Data & AI toolkit.

My thinking layer for product reasoning, PRDs, strategy, rapid research, and comparing perspectives on complex questions.

I use these cheaper open-weight models for a second opinion and for faster work on low- to medium-scale tasks, including recent side projects.

I source open models and datasets on Hugging Face and use Groq for fast inference and experimentation.

Used to interrogate source-heavy material and synthesize reports and papers against a controlled document set.

My system for requirements, roadmaps, documentation, project tracking, and keeping execution visible.

Cowork agents with custom skills and n8n for automating workflows across documents, analysis, planning, and everyday knowledge work.

My vibe-coding and agentic development stack for planning, implementation, larger changes, code review, and multi-step execution.

The IDE I use daily, paired with Copilot as an agentic code companion for refactors, debugging, and staying close to the code while iterating.

The local runtime I use when a prototype needs to stay private or stay cheap.

The core stack for cleaning data, exploring relationships, automating analysis, and building evidence-backed models.

My modeling toolkit for interpretable machine learning, anomaly detection, evaluation, and neural networks when they measurably beat the simpler baseline.

For products that need retrieval, tool use, domain context, or multi-step reasoning instead of a single model response.

I turn models into usable interfaces early, so stakeholders can react to behavior rather than abstract specifications.

I use these tools to turn data products, dashboards, and visualizations into decisions, showing where the numbers disagree, where the risk sits, and which trade-off we're making.