Fuck AI

A very very large part of programming is boilerplate code you cant get past, it must be written.

A huge part is integration testing.

You have like hundreds or thousands of tests that are very repetitive. "Open this, click that, do this, type that, wait... assert this happens"

You have all these in a human readable format/doc provided to you by your requirements team

You uabe to convert all of that into code so a program can do the steps, such that it runs every day to confirm "website isnt broken boss!"

Converting all that human text into code is very easy but very monotonous

It can be tens of thousands of lines of code, easily.

This type of task is extremely easy for AI though, especially if you start it off with 10~15 examples to show it how it outta be done

Then you just give it the doc and go "okay draw the rest of the owl please"

This is called "nth shot prompting", where it has samples to start with and then it just copies your work 1000 times given input.

AI is extremely good at this.

It can turn weeks of work into hours.

The ability to turn human contextual English into code is one of its top skills, and turns out for a serious prod scale app at a company, thats like... 90% of software dev

And since we can work in parallel, I can focus more of my effort on that remaining actually challenging 10% where stuff matters more.

Its like swapping from pulling a wagon by hand of dirt to a job site, to instead pulling it with machine.

I get that part done 10x faster/easier, or better, and now I can actually put my time/energy into way more important shit than just hauling dirt around.

Summarized: when ppl talk about it making them do their job faster/better, its usually cuz it got rid of a bunch of boring parts and now they can focus on the actually important parts of their job more, and thus produce way higher quality results net.

What people need to wrap their heads around is almost all of these cases are/were companies that were gonna lay people off anyways.

They just used "cuz AI" as a PR spin to avoid making investors panic.

"We laid off 25% of our workers cuz we are failing" makes your stocks tank.

"We replaced 25% of our workforce with AI" makes stocks go up.

And they can just lie about it. They probably arent even fuckin using AI... or they are half assing it to make it look like they are using AI to investors.

The reality is, the company is just shitting the bed and upper management is doing everything they can to stop the stocks ftom ranking for just 6 more months so they can sell out first before the company goes bottom up.

Companies actually using AI intelligently arent "replacing" anyone with AI.

What tasks make economic sense to devolve to AI?

So, the main one I use it for, as its my job, is software development.

I offload about 90% to 95% of my workload to AI, almost all of which is "boilerplate" code that sits in the realm of "very easy to do, but very repetitive and time consuming" which is... most of it. Thats just the reality of software dev, especially web app dev. A lot of our stuff is just plumbing "this api endpoint calls this backend logic which just maps to this basic database operation"

IE, the POST endpoint to /users/{id} invokes the UpdateUserHandler which takes in an UpdateUserRequest which maps to an UPDATE [dbo].[Users] ... sql statement... not exactly super complicated stuff, but you do have to actually write the stuff that defines this.

This type of work is trivial for AI, but any given project has its own set of business rules, code rules, syntax rules, formatting rules, etc etc etc.

A naive approach is just yolo throw an AI agent at it, cross your fingers and pray that it randomly chooses to read the right stuff and happen to succeed at following your code quality and methodologies (it wont)

The naive agent also will demolish its way through tokens as it reads way more files than it has to, because every single time you do work its basically starting all over again from ground zero with no context of wtf its doing. This wastes.... so many tokens, because its gonna sit and read like 20 files just to figure out "what am I supposed to be doing here?" and this in turn pollutes its context window up so damn full it will start forgetting shit anyways.

This is where actual tools come into play that make this stop being an issue...

1. RAG Memory, instead of blindly searching your codebase, you can tokenize your codebase into a much easier to semantic search system, the agent can WAY faster do a simple search and get returned pointers to "Look over here", its like creating an index of your codebase itself so the agent has a useable optimized "map" of the project.

2. MCP Tools, which are basically tools that the agent can invoke to do.... anything. Normally by default the agent is just given willy nilly access to the terminal and it'll just fumble through trying to use that to do anything it needs to. This is a great way to fuck stuff up, especially if it also has access to shit it shouldnt (que "our agent accidently deleted our database" type shit). MCP tools allow you to build a curated set of stuff it can invoke, so instead of just doing random shit it has prefab commands to run. If you flesh out your MCP Tools well enough you can outright disable its access to the terminal entirely, because it doesnt even need it anymore. No more accidental database deletions, and it uses waaaay less tokens fumbling around in the terminal.

3. Skills, which are special files that allow it to "lazy load" guides on "how to do x/y/z", which you can break up into bite sized pieces. So instead of a giant AGENTS.md file that uses up half its context, even though the agent doesnt need 90% of whats in it for a given job, it can instead have a big list of "how to do this, how to do that" and it'll load a skill for a given task its working on ad hoc, only loading in the instruction relevant to the task at hand. These are huge and critical to further reduce token usage a lot

4. Token reduction skills (caveman being the most popular), theres certain skills people have made that outright change the way the agent behaves, namely the caveman skill. Make agent talk like this. Why more word when less word good. Less word, less tokens. Less tokens, less money. Also faster. Ungabunga. (Caveman mode can give you like 50% to 70% token reductions alone)

5. General prompting skills, know how to prompt agents genuinely makes a big fuckin difference. Baseline thing you learn asap is NEVER correct an agent, this does not work well. Instead you should be going back in the timeline and editing your prior prompt to preemptively correct the mistake before it even happens

Example, responding with "X is wrong" is bad. Instead, going backwards and editing your prior prompt with "And dont do X btw" is far better

This is just a handful of stuff, this is literally the basics, but hopefully gives you an idea of how deep the rabbit hole can go, I didnt even touch on stuff like agentic workflows and agent orchestration, which is where shit really starts to pop off...