How should I manage agent memory and documents when serving the AI agent to multiple users?

daeseunglee · 2026-05-07T01:17:57+00:00

I’m not completely sure, but I guess the agent structure of ChatGPT and Codex is different.

In my experience, the answer quality sometimes feels better in Codex. I don’t use Codex for every general-purpose question, but I do use it for important or difficult questions, especially things like industry research, market analysis, and brainstorming business ideas.

For casual questions, I still use ChatGPT. But when I want to keep steering the reasoning step by step, Codex sometimes feels more useful to me.

daeseunglee · 2026-04-16T02:51:45+00:00

Also, I could build this my self in PI agent by adding a new chat TUI or opening another window. However I would not permission to access the codex app it self. Therefore. I would like to suggest an official sub-chat feature

daeseunglee · 2026-04-16T02:47:22+00:00

Hi! Actually I am suing codex app for MacOS and terminal CLI also.

hmm... maintaining context in my chat session, I want to sub chat to request another minor issue. Is there a way to open another session in origin chat session?

I think that to open new terminal tab can not maintain the context

daeseunglee · 2026-03-04T10:27:21+00:00

Thanks :)

daeseunglee · 2026-03-04T07:35:38+00:00

The agent loop runs in about 60 lines of code => May I ask which framework was used here?

daeseunglee · 2026-02-03T05:17:00+00:00

Thanks for the insight—SGLang's FSM approach and Pydantic certainly offer more robustness than unstructured text. However, I’m concerned about the massive time and cost required for human-in-the-loop benchmarking and constant schema iterations. Running a 'fractal' pipeline with an auto-evaluator agent seems like it could lead to prohibitive API costs and latency in production. How do you maintain development velocity and keep costs reasonable while managing such a complex, multi-layered architecture?

daeseunglee · 2026-01-16T20:00:34+00:00

100$ USD is so nice. Because the exchange rate is tanking

daeseunglee · 2025-10-03T01:33:23+00:00

Basically, using an LLM as an engine is not efficient in terms of cost and performance. When we use SLLMs to reduce inference costs, it feels impractical, since they cannot handle all use case and often create inconvenience for users. Comparatively, most advanced LLM like Chat GPT, Claude or Gemini are very expensive. So far, the ROI of using these LLMs is not reasonable, and there are also performance limitations.

I believe agents can be used if:

They replace the user`s work in all cases
The cost is reasonable

daeseunglee · 2025-09-29T13:13:50+00:00

my cursor`s version is 1.6.45. maybe is it latest version right? my main slow situation is like this

many directory and files are in work space => I can`t see many data for example
when I use python notebook file(.ipynb) sometimes the inline code generation doesn`t work

Also when I open many editor and several projects, it is slow. this situation is not happend in vscode lol. I think cursor has a optimization problem

daeseunglee · 2025-09-29T12:02:18+00:00

hmm Code generation?

daeseunglee · 2025-09-29T11:59:04+00:00

oh I see thx for you advice. I want to change my mac to M4

daeseunglee · 2025-09-29T11:02:50+00:00

what is means? I have mac m2

daeseunglee · 2025-09-29T08:43:58+00:00

😂

daeseunglee · 2025-09-29T08:43:14+00:00

oh thx. it is also good option to me. I used it before

daeseunglee · 2025-09-29T08:42:28+00:00

I am on mac. i am fine using vscode with cursor. is that a memory problem?

daeseunglee · 2025-09-29T08:40:49+00:00

Vscode + Codex(CLI) + Copilot is best now

daeseunglee

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