I mean, a lot? I have multiple times felt like that was my entire life for weeks or months on end during the past over three decades of doing software development...
(If we expand the scope a bit to network protocols, as opposed to just "APIs", I was even the person who first spiked nmap's protocol scanning and detection logic.)
To wit, I am one of those people who pretty much never use an SDK provided for an API: if I have to, I will rather reverse engineer the protocol using a disassembler.
(This then being part of why I've won millions of dollars in bug bounties, as part of my relentless drive to always operate at the lowest level presented to me.)
But, regardless, can we move past trying to attack my credibility on software, and shift back to more productive forms of analysis? (Why did this become so personal?!)
> What happens when the docs are wrong or incomplete?
If we posit that the documentation for the API is wrong, so we should this MCP description / wrapper, as both were written by the humans charged to enable this function.
And, of course, the real point is whether the task is easier than the thing we are trying to do... even writing a correct tree map is much harder than an API client.
^ Both of these arguments can be made by someone who doesn't even do software development, helping us try to understand why MCP is being hyped up as a new paradigm.
I’m not hyping or defending MCP at all: I’m just saying AI can’t figure out APIs well enough to be something you can promise as a product.
I founded an integration platform so definitely a developer and I’ve been living these problems every day.
Also > ...if an LLM is failing to do this task...
It CURRENTLY fails to do so, PREDITABLY and securely. What are you gonna do about that? Keep throwing more data into it and hope to start building stuff on top, one day?
Yes and it's working? People ARE CURRENTLY building things.
They are NOT currently whinning that LLM is not smart enough so they must sit and wait for the next model to be able to code any problem, (again RELIABLY) on demand.
> People are trying to get these things to do complex multi-step reasoning tasks, including making changes to their codebase (?!), automating behaviors as "agents" that need to predictably and secure function...
You understand that all these are powered by tools calling underneath? The planning and orchestration of tasks follows a structure, to be fed into tools. This is why a plain model cannot do shit, people have to make products with the right tools on top to make a llm behave the way they want, and not just chit chat endlessly.
The abitrary execution approach, if it ever works, is by building tools and MCP servers for code execution. Because obviously it's not the LLM server who executes code.
You clearly have never thought about how to actually build any of these things.
> ...writing API boilerplate
Tool/function calling can be anything, it's you who decided that you can only use it for API boilerplate. Does the word "function" always mean boilerplate in progranming?
