AI-Driven Software Development Lifecycle

Build Real Products
with AI at Every Phase

A hands-on course series covering the full AI-SDLC — from data pipelines to APIs to frontends. Every phase uses AI tools: planning, design, implementation, testing, deployment, and governance.

23
Courses
130+
AI-SDLC Phases
500+
Code Samples
6
Learning Tracks
💡 New to AI development tools?
Not sure where to begin? Start here.
Every course is anchored in one real-world platform: a UCC Lien Risk Intelligence system. Begin with the domain reference & prompt engineering — they make every technical course 3× faster to complete.
Quick Navigation
23 Courses. 6 Tracks. One Unified System.

Each course builds a real component of the UCC Lien Risk platform. Organized into six tracks — from domain foundations through data engineering, APIs, frontends, AI tools, and autonomous agents. Every course uses real AI tools at every SDLC phase.

📚
Foundation
Start Here • No Prerequisites

Master the domain and prompting skills first — they make every other course 3× faster. No cloud accounts or code experience needed to begin.

08
📋
Domain Reference · Commercial Credit
Beginner
US Public Records — Commercial Credit Data Reference
The domain intelligence backbone for the entire series. Master UCC filings, tax liens, civil suits, judgments, and bankruptcies — the public data layers that drive commercial credit decisions. No code required.
UCC FilingsTax LiensCivil SuitsJudgmentsBankruptcies§9-503
8 Phases
48 Sections
Domain Intel
10
🌟
AI Skills · Prompting
Beginner
Prompt Engineering Masterclass for AI-SDLC
The #1 skill that multiplies every other AI tool. Master the RCTF framework, context engineering (CLAUDE.md / GEMINI.md), Chain-of-Thought reasoning, debugging patterns, agent task design, and anti-patterns.
RCTF FrameworkContext EngCoT ReasoningAgent PromptsDebug PatternsAnti-Patterns
10 Phases
47 Sections
RCTF→Agent
⚙️
Build Track — Full Stack
Data Eng • APIs • Frontends • GCP + Local

Build every layer of the UCC Lien Risk platform — data pipelines, REST APIs, React and Angular frontends. Each course has a GCP cloud and Local (Docker/DuckDB) edition.

DE
📊
Data Pipelines · PySpark · GCP
Intermediate
Data Engineering — GCP Medallion Pipeline
Build a Bronze→Silver→Gold pipeline with PySpark on Dataproc, BigQuery, and Cloud Composer. Processes 50K+ UCC filings with deduplication, name standardization, and risk score aggregation.
PySparkBigQueryCloud ComposerDataprocParquet
12 Phases
GCP
Medallion
DE-L
📊
Data Pipelines · PySpark · Local
Intermediate
Data Engineering — Local (DuckDB + Docker)
Same medallion pipeline, zero cloud cost. DuckDB for analytics, Docker Compose for services, local PySpark.
PySparkDuckDBDockerParquetWSL2
11 Phases
Local
Zero Cloud
API
REST API · Spring Boot · GCP
Intermediate
Spring Boot API — GCP
Build the UCC Risk API with Spring Boot 3, JPA, PostgreSQL, Redis caching, OAuth2, and Testcontainers.
Spring BootJPAPostgreSQLRedisOAuth2
10 Phases
GCP
REST + Auth
API-L
REST API · Spring Boot · Local
Intermediate
Spring Boot API — Local (Docker)
Same API architecture, fully local. PostgreSQL and Redis in Docker Compose, no cloud account required.
Spring BootDocker ComposePostgreSQLRedis
10 Phases
Local
Zero Cloud
FE
⚛️
Frontend · React · TypeScript
Intermediate
React Frontend — UCC Risk Dashboard
Filing search UI and risk dashboard with React, TypeScript, TanStack Query, MSW, and Playwright.
ReactTypeScriptTanStack QueryMSWPlaywright
9 Phases
React 18
Dashboard
FE-L
⚛️
Frontend · React · Local
Intermediate
React Frontend — Local
Same React dashboard, fully local. Mock API server included.
ReactTypeScriptMSWVite
9 Phases
Local
Zero Cloud
NG
🅰
Frontend · Angular · TypeScript
Intermediate
Angular Frontend — UCC Risk Dashboard
Same risk dashboard with Angular 17+, Signals, RxJS, Angular Material, and Cypress.
AngularSignalsRxJSMaterialCypress
9 Phases
Angular 17+
Dashboard
NG-L
🅰
Frontend · Angular · Local
Intermediate
Angular Frontend — Local
Same Angular dashboard, fully local. Mock API server included.
AngularSignalsRxJSDocker
9 Phases
Local
Zero Cloud
🧠
AI Power Tools
Supercharge Your Workflow

The tools that turn a good developer into a 10x developer. Use AI for code review, spec-driven planning, project management, and building custom integrations via MCP.

