Inspect LiveView socket assigns for memory bloat — missing temporary_assigns, unused assigns, unbounded lists needing streams, memory…
Use for Livewire performance work. Covers what one Livewire request actually costs, the snapshot that travels both ways on every request…
Develop and contribute to the PinchTab project.
Deconstructs academic papers into simplified summaries and visualizes cognitive insights using ASCII art and personal knowledge baselines.
Converts structured outlines into high-impact, slogan-style HTML presentations with ultra-bold typography and minimalist aesthetics.
Transforms complex articles, papers, and books into sharp, logical Q&A chains that reveal an author's core argument skeleton.
Runs LLM inference on CPU, Apple Silicon, and consumer GPUs without NVIDIA hardware.
Meta's 7-8B specialized moderation model for LLM input/output filtering. 6 safety categories - violence/hate, sexual content, weapons…
Use when ANY runtime debugging is needed — setting breakpoints, inspecting variables, evaluating expressions, analyzing threads, or…
LLM-based text classification: codebook, validation, agreement statistics.
LLM-based zero-shot and few-shot classification for flexible intent detection
Use proactively whenever LLM API costs come up -- or should.
Run any question, idea, or decision through a council of 5 AI advisors who independently analyze it, peer-review each other anonymously…
Run multi-LLM council for adversarial debate and cross-validation.
Master comprehensive evaluation strategies for LLM applications, from automated metrics to human evaluation and A/B testing.
Bootstrap a reproducible LLM Observability experiment through the Python ddtrace SDK or the Node dd-trace SDK.
LLM Operations -- RAG, embeddings, vector databases, fine-tuning, advanced prompt engineering, LLM costs, quality evals and…
Pydantic-AI agents, RAG, embeddings for Pulse Radar knowledge extraction.
LLM streaming response patterns. Use when implementing real-time token streaming, Server-Sent Events for AI responses, or streaming with…
Get reliable JSON, enums, and typed objects from LLMs using response_format, tool_use, and schema-constrained decoding across OpenAI…
Use when building or maintaining a persistent personal knowledge base (second brain) in Obsidian where an LLM incrementally ingests…