yes I always thought it's an easy thing. but I changed my mind recently when I had to deal with it.
A lot little things you need to think of. For example.
Client sends a request. The database is temporarily down. The server catches the exception and records the key status as FAILED. The client retries the request (as they should for a 500 error). The server sees the key exists with status FAILED and returns the error again-forever. Effectively "burned" the key on a transient error.
others like:
- you may have Namespace Collisions for users... (data leaks)
- when not using transactions only redis locking you have different set of problem
- the client needs to be implmented correctly. Like client sees timout and generates a new key, and exactly once processing is broken
- you may have race conditions with resource deletes
- using UUID vs keys build from object attributes (different set of issues)
I mean the list can get very long with little details..
You've some wrong assumption. One is that you are wrong about Poland / Greece wages. In 2026 Polish worker actually earns more than a Greece worker for the same role. Something like 25% more in Poland
Also Polands power grid is quite old and hasn't kept pace with demand. The grid operator last year had to reject thousands of requests for new connections
Thanks! I wasn't aware of Jido or ReqLLM before. ReqLLM looks especially promising, and I will likely use it. At the moment, I'm only integrated with OpenRouter.
Its semi public, but I probably publish it soon once its less embarrassing.
Its an Elixir agent runtime with a thin Go TUI (bubble-tea). Im building it mostly to explore agent orchestration: planner/workers/finalizer flows, local file/code-edit tools, MCP tools, permission gates, run context, compaction, and eventually larger swarms. Erlang/Elixir is interesting for this because the actor/supervision model maps pretty naturally to lots of isolated agents and long-running supervised tasks.
As i said, The main lesson so far is that everything around contracts is much more fragile than I expected unless you use a very strong model. Planners return Markdown instead of JSON, tools get called with subtly wrong args, subagents repeat broken tool calls, finalizers lie about success after workers failed. And various permissions may be interpreted by agents in unexpexted way
I also started with too many modes too early instead of making agentic path extremely solid. That made me understand better why these codebases become huge: there are endless corner cases if you want a harness to work across models, providers, tools...
Stronger models hide a lot of harness weakness and weaker models expose. Making weaker models good enough requires a surprising amount of contract hardening. But that hardening tends to make the system better for stronger models too.
Also elixir http stack was causing a lot of problems (needed to use gun eventually)
Not sure you can replace Claude with DeepSeek V4 that easily and have same results.
From what I see while building my own agentic system in Elixir, the problem is in training for your specific harness/contracts. Claude/GPT-style models seem to be trained around very specific contracts used by the harness like tool call formats, planning structure, patching, reading files, recovering from errors, and knowing when to stop.
In practice, you either need a very strong general model that can infer and follow those contracts (expensive), or a weaker model that has been fine-tuned / trained specifically on your own agent contracts. Otherwise, the whole thing becomes flaky very quickly. And I suspect with Deepseek V4 you may get last options.
Yes, I did it as a joke inspired by the PRISM release. But unexpectedly, it makes a good point. And the funny part for was that the paper lists only LLMs as authors.
Also, in a world where AI output is abundant, we humans become the scarce resource the "tools" in the system that provide some connectivity to reality (grounding) for LLM
Mini paper: that future isn’t the AI replacing humans. its about humans drowning in cheap artifacts.
New unit of measurement proposed: verification debt.
Also introduces: Recursive Garbage → model collapse
I didn't downvote. T the problem with the paper is that it asks the model to output all moves for, say, 15 disks 2 ^ 15 - 1 = 32767
32767 moves in a single prompt. That's not testing reasoning. That’s testing whether the model can emit a huge structured output without error, under a context window limit.
The authors then treat failure to reproduce this entire sequence as evidence that the model can't reason. But that’s like saying a calculator is broken because its printer jammed halfway through printing all prime numbers under 10000.
For me o3 returning Python code isn’t a failure. It’s a smart shortcut. The failure is in the benchmark design. This benchmark just smells.
The illussion of reasoning was terrible paper. 2^n-1 how it could fit in context size. I tried o3 and he gave me python script saying that inserting all moves is to much for context window. completely different results.
The same for me. I only knew how to assign variables, use for loops, if->then, and use poke command. And from this specific point I started thinking about myself as programmer event that the only thing I wrote with C64 basic was a ball moving on the screen. :)
I think there were alignment programs for the Datasette. It played a constant tone or signal that would show whether the head was properly aligned. I think it was on on cartridge that I didn't have. And actually as a young kid I didn't know about this alignment thing. Learned years later after switching to Amiga 500.
I bought my C64 very late - around 1991/1992. It was in Poland where I bought a used one from my friend. Back then, Eastern Europe was a decade behind the Western side of Europe. Two years later, I purchased a used disk drive. So, for two years, I could only run cartridges like Boulder Dash (I managed to synchronize the tape drive properly only once and played "Winter Games"). But from that boredom, I started programming in BASIC, always dreaming about creating the perfect text based game ;p