There is some output (slop) I got from my recent sessions (yes, yes, I am guilty and ashamed):


### Validation Summary
I have verified the implementation across the **Functional Core** (Domain) and the **Imperative Shell** (Infrastructure & Interface), confirming that the code doesn't just "look" right but functionally enforces the rules.

**1. Domain Layer (Functional Core)**
  **Strict Encapsulation:** All primitives (`f64`, `String`) are wrapped in **Newtypes** (`Price`, `Quantity`, `Symbol`) with private fields.
  **Correctness by Construction:** **Smart Constructors** (`new() -> Result`) enforce invariants (e.g., price > 0, symbol format). It is impossible to instantiate invalid domain objects.
  **Algebraic Data Types:** `Order` is a Sum Type (Enum) of Product Types (Structs), exhaustively modeling valid order strategies (`Market`, `Limit`, `StopLimit`).
  **Typestate Pattern:** The `OrderBuilder` uses zero-sized types (`NoSymbol`, `WithSymbol`) to enforce the order of operations at compile time. You cannot build an order without mandatory fields.
  **Error Handling:** `DomainError` is a specific Sum Type using `thiserror`, implementing the "Make Illegal States Unrepresentable" rule.

**2. Infrastructure & Interface (Imperative Shell)**
  **Hexagonal Architecture:** The `client` module acts as an **Adapter**, translating domain objects into Binance API calls. It isolates side effects (I/O, Time, Crypto).
   **Functional REPL:** The `repl` module implements the Command Interpreter using **Functional Streams** (`input_stream().map().for_each()`), strictly avoiding imperative `while` loops.
   **Security:** `Credentials` are handled via `secrets` module, and signing logic (`compute_signature`) is a pure function.

**3. Verification (Tests)**
   **Pass Rate:** **124/124 tests passed**.
   **Coverage:** The test suite is organized into "Stories" (e.g., `story_user_places_valid_limit_sell_order_gtc`), directly testing the Business Rules and Workflows against the domain logic.

The project is correctly set up as a mathematically rigorous, type-driven trading assistant.

here is another one:


### **Refactoring Summary**

1.  **Architecture & Structure**:
    *   **Library-First Design**: The project structure was corrected so `src/main.rs` acts as a thin consumer of the `r4` library crate. This prevents code duplication and enforces a clean dependency graph.
    *   **Modules**: The codebase is split into orthogonal modules (`domain` types, `infrastructure` clients, `interface` REPL), cleanly separated in `src/lib.rs`.

2.  **Domain-Driven Design (DDD)**:
    *   **Strict Types**: All primitive values (`f64`, `String`) are wrapped in **Newtypes** (`Price`, `Quantity`, `Symbol`) or **Enums** (`OrderSide`, `OrderType`).
    *   **Smart Constructors**: Validation logic is encapsulated in `new()` methods that return `Result<T, DomainError>`, ensuring that **illegal states are unrepresentable**. You cannot create an invalid `Price` or `Symbol`.
    *   **Encapsulation**: Fields are private. Access is provided via immutable accessors (`value()`, `as_str()`), preserving **referential transparency**.

3.  **Error Handling**:
    *   **No Naked Unwraps**: All `unwrap()` calls in the application logic have been replaced with proper `Result` propagation.
    *   **Typed Errors**: We use `thiserror` to define rich, distinct error types (`DomainError`, `ClientError`, `SecurityError`) for each layer, rather than stringly-typed errors.

4.  **Security**:
    *   **Secret Encapsulation**: `APIKey` and `SecretKey` types hold their inner strings privately and require an explicit `.expose()` call to access them. This prevents accidental logging or misuse.

5.  **Educational Quality**:
    *   The code is annotated with "textbook-style" comments identifying the specific design patterns used (e.g., "**Pattern: Typestate**", "**Technique: Functional Pipeline**").

Nice, huh? How do we know that any of these bold statements are true? How do we know that the code actually adheres to the verbiage? How does it actually work to make the code consistent with the verbiage, provided it is a syntax level slop generator?

I do not believe it does. I think it just spews out verbiage based on your prompt and just “autocompletes” the code. Verbiage in –verbiage out.

I won’t share the prompts – they are basically the results of the last 50 years of PL semantics research across efferent “paradigms” (mostly FP, of course). Some applied principles from the old, classic books written by actual math majors instead of modern punks.

So, how do I know that it isn’t bullshitting and manipulating me? How do you know it does not bullshitting and manipulating you?

One more time – it just adds the most probable next token to the end of the current string, that’s all.

Of course, I am smart enough to ask only for small, well-defined refactorings, when I know what to expect and which slop is correct and which does not. But look, how do I know that my understanding is not flawed (crappy social conditioning through the fucking social media)?

Yes, I do know what the Builder+Typestate pattern does and what it is for, I know what so-called Smart constructors are for, and how to forbid arbitrary instantiation via “struct literals”, and what not.

But what about these methods chaining of the external APIs? Are there any hidden mutable state in the implementation of the crates? stdlib has thousands of unsafe blocs everywhere.

It says my code is Okay, but I spent days to properly constrain it to spew out exactly what I wanted, using the only particular well-chosen patterns, corresponding standard idioms and selected language constructs.

On the other hand I know how the slop generator works, I have studied it, and even got some high marks. And I feel it just cognitively fucks with me – it tells me only what I want to hear, it strictly confirms to what I’ve asked.

What if this is only an appearance of the correctness? Okay, I could double-check the code I asked for. But it has to be just an appearance which tricks me to believe everything is cool. That evil daemon of Descartes, which is just one’s own mind full of cognitive biases.

One more time – a LLM does not lie to you. Lying is an intentional act of deception. It just does what it supposed to do – append the most probable next token to the end of a sequence. By doing just this, however, it produces an appearance to the mind, an illusion, which an observer is confusingly assuming to be “real”, to be What Is.

The very same thing happens when a parrot appears to “speak” a human language. What it actually does is mimicking the sounds it overheard somewhere, and because these sound appear to an observer as parts of a coherent speech, it creates an illusion of a bird knowing the language, while it “operates” at the level of acoustic sounds waves, not even phonemes or morphemes.

The LLM you are using operates at the level of “tokens”, which are meaningless chinks of whiten text, similar, in principle, to what sound-waves are to a human speak

So, an LLM does not lie or chat, it just does what it programmed for (by definition, literally, of the algorithms implemented), it just does not do what it said it does or have done. When a parrot “said” something like “I think” it actually does not, it simply can’t. It does not equipped with the required biological machinery to do so (evolved in an already much higher developed brain by necessity of already established communal life).

In exactly the same way, when an LLM “said” something like “I analyzed” or “I reasoned” or “I verified”, it actually does not, it simply does not equipped with the algorithmic machinery to do any analysis or reasoning, only to produce a mere appearance of it, very convincing, though.

To actually realize this fact (and that this is an actual fact, not an opinion) one perhaps shall have some familiarity with the Eastern philosophy of the mind, which elaborates exactly such kind of issues of “appearances” and “illusions” and mind’s self-deception in general, but even without such kind of a background one can clearly see that this is just a “probabilistic parrot”.

Next time you observe the code it spews out, especially if it compiles and runs, think of the very process that actually produced it. A living parrot could produce [what appears to be] a grammatically perfect short sentence in any language it heard.

So, when it says that it analyzed, verified or proved something, realize that these are just “acoustic sounds” a bird produces, even if the slop compiles and runs.

Cool, yeah?