Keeping my GitHub repo private while publicly distributing my software – what's the best license?
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A year ago, most people I knew were mainly prompting Claude or ChatGPT and writing the orchestration around the responses.
Now there are agent frameworks everywhere - Google ADK, OpenAI Agents SDK, LangGraph, and more.
Has your workflow changed because of these frameworks, or do you still mostly prompt Claude/ChatGPT and build the rest with custom code?
I'd love to hear what people are actually using in practice.
A year ago, most people I knew were mainly prompting Claude or ChatGPT and writing the orchestration around the responses.
Now there are agent frameworks everywhere - Google ADK, OpenAI Agents SDK, LangGraph, and more.
Has your workflow changed because of these frameworks, or do you still mostly prompt Claude/ChatGPT and build the rest with custom code?
I'd love to hear what people are actually using in practice.
A year ago, most people I knew were mainly prompting Claude or ChatGPT and writing the orchestration around the responses.
Now there are agent frameworks everywhere - Google ADK, OpenAI Agents SDK, LangGraph, and more.
Has your workflow changed because of these frameworks, or do you still mostly prompt Claude/ChatGPT and build the rest with custom code?
I'd love to hear what people are actually using in practice.
Hey everyone,
I'm curious - what are the biggest problems you face while building AI agents (whether hand-coded or vibe coded)?
Could be anything: prompting, tool calling, memory, context management, debugging, deployment, latency, integrations, evaluation, or something else entirely.
Would love to hear what's been the most frustrating part for you.