Build a Data Pipeline with AI · Execution Map
Design
Design the right solution before building.
Build & Refine
Build, test, secure, and make it production-ready.
Ship & Validate
Ship with confidence and validate results.
Step 1 of 6
Design the ingestion and transforms
Sources, ingestion, and transformation stages designed.
Phase
Design
Everything you need for this step
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Workflow
AI Data Pipeline & ETL Workflow
Design a pipeline that moves data without corrupting it — map the sources and ingestion, design the transformation stages, set validation and quality gates, then document the pipeline and monitoring.
Resource
Data Analyst Role Prompt
A data analyst role prompt with statistical honesty built in — clarify the decision first, treat correlation as a hypothesis, and never launder uncertainty into precision.
Tool
Role Prompt Generator
Generate expert role prompts — perspective, responsibilities, and decision criteria, not just "act as".
Step 2 of 6
Extract and structure the sources
Raw sources extracted into a clean, structured shape.
Phase
Build & Refine
Everything you need for this step
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Workflow
AI Data Extraction Workflow
Turn messy text into structured data you can trust enough to feed another system — bound the source, extract the fields, force clean JSON, and validate before it flows downstream.
Resource
Extract Data From Text with AI
Free text in, named fields out. The extraction prompt pattern that turns any unstructured text into consistent, parseable records.
Tool
Extraction Prompt Generator
Build prompts that extract defined fields from unstructured text — emails, invoices, tickets, résumés.
Step 3 of 6
Gate the data with validation
Validation gates that stop bad data before it's stored.
Phase
Build & Refine
Everything you need for this step
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Workflow
AI Reliable JSON Output Workflow
Make any AI task return JSON your code can rely on — define the schema, force the model to it, validate every response, and diff the drift when a model update breaks the shape.
Resource
Validate Structured Output from AI
Fields checked against the contract: missing ones flagged, invented ones caught, prose around the object detected.
Tool
AI Output Validator
Paste an AI's output and validate it against the expected format — with a repair prompt for every failure found.
Step 4 of 6
Design the storage schema
A target storage schema designed for the pipeline's output.
Phase
Design
Everything you need for this step
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Workflow
AI Database Design Workflow
Design a schema on its data, not a hunch — model the entities and relationships, set the constraints that protect integrity, plan indexes around real queries, then document the schema and migration.
Resource
Schema Design & ERD Prompt — Entities, Relationships, and Keys
Turn product requirements and key entities into an ERD-ready schema spec: tables, fields, primary and foreign keys, relationships with cardinality, indexes, and constraints — with the modeling gaps named as open questions.
Tool
SQL Optimization Prompt
Build evidence-based SQL optimization prompts — goal, platform, and the evidence you have turn into a query tuning contract.
Step 5 of 6
Deliver the data via an API
A delivery API contract for the pipeline's consumers.
Phase
Build & Refine
Everything you need for this step
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Workflow
AI API Design Workflow
Design an API on its contract instead of discovering it endpoint by endpoint — model the resources, design the endpoints and payloads, pin the contract, then review it before code locks it in.
Resource
Turn a JSON Schema into a Prompt
You have the schema — fields, types, requirements. The translation into a prompt the model actually follows: schema lines, realistic example, and validation rules.
Tool
JSON Output Prompt Builder
Build prompts that return structured data — JSON first, with YAML, XML, and CSV modes — parseable every time.
Step 6 of 6
Ship and monitor the pipeline
The pipeline shipped with monitoring on volume, freshness, and quality.
Phase
Ship & Validate
Everything you need for this step
Download full path PDF
Workflow
AI Deployment & Release Workflow
Cross the gap between 'tests pass' and 'safe in production' — assess release readiness, plan the deploy and its rollback, and set up the monitoring and launch checks before you ship, not after.
Resource
Production Readiness Review Prompt
SHIP or DO NOT SHIP: twelve checks on failure modes, observability, rollback, and load — the review that happens before the incident.
Tool
Markdown Output Builder
Build prompts that produce documents in a fixed structure — headings, sections, and tables.