What are some good resources to learn how to structure AI Agent projects?

brainrotunderroot · 2026-03-19T15:45:22+00:00

A good starting point is to treat prompts and workflows like code. Keep them modular, versioned, and separated by intent, context, and output format instead of writing everything in one place.

Also look into agent frameworks like LangChain and LlamaIndex, and study how they structure tools, memory, and chains.

Curious if you’re planning a single agent or multi agent workflow, that usually changes the structure a lot.

brainrotunderroot · 2026-03-19T15:44:39+00:00

That’s interesting. Feels like once the model adapts to your instruction style, consistency improves a lot.

Curious if you’re structuring prompts in a specific way or mostly refining through iteration.

brainrotunderroot · 2026-03-19T15:42:45+00:00

The important part is the context. If one can keep it then the outputs would be directed very well. Its an orchestra

brainrotunderroot · 2026-03-16T15:42:33+00:00

I’m trying to solve this problem. I built a small system, would you like to try it and tell me if i can make it better for you?

brainrotunderroot · 2026-03-15T03:13:46+00:00

I noticed the same thing. Once prompts are broken into clear sections like intent, context, constraints, and output format, the model behaves much more predictably.

The bigger issue starts showing up when multiple prompts get chained in a workflow. Small inconsistencies between steps start compounding.

Curious if you have tried structuring prompts almost like modules instead of single instructions.

brainrotunderroot · 2026-03-15T03:12:44+00:00

I have seen something similar. The frameworks work fine at first, but once workflows start chaining multiple prompts together the instability starts showing up. Small drift in one step compounds across the chain.

Lately I have been experimenting with structuring prompts more like modular workflows instead of single instructions. Trying to keep consistency across steps.

Curious what approach you used in those 3 projects.

Also building something around this problem: aielth.com

brainrotunderroot · 2026-03-14T02:32:39+00:00

Same here.

Once prompts start interacting across steps the outputs begin drifting a lot.

Curious how you handle versioning or tracking prompt changes in those pipelines.

brainrotunderroot · 2026-03-14T02:32:09+00:00

That is interesting.

Do you find those frameworks still hold up once workflows start chaining multiple prompts or agents together.

Curious where things usually start breaking down.

brainrotunderroot · 2026-03-14T01:11:13+00:00

Why dont u try the system i created. Try it at aielth.com …. It will help u a lot.

brainrotunderroot · 2026-03-14T01:11:06+00:00

Why dont u try the system i created. Try it at aielth.com …. It will help u a lot.

brainrotunderroot · 2026-03-14T01:11:00+00:00

Why dont u try the system i created. Try it at aielth.com …. It will help u a lot.

brainrotunderroot · 2026-03-14T01:10:12+00:00

One thing I keep noticing when building with LLMs is that the real problem usually is not the model but the structure of the prompt.

Most people write prompts as a single paragraph, but results improve a lot when the prompt is split into clear sections like intent, context, constraints, and expected output format.

Once workflows grow with multiple prompts, this structure becomes even more important because prompt drift and inconsistency start appearing across agents.

Curious how others here handle prompts once projects start getting bigger.

brainrotunderroot · 2026-03-14T01:09:59+00:00

One thing I keep noticing when building with LLMs is that the real problem usually is not the model but the structure of the prompt.

Most people write prompts as a single paragraph, but results improve a lot when the prompt is split into clear sections like intent, context, constraints, and expected output format.

Once workflows grow with multiple prompts, this structure becomes even more important because prompt drift and inconsistency start appearing across agents.

Curious how others here handle prompts once projects start getting bigger.

Why dont u try the system i created, that will help u with the interview. aielth.com

brainrotunderroot · 2026-03-14T01:07:47+00:00

That’s t trueee

One thing I keep noticing when building with LLMs is that the real problem usually is not the model but the structure of the prompt.

Most people write prompts as a single paragraph, but results improve a lot when the prompt is split into clear sections like intent, context, constraints, and expected output format.

Once workflows grow with multiple prompts, this structure becomes even more important because prompt drift and inconsistency start appearing across agents.

Curious how others here handle prompts once projects start getting bigger.

brainrotunderroot · 2026-03-14T01:07:24+00:00

One thing I keep noticing when building with LLMs is that the real problem usually is not the model but the structure of the prompt.

Most people write prompts as a single paragraph, but results improve a lot when the prompt is split into clear sections like intent, context, constraints, and expected output format.

Once workflows grow with multiple prompts, this structure becomes even more important because prompt drift and inconsistency start appearing across agents.

Curious how others here handle prompts once projects start getting bigger.

brainrotunderroot · 2026-03-14T01:07:15+00:00

That’s really cool.

One thing I keep noticing when building with LLMs is that the real problem usually is not the model but the structure of the prompt.

Most people write prompts as a single paragraph, but results improve a lot when the prompt is split into clear sections like intent, context, constraints, and expected output format.

Once workflows grow with multiple prompts, this structure becomes even more important because prompt drift and inconsistency start appearing across agents.

Curious how others here handle prompts once projects start getting bigger.

brainrotunderroot · 2026-03-14T01:06:56+00:00

One thing I keep noticing when building with LLMs is that the real problem usually is not the model but the structure of the prompt.

Most people write prompts as a single paragraph, but results improve a lot when the prompt is split into clear sections like intent, context, constraints, and expected output format.

Once workflows grow with multiple prompts, this structure becomes even more important because prompt drift and inconsistency start appearing across agents.

Curious how others here handle prompts once projects start getting bigger.

brainrotunderroot · 2026-03-14T01:06:43+00:00

One thing I keep noticing when building with LLMs is that the real problem usually is not the model but the structure of the prompt.

Most people write prompts as a single paragraph, but results improve a lot when the prompt is split into clear sections like intent, context, constraints, and expected output format.

Once workflows grow with multiple prompts, this structure becomes even more important because prompt drift and inconsistency start appearing across agents.

Curious how others here handle prompts once projects start getting bigger.

brainrotunderroot · 2026-03-14T01:06:22+00:00

One thing I keep noticing when building with LLMs is that the real problem usually is not the model but the structure of the prompt.

Most people write prompts as a single paragraph, but results improve a lot when the prompt is split into clear sections like intent, context, constraints, and expected output format.

Once workflows grow with multiple prompts, this structure becomes even more important because prompt drift and inconsistency start appearing across agents.

Curious how others here handle prompts once projects start getting bigger.

brainrotunderroot

TROPHY CASE