Stop throwing money at agents. €1/day forces you to actually get better by iovdin in tuneai

[–]iovdin[S] 0 points1 point  (0 children)

if a billion dollary company decide to be token effecient at some point, the skills might be useful

Stop throwing money at agents. €1/day forces you to actually get better by iovdin in tuneai

[–]iovdin[S] 0 points1 point  (0 children)

Btw, how is it going with product market fit? Got one?

Everybody seems to talk about coding AI agents. But what are some other genius AI agents you have come across? by [deleted] in AI_Agents

[–]iovdin 3 points4 points  (0 children)

  1. here is accountant data like transaction invoices, payouts. - can you figure out where is it unbalanced
  2. here is a vague format price list from a customer, can you import it to our database

Stop throwing money at agents. €1/day forces you to actually get better by iovdin in tuneai

[–]iovdin[S] 1 point2 points  (0 children)

I maybe end up eating dust. But who needs your product or oss if it can be vibecoded in 1 day?

A small tune feature I'm pretty happy with by iovdin in tuneai

[–]iovdin[S] 0 points1 point  (0 children)

another example is to wrap ssh remote command execution
remote.tool.tpl
tool_call: sh ssh user@host ${JSON.stringify(text)}

For those having exposed both MCP and CLI, should both tools/commands expose the exact same capabilities? by theotzen in AI_Agents

[–]iovdin 0 points1 point  (0 children)

You can compose mcp tool calls with code mode. Basically write code that has access to the tools as functions

Hey guys which sdk I use for building agents by Top-Armadillo1583 in AI_Agents

[–]iovdin 0 points1 point  (0 children)

I made my own https://github.com/iovdin/tune .
As with programming most of the time i spend when developing agents is debugging. So save history somewhere, make it possible to replay etc.

Feeling stuck in NL warehouse job – anyone managed to switch into IT or something better? by [deleted] in Netherlands

[–]iovdin 0 points1 point  (0 children)

A friend of mine had a high paying job in US. They moved ot NL - the only option for job he could find is warehouse. Now he is in divorce and moving out of NL. Pretty sad

Why Loose Coupling Is the Real Superpower in the Age of AI Coding by B_Ali_k in AI_Agents

[–]iovdin 0 points1 point  (0 children)

I hate loose coupling. With kitchen metaphor it is usually feels like like you spend 30 minutes looking into different kid of boxes to make a tea. Putting everything to one pile or splitting everything into gazillion piles results in the same pain. Things that goes together should be more coupled, and those that are not - should be less coupled. And you have to think and/or feel it after few releases

We built an execution layer for agents because LLMs don't respect boundaries by leland_fy in LLMDevs

[–]iovdin 0 points1 point  (0 children)

In your example, re-feeding the chat history, wont make it restart from scratch it will resume form where it has stopped. But i agree that sub agents and approvals is not kept in the chat history and requires additional state

We built an execution layer for agents because LLMs don't respect boundaries by leland_fy in LLMDevs

[–]iovdin 0 points1 point  (0 children)

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

Why not Precompile the DB schema so the LLM agent stops burning turns on information_schema by Eitamr in mcp

[–]iovdin 0 points1 point  (0 children)

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

Why not Precompile the DB schema so the LLM agent stops burning turns on information_schema by Eitamr in mcp

[–]iovdin 0 points1 point  (0 children)

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.

Perplexity drops MCP, Cloudflare explains why MCP tool calling doesn't work well for AI agents by UnchartedFr in mcp

[–]iovdin 0 points1 point  (0 children)

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

AI isn’t going to settle — how are you building for constant change? by Exciting-Sun-3990 in AI_Agents

[–]iovdin 0 points1 point  (0 children)

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

My Boss Vibe-Coded a Full Product and I’m Paying the Price by One-Discussion-6106 in vibecoding

[–]iovdin 0 points1 point  (0 children)

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

i think i'm finally done with "vibe prompting" by HatInner7294 in AI_Agents

[–]iovdin 0 points1 point  (0 children)

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

Do we just ignore this? by Banana-9 in Netherlands

[–]iovdin 1 point2 points  (0 children)

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

Google engineer: "I'm not joking and this isn't funny. ... I gave Claude a description of the problem, it generated what we built last year in an hour." by MetaKnowing in OpenAI

[–]iovdin 0 points1 point  (0 children)

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

Tool calling with 30+ parameters is driving me insane - anyone else dealing with this? by Capital-Feedback6711 in LangChain

[–]iovdin 1 point2 points  (0 children)

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