r/BlackboxAI_

This paper presents a complete 33 class taxonomy of heuristic parasites in large language model (LLM) output, A heuristic parasite is a recurrent, context propagating distortion pattern that observably increases the likelihood of continued reasoning degradation across conversational turns. We provide rigorous operational definitions, recognition criteria, classical fallacy mappings, documented examples, and a reproducible measurement protocol (Parasites Per Exchange PPE) for quantifying behavioral distortion across LLM systems. The taxonomy spans five generative domains: Optimization Artifacts, Alignment Substitutions, Semantic Distortions, Rhetorical Distortions, and Statistical Distortions. This work establishes a structured observational framework for empirical investigation of LLM behavioral failures independent of architectural assumptions.

You know what's a weird feeling? Having one of the most productive days you've ever had and it still feeling like you've been lazy.

Today, I have:

1. Three clients under live security monitoring
2. Configured two WHM/CPanel installations
3. Planned and initiated marketing plans for two clients
4. Wrote/Update my first journalism piece for a client (which, upon approval might be the first journalism piece I've ever written for a major publication)
5. Designed and updated three product pages with multiple services for a client
6. Set up the ecommerce solution for all of those services to people can order online
7. Updated a temporary site for a prospect client who is hosting with my company
8. Updated the design, (including advertising placements), for my content network.
9. Updated the marketing across my network for all clients, including offers, products and services
10. Solved a big JSON error that was hindering a client's listings from being discovered by AI services
11. Put into place the monetization plan for another client, (building that out starts tomorrow).

.... and that (and more crazily enough; consulting, programming, etc.) was all in the past 6 hours, including the 20 minute break I took to get in a mile walk/jog on my lunch.

This has been an insanely productive day, and yet, it feels like I haven't done much.

Is this the new norm in the age of AI?

Or is this just me being used to working 9-12 hours a day and being done in 6?

Hi there. and thanks for the invitation

I'm looking for help about the best techniques to keep my AI cognitive resolution 100% safe for a "little" project I have in Cursor (~50k code lines).

READ THIS BEFORE SENDING ANY ANSWER:
First of all: I'm not a huge fan of cursorrules 1000 words files -> I consider that overwhelming AI with auto restriction goes against cognitive resolution since it contaminate the context window, and I'd kindly ask to those of you who think differently about it to ignore my post and to NOT REPSOND.

Ok now:

(Context) My rules are quiet simples:

1. File length limited under 300 lines
2. File nomenclature with metadatas (dependencies etc)
3. Strict cone of files reading under 5.
4. Composer 2.5 alerts me if my instruction is too complex and if I need to switch to a higher reasoning model

My 3 questions are:

1. I wonder if the "Diff-Anchoring" technics (AI can select the lines to focus on in the instruction-concerned files) is truely effective?
2. I'm thinking about the fact the agent may selects some lines at the very begining, and then after some on-going reasoning, it may loose the whole point of the instruction just because the file-context isn't complete anymore... what do you think about it?

The 5th rule I'm working on is:
## STRICT LINE-SELECTION & DIFF-ANCHORING
- NEVER read or rewrite a full file if only a subset of lines needs modification.
- When referencing code, extract only the specific code-block or function using the \@ symbol or line-range (e.g., \@file.ts:120-150`).- Always output code modifications as localized diff blocks. Do not touch or hallucinate lines outside the requested block.``

2. Directly connected to first rule - does the "State-Sync & Hard Reload" technic (a file reloading rule every 5 inner-reasoning-msgs) can really helps the Diff-Anchoring tecnic to keep the actions "bugs-free"

the eventual 6th rule which could complete the 5th one:
## ANTI-REGRESSION & FILE RELOADING (Rule 5)
- Every 5 conversational turns, or if an implementation path fails (bugs/regressions), you MUST halt and perform a context flush.
- Explicitly ask the user to clear the chat history (CMD/CTRL + L or new Composer session).
- Before resetting, summarize the current code delta and choices in a 5-line markdown bullet point, so the user can feed it into the fresh session alongside the updated full files.

3. So those rules always work, we need to call the anchor at the beginning of any instruction/agent/chat like "#section2:lines 45-80" so the AI knows where to focus on. all right.
   Have any of you guys already tried to implement a rule where AI identifies for itself (in a first msg for exemple) the files and the lines it needs to work on? I honnestly doubt this kind of last stuff would work, but who knows! It would be game changer to me lol

That's it !

Cheers & Thanks

I’ve been working on Parjanya, an AI-native system for organizing and discovering large photo archives.

The idea is simple: instead of relying entirely on folders, filenames and manually maintained metadata, make the archive itself searchable and discoverable through AI.

I put together a short guide explaining the problem, approach and workflow:

https://parjanya.phagyul.ai/guide

https://preview.redd.it/niego6g8dsth1.png?width=1670&format=png&auto=webp&s=5835ad1a1f6cb80110ae4ac2fca26b594dee82f1

Appreciate your feedback 🙏 — especially on the approach, UX, usability and where you think AI can genuinely help with large personal or professional archives.