09
AI Coding · Gemini
Beginner–Intermediate
AI-Powered Development with Gemini Code Assist
Master Google's Gemini Code Assist from IDE plugin to autonomous Agent Mode. VS Code & JetBrains setup, Gemini CLI, GitHub PR review bot, Jira AI integration, MCP server connections, and enterprise governance.
VS CodeJetBrainsAgent ModeGemini CLIGitHub BotMCPISO 42001
9 Phases
38 Sections
IDE→Agent→CI
04
📄
Spec-Driven Dev · OpenSpec
Intermediate
AI-SDLC for Spec-Driven Development with OpenSpec
Master OpenSpec — the universal planning layer for AI coding agents. Write durable capability specs, generate structured proposals before writing code, implement with /opsx:apply, integrate spec coverage into CI. Works with 30+ agents.
OpenSpecClaude CodeCursorGitHub CopilotSpec DeltasISO 42001
9 Phases
6 Spec Files
🏆 Capstone
04C
🎹
Context-Driven Dev · Conductor
Intermediate
Context-Driven Development with Gemini Conductor
Master Google's Conductor extension for Gemini CLI. Persistent context as managed artifact — product specs, TDD-driven implementation, automated review, and semantic revert. Includes full Conductor vs OpenSpec decision framework.
Gemini CLIConductorTDDSpec & PlanAuto ReviewOpenSpec
11 Phases
180 Sections
🏆 Capstone
05
🛠️
Project Intelligence · Atlassian AI
Beginner–Intermediate
AI Project Management with Atlassian AI
Jira AI, Confluence AI, and Atlassian Rovo as the project intelligence layer. Generate stories and acceptance criteria, draft ADRs and runbooks, automate PR-to-issue linking, run AI-assisted sprint ceremonies, govern AI usage for ISO 42001.
Jira AIConfluence AIAtlassian RovoJira AutomationSprint CeremoniesISO 42001
10 Phases
3 AI Tools
🏆 Capstone
06
🔫
MCP Servers · Node.js
Advanced
Build Your Own MCP Servers with AI
Build production-ready MCP servers for BigQuery, GitHub, Jira, and Spring Actuator. Connect them to Gemini Code Assist Agent Mode. Use AI to scaffold the servers themselves — tools, resources, and prompts from scratch.
Node.jsMCP SDKBigQueryGitHub APIJira RESTGemini Agent
11 Phases
4 MCP Servers
🏆 Capstone
07
🤖
AI Agent · Claude API
Advanced
Build an AI Agent That Codes, Tests & Ships
Build a Python agent using the Claude API that reads OpenSpec tasks, writes code, runs tests, auto-fixes failures, creates PRs, and updates Jira — a full autonomous SDLC loop from spec to merged PR.
PythonClaude APITool UseOpenSpecGitHubJiraDocker
10 Phases
Full SDLC Loop
🏆 Capstone
RA
🛡️
Governance · Security
All Roles
Responsible AI in the SDLC
Every AI output is a draft. Verification protocols, prompt injection defense, EU AI Act & NIST AI RMF for developers, token cost estimation, AI observability, and living documentation. Build AI systems you can trust and audit.
Prompt InjectionEU AI ActNIST RMFCost CalculatorAudit Trail
6 Phases
~4 hrs
All Levels
AI Power Tools — Java Spring Boot
Same Tools • Java Examples • Spring Boot Labs

Every course above has a Java Spring Boot edition — identical frameworks and concepts, but every code example, prompt, and lab uses Java 21, Spring Boot 3, Maven, and JUnit. Pick these if your team writes Java.

J2
AI Skills · Prompting · Java
Beginner
Prompt Engineering Masterclass — Java Spring Boot Edition
The same RCTF framework and prompt patterns, grounded in Java Spring Boot examples. Context engineering with CLAUDE.md / GEMINI.md for Java projects, Spring Boot–specific CoT patterns, JUnit test generation prompts, and Java API design prompts.
RCTF FrameworkJavaSpring BootContext EngCoT ReasoningJUnit Prompts
11 Phases
Java Examples
RCTF→Agent
J3
AI Coding · Gemini · Java
Beginner–Intermediate
Gemini Code Assist — Java Spring Boot Edition
Gemini Code Assist applied to Java Spring Boot development. IDE setup for IntelliJ & VS Code, Agent Mode for Java, Spring Boot–specific code generation, JUnit test scaffolding, Maven/Gradle integration, and enterprise governance for Java teams.
JavaSpring BootIntelliJVS CodeAgent ModeGemini CLIMaven
10 Phases
107 Sections
IDE→Agent→CI
J4
Spec-Driven Dev · OpenSpec · Java
Intermediate
OpenSpec — Java Spring Boot Edition
Spec-driven development with OpenSpec for Java Spring Boot projects. Write capability specs for REST APIs, generate structured proposals with /opsx:apply, integrate spec coverage into Maven builds, and govern multi-repo Java architectures.
OpenSpecJavaSpring BootClaude CodeSpec DeltasMaven CI
8 Phases
Java REST API
🏆 Capstone
UCC Lien Risk Intelligence

