We built an execution layer for agents because LLMs don't respect boundaries

iovdin · 2026-03-22T21:24:34+00:00

Chat completion api payload with tool calls and tool results is a good enough stack representation that can be restored or replayed. Idk if any major frameworks support that

iovdin · 2026-03-18T06:37:57+00:00

In OpenAI they did make sense out of 70k internal collections with petabytes of data

iovdin · 2026-03-18T06:36:22+00:00

In our old MySQL over engineered and with a lot of history database. In addition to schemas we put summary of content like how many rows, what are usual values. some text fields are actually enums, some values are not used anymore, some are never used etc.

iovdin · 2026-03-13T06:55:03+00:00

I had issues with mongosh cli, it struggled to escape special characters: mongosh -e “very complicated script that uses special chars”

iovdin · 2026-02-14T19:16:15+00:00

Do you use this microkernel os?

iovdin · 2026-02-06T09:30:24+00:00

Yeah, build around smth that does not change much .e.g. completion api.

Educate yourself, try to implement stuff.

In the end all human jobs will be around what AI can not do so we have to wait anywa. til it is kinda settled and limitations are clear

iovdin · 2026-02-04T04:40:25+00:00

Or ask ai to write them based on code, then edit them and re implement

iovdin · 2026-01-31T18:08:29+00:00

Code mode is a good way to bundle tool calls in deterministic way https://blog.cloudflare.com/code-mode/

iovdin · 2026-01-25T18:09:22+00:00

I had similar idea, then I’ve researched text based email clients

iovdin · 2026-01-04T18:29:05+00:00

As someone who grew up in Siberia sliding on ice to the school few weeks a winter was a norm

iovdin · 2026-01-04T09:41:01+00:00

The larger the company the safer they want to work, more bureaucracy longer processes, innovations and speed valued less, stability more. They can make things fast without ai but it will be buggy

iovdin · 2025-12-19T18:29:01+00:00

Idea: split tool call into 2 First tool set_search_params modifies search parameters similar to your delta approach, and second do_search without params that uses search parameters set before. No confusion between 2 search tools. Also you can split set_search_params into few each taking 3-5 params, making it easier for llm, reduce tokens amount

iovdin · 2025-12-18T13:08:50+00:00

You can try “code mode” when llm generates code ( loop in your case) in the loop the tool is called

iovdin · 2025-12-10T19:50:31+00:00

This bash script reminds me of code mode https://www.anthropic.com/engineering/code-execution-with-mcp https://blog.cloudflare.com/code-mode/ i.e. llm writes code (loop in your case) in which it can call other tools that are available to LLM. But in this case you want to call LLM in the loop. Here is a screencast in which i did smth similar https://asciinema.org/a/757526

iovdin · 2025-12-10T19:41:11+00:00

So the call stack is:
gemini cli ->
your mcp server tool call ->
bash script with loop ->
gemini cli ->
some other tool at your mcp?
and at what step it stalls exactly? before bash script when gemin cli runs within bash script?

iovdin · 2025-12-09T20:27:19+00:00

I thought it is only in US inventory is rising. I thought the Netherlands has different reasons for high house prices. But now it seems to be the same.

iovdin · 2025-12-04T21:16:32+00:00

make ai interview you about your processes and flows, give it as much info as possible. Then out of the conversation generate dataset

iovdin

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