PHASE 8A — DAILY USAGE WORKFLOW (HOW YOU ACTUALLY USE THE SYSTEM)

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🎯 Goal

This phase is NOT technical.

It defines:

how you use your AI trading research system every day to produce real strategy insights

Think of it as your operating procedure for turning data into decisions.


🧠 CORE IDEA

Your system is not meant to be “chatty AI.”

It is meant to behave like a:

quantitative research assistant for your historical trading data

So your workflow must be structured.


🔁 DAILY RESEARCH WORKFLOW (STANDARD LOOP)

You will always work in this cycle:


🟢 STEP 1 — PICK A RESEARCH QUESTION

You never start with random prompts.

You start with structured intent:

Examples:

  • “Why did Strategy A underperform in 2022?”
  • “Which strategies survive high volatility regimes?”
  • “What causes drawdowns in my momentum system?”

🟡 STEP 2 — SELECT CONTEXT (FILTER YOUR SYSTEM)

In the dashboard:

  • choose strategy (or multiple)
  • select regime (bull / bear / volatility)
  • optionally select time window

This narrows the RAG search space.


🔵 STEP 3 — RUN ANALYSIS (PHASE 4 ENGINE)

You submit the question.

System automatically:

  • retrieves relevant historical chunks
  • filters by regime
  • builds structured context
  • runs LLM (14B / 20B)
  • returns structured output

📊 STEP 4 — READ OUTPUT LIKE A RESEARCHER (NOT CHAT)

You NEVER treat output as “answers.”

You treat it as:

hypothesis + evidence summary

You evaluate:

  • Is reasoning consistent with data?
  • Are comparisons actually supported?
  • Are regime differences meaningful?
  • Are weaknesses clearly explained?

🧠 STEP 5 — IDENTIFY INSIGHTS

You extract:

  • what works
  • what fails
  • under what conditions
  • why performance changes

You are building strategy knowledge, not reading chat replies.


💾 STEP 6 — SAVE INSIGHTS

Every useful result is stored:

  • /06_ANALYSIS_OUTPUTS/

You are building a research memory system over time.


🔁 STEP 7 — ITERATE QUESTIONS (IMPORTANT)

Good workflow is recursive:

  1. Ask question
  2. Get result
  3. Identify gap
  4. Refine question

Example loop:

  • “Why did momentum fail?”
  • “Was failure concentrated in high volatility only?”
  • “Which trades caused most drawdown?”
  • “What happens if we remove those periods?”

🧠 DAILY SESSION STRUCTURE (REAL USE)

A proper session looks like:


🟢 1. Exploration Phase

  • broad strategy questions
  • identify patterns

🟡 2. Deep Dive Phase

  • isolate regimes
  • compare strategies

🔵 3. Stress Test Phase

  • challenge assumptions
  • test edge cases
  • use 20B model

🟣 4. Synthesis Phase

  • summarize findings
  • store insights
  • update strategy thinking

🚫 COMMON MISTAKES TO AVOID

❌ Treating AI like prediction engine

It is not forecasting.


❌ Asking random unstructured questions

You lose retrieval quality.


❌ Not using regime filters

You lose the entire point of your architecture.


❌ Not saving outputs

You lose compounding knowledge.


🧠 WHAT THIS PHASE REALLY GIVES YOU

This is what changes everything:

You are no longer “chatting with AI”

You are:

running structured quantitative research sessions on your own trading history


💡 ONE-LINE SUMMARY

Phase 8A defines how you operate your system daily as a structured research workflow to generate, test, and refine trading strategy insights.