe I’m a Cloudflare worker and don’t even have a file system. Agent as a service like thi…
> you’d want to be using GLM 5.3 Flash right now for most things agentic That was yesterday. I think the crown currently belongs to DeepSeek Flash v4.1 for the next few days or weeks.
I can't wait for next week
Re: OpenAI Agents API
#114I think we’re still figuring out the right abstraction for offering agents as a product. - LLMs are a great foundation but building your own harness is a huge undertaking, a deep rabbit hole. - There are harnesses available as open source libraries but that’s still coupled to an environment. Where does the state persist? Like maybe I’m a Cloudflare worker and don’t even have a file system. Agent as a service like thi…
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Re: OpenAI Agents API
#115I think we’re still figuring out the right abstraction for offering agents as a product. - LLMs are a great foundation but building your own harness is a huge undertaking, a deep rabbit hole. - There are harnesses available as open source libraries but that’s still coupled to an environment. Where does the state persist? Like maybe I’m a Cloudflare worker and don’t even have a file system. Agent as a service like thi…
Libraries such as agent development kit (https://adk.dev/) provides abstraction over multiple LLM vendors, long-term memory (persistance + compaction) and allow us to manage subagents & their lifecycles. Vendor neutral memory & context management is a challenge as default long-term memory uses vertext AI (gemini) in ADK.
Re: OpenAI Agents API
#116[dead]
Re: OpenAI Agents API
#117Buried in there, note you can opt to self-host your sandbox https://developers.openai.com/api/docs/guides/agents-api/env... That makes this much more enticing, and potentially eases transition between providers.
Then why tf do i need their api
The self-hosted environment is just the backend for shell calls the agent wants to make. The inference bits, thread persistence, and (optionally) mcp/tool calls happen from the API.
Re: OpenAI Agents API
#118Earlier quoted context omitted.
> building your own harness is a huge undertaking, a deep rabbit hole. I eventually gave up on this task. It's not possible to fight OpenAI or Anthropic's engineering teams. Their reasoning models have all kinds of undocumented back door access to the base models that you'd never be able to replicate from the outside. Even if you had full access you would not have the engineering man hours or experience to keep up. I…
I built my harness in pi within herdr, I cloned (zipped and downloaded) 0xRichardH/pi-herdr-subagents and went from there, and used pi to build itself, adding gate workflow state control, provider fallbacks (I use many token plans), subagent skill injection, etc. It is highly custom to my needs and wants, and I think every developer needs to do this. I only talk to my planner which plans, and it subs out to designer,…
I'm very interested in this but I am confused on what Pi provides you if you are building the harness? What does Pi get you that writing from scratch doesn't?
Any good starting points or tutorials you recommend?
Re: OpenAI Agents API
#119I think we’re still figuring out the right abstraction for offering agents as a product. - LLMs are a great foundation but building your own harness is a huge undertaking, a deep rabbit hole. - There are harnesses available as open source libraries but that’s still coupled to an environment. Where does the state persist? Like maybe I’m a Cloudflare worker and don’t even have a file system. Agent as a service like thi…
IMO building a harness is not wildly difficult (customize pi?) but the offerings from openai and anthropic are wildly subsidized in the subscriptions so they win by default if you want frontier capabilities. Glm 5.3 flash is great but it's not cheaper than a codex or Claude code 200 dollar sub and it does not have astra or fable level capabilities.
Re: OpenAI Agents API
#120Earlier quoted context omitted.
I built my harness in pi within herdr, I cloned (zipped and downloaded) 0xRichardH/pi-herdr-subagents and went from there, and used pi to build itself, adding gate workflow state control, provider fallbacks (I use many token plans), subagent skill injection, etc. It is highly custom to my needs and wants, and I think every developer needs to do this. I only talk to my planner which plans, and it subs out to designer,…
I'm very interested in this but I am confused on what Pi provides you if you are building the harness? What does Pi get you that writing from scratch doesn't? Any good starting points or tutorials you recommend?
Pi is just a nice base and it has defined extension protocols and such. You might as well start there, it's just easier and going from nothing to working to adding whatever functionality is like 2 minutes.