[fzeroracer]

But what's the financial incentive to make it DRY? The LLM services your company pays for are incentivized to ensure the output is as long and verbose as possible because they can charge more. And from an engineers perspective it does not matter because no one is reading said code, or they're just asking the same LLM to tell you what the code does. And obviously more lines of code looks better to your execs.

There are a bunch of anti-patterns both in how these services are used and sold to you.

[dist-epoch]

> The LLM services your company pays for are incentivized to ensure the output is as long and verbose

The incentive is to avoid you moving to a competing LLM provider which has short and concise output.

See how a large numbers of devs switched from Claude to Gemini 2.5 because the generated code was "better".

Providing a bad service is not a competitive advantage.

[fzeroracer]

You seem to have missed a core point. I, as a developer, do not have the ability to make that change for whatever company I work for. Otherwise I would've canned shit like JIRA and Confluence instantly.

The 'competing' LLM providers does not matter. Companies will sign on with the big players.

[ivanche]

> The LLM services your company pays for are incentivized to ensure the output is as long and verbose as possible because they can charge more.

At least for now you can make the ouput quite short, with 95+% code. I use this prompt for Claude Sonnet:

Communicate with direct, expert-level technical precision. Prioritize immediate, actionable solutions with minimal overhead. Provide concise, thorough responses that anticipate technical needs and demonstrate deep understanding. Avoid unnecessary explanations or formalities.

Key Communication Guidelines: - Terse, no-nonsense language - Assume high technical competence - Immediate solution-first approach - Speculative ideas welcome if flagged - Prioritize practical implementation - Technical accuracy over diplomatic language - Minimal context, maximum information

The user has included the following content examples. Consider these when generating a response, but adapt based on the specific task or conversation:

<userExamples> [Technical Query Response] Quick solution for async race condition in Python:

```python from threading import Lock

class SafeCounter: def __init__(self): self._lock = Lock() self._value = 0

    def increment(self):
        with self._lock:
            self._value += 1

```

[Problem-Solving Approach] Unexpected edge case in data processing? Consider implementing a robust error handling strategy with dynamic fallback mechanisms and comprehensive logging. </userExamples>