LLMs

Discover how to audit your personal writing history and reconcile the scale of human memory with the massive context windows of modern AI models.

Explore why AI coding assistants often struggle with UI development and discover practical strategies to improve their output, from better prompting to multimodal context integration.

With the Fable 5 free promotional period ending, developers debate whether the model's performance justifies a shift to usage-based billing or if existing alternatives remain more cost-effective.

Learn how senior engineers move beyond basic AI prompting by implementing systematic workflows, maintaining context, and focusing on structural integrity.

Discover how developers are leveraging Fable 5 for a wide range of projects, from autonomous AI agents and complex web apps to system architecture and data visualization.

Explore the shift from passive chatbot interactions to active, bespoke developer workflows to maintain flow state when building with LLMs. Discover how to create your own harnesses and orchestrated agent systems for higher productivity and deeper code understanding.

Does AI consumption ruin your ability to read books? Explore why instant knowledge affects our attention spans and how to reclaim the joy of slow, deep reading.

Explore the trade-offs between using high-memory MacBook Pros versus dedicated NVIDIA-based workstations for running local LLMs and agentic workflows.

Explore the current landscape of running local LLMs, covering popular model choices like Qwen 3.6, hardware recommendations, and the challenges of non-NVIDIA setups.

Explore whether copying software functionality and UI is still defensible when not directly copying source code, especially in the age of AI.