Prompting, Grounding and Sampling Controls
This topic covers prompt design, examples, instructions, output formats, grounding, retrieval, temperature, token limits, safety settings, and iteration.
How to study for Google Cloud Generative AI Leader
Treat each item as a leadership decision: define business value, match Google Cloud capabilities, improve output quality, then govern rollout responsibly.
Core concepts
Concept 1
Prompt design should define the role, task, constraints, context, examples, output format, and failure behavior.
Exam cue: Tighten instructions and output format when responses are inconsistent.
Concept 2
Grounding and retrieval help the model use trusted sources instead of relying only on general model knowledge.
Exam cue: Add grounding when answers must reflect current or private facts.
Concept 3
Sampling and output controls affect creativity, consistency, length, cost, latency, and repeatability.
Exam cue: Lower randomness when predictable answers are more important than variety.
Risk pitfalls and guardrails
Using vague prompts for regulated or customer-facing outputs.
Guardrail: Avoid choosing a model before proving business value, data readiness, evaluation criteria, and responsible AI controls.
Adding more tokens without improving source quality or instructions.
Guardrail: Avoid choosing a model before proving business value, data readiness, evaluation criteria, and responsible AI controls.
Using high creativity settings when accuracy and consistency matter.
Guardrail: Avoid choosing a model before proving business value, data readiness, evaluation criteria, and responsible AI controls.
Memory anchors
Prompt Design
Prompt design specifies role, task, context, constraints, examples, output format, and failure behavior.
Few-Shot Example
A few-shot example shows the model the desired style, reasoning pattern, or output structure.
Grounding
Grounding supplies trusted source context so outputs can reflect known facts and citeable evidence.
Retrieval
Retrieval finds relevant source content before generation.
Temperature
Temperature affects output randomness and creativity.
Token Limit
A token limit constrains input or output length and influences cost, latency, and completeness.
Output Format
An output format makes responses easier to review, parse, score, or integrate with workflows.
Safety Filter
A safety filter blocks or flags outputs that violate harm, policy, or compliance expectations.
Checkpoint rule
Do the check-up only after you can summarize each concept in one sentence and identify one dangerous pitfall from memory.
Knowledge Check (after reading)
Short check-up to confirm understanding of this module.
Check-up Questions
A user asks a model to classify a support message as Billing, Technical, or Account, and the prompt provides instructions but no demonstrations. Which prompting approach is this?
A prompt shows one correctly formatted expense-summary example before asking the model to summarize a new report. Which technique is being used?
Answer all questions to submit.
Next step personalized recommendations
Continue learning
Move forward only after this module is stable.
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