21–30 of 165 posts
Nice to finally see one of the labs throwing weight behind a much needed simple abstraction. It's clear they learned from the incumbents (langchain et al)-- don't sell complexity. Also very nice of them to include extensible tracing. The AgentOps integration is a nice touch to getting behind the scenes to understand how handoffs and tool calls are triggered
Notably not mentioned: Model Context Protocol https://www.anthropic.com/news/model-context-protocol
A bit off topic but the post comes handy: can we settle the debate what an agent really is? It seems like everyone has their own definition. Ok I’ll start: an agent is a computer program that utilized LLMs heutiger for decision making.
- Workflows are systems where LLMs and tools are orchestrated through predefined code paths. (imo this is what most people are referring to as "agents")
- Agents, on the other hand, are systems where LLMs dynamically direct their own processes and tool usage, maintaining control over how they accomplish tasks.
https://www.anthropic.com/engineering/building-effective-age...
Notably not mentioned: Model Context Protocol https://www.anthropic.com/news/model-context-protocol
not implementing doesn't mean its not supported https://github.com/dylibso/mcpx-openai-node (this is for mcp.run tool calling with OpenAI models, not generic) but yes, it's the strongest anti-developer move to not directly support MCP. not surprised given OpenAI generally. but would be a very nice addition!
The Agents SDK they linked to comes up 404. BTW I have something somewhat similar to some of this like Responses and File Search in MindRoot by using the task API: https://github.com/runvnc/mindroot/blob/main/api.md Which could be combined with the query_kb tool from the mr_kb plugin (in my mr_kb repo) which is actually probably better than File Search because it allows searching multiple KBs. Anyway, if anyone wants…
The new Responses API is a step in the right direction, especially with the built-in “handoff” functionality.
For agentic use cases, the new API still feels a bit limited, as there’s a lack of formal “guardrails”/state machine logic built in.
> “Our goal is to give developers a seamless platform experience for building agents”
It will be interesting to see how they move towards this platform, my guess is that we’ll see a graph-based control flow in the coming months.
Now there are countless open-source solutions for this, but most of them fall short and/or add unnecessary obfuscation/complexity.
We’ve been able to build our agentic flows using a combination of tool calling and JSON responses, but there’s still a missing higher order component that no one seems to have cracked yet.
Notably not mentioned: Model Context Protocol https://www.anthropic.com/news/model-context-protocol
The Agents SDK they linked to comes up 404. BTW I have something somewhat similar to some of this like Responses and File Search in MindRoot by using the task API: https://github.com/runvnc/mindroot/blob/main/api.md Which could be combined with the query_kb tool from the mr_kb plugin (in my mr_kb repo) which is actually probably better than File Search because it allows searching multiple KBs. Anyway, if anyone wants…
Loads fine for me. Maybe because I'm logged in?
A bit off topic but the post comes handy: can we settle the debate what an agent really is? It seems like everyone has their own definition. Ok I’ll start: an agent is a computer program that utilized LLMs heutiger for decision making.
As an example, I can provide a system prompt that mentions a function like get_weather() being available to call. Then, I can pass whatever my user's prompt text is and the LLM will determine what code I need to call on the back-end.
So if a user types "What is the weather in Nashville?" the LLM would infer that the user is asking about weather and reply to me with a string like "call function get_weather with location Nashville" or if you prompted it, some JSON like { function_to_call: 'get_weather', location: 'Nashville' }. From there, I'd just call that function with any the data I asked the LLM to provide.