Every course is anchored in a real-world use case: processing US Business UCC Filings to surface secured-transaction lien risk for commercial credit decisions. Here's the domain you'll master.

What is UCC?

The Uniform Commercial Code Article 9 governs secured transactions in the US. When a lender takes collateral, they file a UCC-1 Financing Statement with the secretary of state — creating a public lien record that signals credit risk to other creditors.

Our platform ingests filings across 5 states, standardizes debtor names, links entities, and computes a composite Lien Risk Score (0–100) used in commercial underwriting.

Filing Lifecycle

1 · UCC-1 Initial Filing
Lender files to perfect security interest; lien becomes public record
2 · UCC-3 Continuation
Extends lien beyond the 5-year lapse period; must be filed timely
3 · UCC-3 Amendment
Updates collateral description, debtor name, or secured party info
4 · Lapse (5-year rule)
Unfiled continuation causes automatic lien termination; priority lost
5 · UCC-3 Termination
Secured party releases interest; lien removed from active record
The Data Journey — From Raw Filings to Risk API
BRONZE
Raw Ingestion
XML → Parquet
GCS landing zone
Schema validation
Data Eng
SILVER
Standardization
§9-503 name rules
Entity deduplication
State normalization
Data Eng
GOLD
Risk Profiles
Lien risk scoring
Entity graph
Blanket lien flags
Data Eng
API
Spring Boot
REST endpoints
Risk score serve
Search & filter
Spring Boot
UI
React Dashboard
Search filings
Risk dashboard
Entity graph viz
Frontend
📄
UCC-1 Financing Statement
The initial lien filing that perfects a secured party's interest in collateral. Contains debtor name, secured party, and collateral description — the raw material of the entire pipeline.
⚖️
§9-503 Name Standard
Registered organizations must use their exact name from the public organic record. Errors make filings “seriously misleading” and legally ineffective — a core NLP challenge in the pipeline.
🏆
Perfection & Priority
A lien is “perfected” when properly filed. The first to file generally wins priority — making data freshness and search accuracy directly tied to real credit risk decisions.
📊
Lien Risk Score (0–100)
Composite score: active lien count (40%), blanket lien presence (30%), lien age & recency (20%), cross-state exposure (10%). Drives underwriting decisions in the Gold layer.
🔗
Entity Linking
The Silver layer resolves variant debtor names (abbreviations, misspellings, trade names) to canonical legal entities using fuzzy matching + ML disambiguation.
🔒
Blanket Lien
A UCC-1 covering “all assets” or “all personal property” of a debtor. Blanket liens signal maximum encumbrance — a high-risk flag triggering special scoring logic and UI alerts.
847K
UCC filings processed
1.2M
entities resolved
5
US states covered
78.4%
name-match accuracy
412K
risk profiles / day
42 min
end-to-end runtime
Choose Your Path

Every developer has a different starting point. Select your role to see the ideal course sequence — then level up across the entire AI-SDLC stack.

AI Practitioner
Master AI coding tools, prompt engineering, and spec-driven development
Java Developer
Java Spring Boot focused — prompts, Gemini, and OpenSpec for Java
📊
Engineering Manager
Lead AI-augmented teams with project intelligence & governance
🔫
AI Tool Builder
Build MCP servers, spec-driven pipelines, and AI integrations
👆
Select your role above to see your recommended learning path
60-Second Path Finder
Find Your Ideal Learning Track
Answer 5 quick questions and we'll recommend the right course sequence for your role.
QUESTION 1 OF 5
📋
PHASE 01
Plan
Jira AI decomposes epics into AI-enhanced stories
📐
PHASE 02
Design
OpenSpec turns stories into machine-readable specs
⚙️
PHASE 03
Build
Gemini Agent Mode generates code from specs autonomously
🧪
PHASE 04
Test
AI generates test suites with domain-aware edge cases
🚀
PHASE 05
Deploy
Terraform + Harness CD with AI-generated pipelines
🏛️
PHASE 06
Govern
ISO 42001 + NIST AI RMF with automated audit trails