4. Orchestrator-workers:

In the orchestrator-workers workflow, a central LLM dynamically breaks down tasks, delegates them to worker LLMs, and synthesizes their results.

3. Parallelization:

The Parallelization Pattern divides large tasks into smaller, independent units that can be processed simultaneously.

2. Evaluator-optimizer:

In the evaluator-optimizer workflow, one LLM call generates a response while another provides evaluation and feedback in a loop.

Community Focus:

Feed Generator: Can highlight posts from specific communities or hashtags.

Searching "Python": Shows all posts with the term, regardless of community or context.

Decentralization:

Feed Generator: Anyone can create a feed generator, offering diverse perspectives.

Searching "Python": Relies on Bluesky’s centralized search functionality.

Customization:

Feed Generator: Can be tailored to your preferences (e.g., tutorials, news, memes about Python).

Searching "Python": Limited to the platform’s search algorithm.

Passive vs Active:

Feed Generator: Passive – you get a continuous stream of Python content.

Searching "Python": Active – you need to initiate the search.

Relevance:

Feed Generator: Can filter out irrelevant content (e.g., snakes, Monty Python).

Searching "Python": Shows all posts containing the term "Python," including unrelated topics.

Content Delivery:

Feed Generator: Automatically curates and delivers Python-related posts to your feed.

Searching "Python": Requires you to manually search for "Python" every time.