UNDER THE HOOD / LAB

The technical toolkit.

A working set of languages, tools, methods and questions—not a wall of inflated expertise.

SOFTWARE ENGINEERING

Building the architecture that connects interfaces, APIs, and reliable data.

PythonFlaskJavaScriptHTML & CSSREST APIsSQLAlchemyJinja2PostgreSQLMySQLGit & GitHubDockerLinux

AI & AGENTIC DEVELOPMENT

Using models and coding agents as tools—paired with testing, review and human judgment.

Gemini APIRAG conceptsDocument processingOllamaLocal LLM explorationOpenAI CodexClaude CodeAI-assisted debuggingStructured evaluation

DATA & VALIDATION

Finding structure and traceability within complex technical inputs.

PandasOpenPyXLCSV / JSONData modelingData dictionariesInput validationReproducible testsTechnical specificationsDocumentationResearch evidence

A CURRENT QUESTION

Can an AI observation
be trusted?

In the SMC AI Lab, my ongoing research explores how models could interpret market context, how those observations might be checked, and how evidence-aware analysis could eventually support decisions and journaling. The system is experimental; no production trading or validated predictions are claimed.

READ ABOUT SMC AI LAB ↗

FIG. / 03

SMC AI LAB / RESEARCH CONCEPTSYNTHETIC · NO LIVE EXECUTION

ILLUSTRATIVE MARKET CONTEXTSIM / MTF

CURRENT STAGE / 01

01/ 04

Observe.

MARKET CONTEXT

Synthetic candles and multi-timeframe context are inspected.

ILLUSTRATIVE RECORDResearch observation only

CONCEPTUAL UI · Synthetic candles · No real trading or automatic orders