Part VII — Multimodal & Long Context (Where AI Studio Gets Spicy)

What this part is for

Part VII is about using non-text inputs and long context in a way that keeps your vibe loop fast and correct.

When you can show the model what you’re seeing—UI screenshots, diagrams, long documents, transcripts—you reduce the “translation tax” of turning reality into words. That can make iteration dramatically faster. It can also make mistakes more subtle: the model may confidently describe what it thinks is in the image/document, even when it’s missing key details.

The goal of this part is to make multimodal and long-context work procedural: you’ll learn how to package inputs, ask for structured outputs, and validate quickly.

The multimodal mindset: inputs as evidence

Multimodal vibe coding works best when you treat inputs like evidence in a bug report:

• Be explicit about what the model should do: diagnose, extract, critique, or generate tests.
• Constrain the output: JSON schemas, checklists, ranked lists, or “3 hypotheses max.”
• Ask for uncertainty: “If you’re not sure, say so and ask for a clearer screenshot or missing context.”
• Prefer repeatable steps over clever guesses: “How do I confirm this in DevTools?” beats “What CSS should I write?”
• Keep a privacy posture: minimize what you upload; redact by default.

What you’ll be able to do after Part VII

• Use screenshots to debug UI layout issues with a testable diagnosis plan.
• Extract structured data from images safely (with confidence fields and error handling).
• Get actionable UX critique that produces experiments, not just opinions.
• Generate visual test cases from mockups and screenshots (states, edge cases, selectors).
• Work with long documents by chunking, citation-like outputs, and contradiction handling.
• Turn meeting audio/video into action items, decisions, and a searchable knowledge log—without inventing facts.

Common traps (and how to avoid them)

• “Fix this screenshot” prompts: provide the HTML/CSS, expected behavior, and constraints; demand minimal diffs.
• Unbounded extraction: always define a schema, and allow null for unknown fields.
• Hallucinated details: require quotes/regions-of-interest for claims (“where in the image/doc did you see that?”).
• Overlong context dumps: chunk, summarize, and retrieve; do not paste 100 pages and hope.
• Privacy leakage: remove PII/secrets; don’t upload sensitive user content unless you have a policy and consent.

A practical multimodal vibe loop

Use this loop as a default for images, docs, and transcripts:

1. Package the input: a screenshot pack, doc pack, or transcript pack (high-signal, minimal, redacted).
2. Declare the task: “diagnose,” “extract,” “critique,” or “generate tests.”
3. Constrain output: JSON schema or checklist with required fields.
4. Force evidence: quotes, references, or “call out the UI region you’re describing.”
5. Verify: run a small check (DevTools inspection, sample extraction review, or one test case).
6. Iterate: ask for a minimal patch or the next smallest step.

Part VII map (Sections 21–23)

• 21. Working With Images
• 22. Working With Documents and Large Text
• 23. Audio/Video Inputs (If Your Workflow Uses Them)

Where to go next

• Start with images (Section 21)
• Reference: structured output patterns (Part V)
• Reference: safety and guardrails (Part IV)