GenAI Solutions & Delivery

Scope GenAI solutions with estimation, risk, and success criteria. Orchestrate delivery teams, manage client relationships.

Preview 16 goals free

10 skill groups10 courses1182 goals~534 hrs

Verifiable skill graph

10 skill groups · each becomes a signed node on your graph.

Every lab you pass signs a W3C Verifiable Credential on your public skill graph. Completing the labs in each group below mints one node on that graph — the badge you walk away with is a cryptographic record of what you can ship, not a completion certificate.

Share the URL on your résumé or with a hiring manager. They click; they see the discipline, the labs you passed, and the verification signature. No honor system, no broker.

POC-to-Production Transition

Taking a delivered GenAI POC to production: transition playbooks, observability/SLA instrumentation, robustness hardening, capacity planning. The lab-provable delivery deliverable.

Quality Gates & Eval Pipelines

Eval-driven delivery quality: CI/CD quality gates, golden-trajectory regression suites, RAGAS/DeepEval pipelines, LLM-judge calibration. The strongest lab-assessable bar for this role.

Architecture Conformance & Reviews

Ensuring a delivery conforms to the target architecture: ADR/reference-architecture conformance, technical-standards adherence, architectural-quality gates. The lab-checkable conformance face (the review-judgment half is reserved for the portfolio track).

Solution Tech Depth: Agents + RAG

Hands-on technical depth: agent loops, ReAct, MCP, multi-agent orchestration, production RAG, vector + graph DB engineering. Demonstrable in labs.

Production Ops & Cost Management

Running the delivered solution: incident-response runbooks, automation, cost attribution/chargeback, token-budget controllers, capacity forecasting, FinOps.

Delivery Risk & Compliance (Technical)

The technical/automatable face of delivery governance: compliance pre-flight (EU AI Act/SOC2/HIPAA), regulatory-artifact generation, change-control gates, risk-register tooling. Governance-committee facilitation is reserved for the portfolio track.

Solution Scoping (Technical Feasibility)

The lab-assessable feasibility face of scoping: data-readiness assessment, technical feasibility analysis, effort estimation from technical signals, success-criteria definition. Live client discovery/qualification is reserved for the portfolio track.

Prototyping & Demo Engineering

The buildable half of delivery framing: rapid prototyping for client validation, scaffold libraries, demo engineering, synthetic-data scaffolds. Delivery-framework design is reserved for the portfolio track.

Hosted LLM API Integration

Provider SDK literacy: OpenAI/Anthropic/Gemini integration, multi-provider abstraction. Prerequisite.

Python for Delivery Engineering

Production-grade Python for delivery tooling: async, Pydantic, typing, pytest. Prerequisite.

What you'll ship in production

Core responsibilities this discipline prepares you for.

1
Lead end-to-end GenAI project delivery
from discovery through production handoff
- Run the complete delivery lifecycle: discovery workshops → problem scoping → rapid prototyping → handoff
- Drive evaluation-driven iteration with measurable quality gates and knowledge transfer
- Walk through each delivery phase with realistic client scenarios including scoping and risk assessment
2
Design GenAI architecture
for client engagements
- Apply cell-based AI, MCP mesh, and multi-tenant architecture patterns to client requirements
- Write ADR documentation with reference designs and technology evaluation rationale
- Create architecture proposals for varied client scenarios and defend design decisions under review
3
Build agent-based solutions
for client business processes
- Design LangGraph agents with MCP tool integration and human-in-the-loop approval gates
- Customize agent behavior, tool access, and workflow logic for different business process requirements
- Build and deploy domain-specific agents adapted to varied client business scenarios
4
Customize enterprise LLM deployments
— gateways, RAG, domain adaptation
- Operate LiteLLM gateways with multi-provider management and enterprise RAG stack customization
- Adapt LLM deployments for healthcare, finance, and legal verticals with domain-specific constraints
- Deliver end-to-end LLM customization for regulated industries with compliance validation
5
Manage FinOps
for client GenAI projects
- Build token cost attribution models with budget forecasting and TCO analysis for proposals
- Design cost optimization strategies across providers, caching tiers, and model selection
- Build cost models, forecast annual spend, and present optimization recommendations to stakeholders
6
Scope project timelines and team requirements
- Apply effort estimation frameworks designed for non-deterministic GenAI project delivery
- Map team skills, assess technical risks, and develop detailed project proposals
- Estimate effort for sample GenAI projects and identify optimal team composition and skill coverage
7
Package solutions as deployable artifacts
for client operations teams
- Build Helm charts with operational runbooks, SLA definitions, and integrated monitoring
- Create client handoff documentation with deployment guides and escalation procedures
- Package a complete GenAI solution and conduct a simulated client handoff with operational validation
8
Advise clients on technology roadmaps
with emerging GenAI patterns
- Evaluate emerging patterns: A2A protocol, MCP mesh, cell-based AI, and multi-tenant architectures
- Assess industry trends, adoption timelines, and migration strategies for client technology stacks
- Build technology roadmap recommendations that balance innovation with operational stability

Curriculum

10 courses · each builds on previous goals

16 goals unlocked for preview — click to read. Locked goals need a subscription.

CourseGoalsWeight

Python Essentials for Agent Builders621.8%

Your Dev Environment4

Navigate filesystem with terminal
Manage files from command line
Set up VS Code
Configure terminal in VS Code

Python, Git & Package Management6

Install and verify Python
Write hello world script
Use Python REPL
Initialize Git repository
Track changes with Git
Install packages with pip

Variables & Basic Types5

Create and name variables
Work with strings
Work with numbers
Work with booleans
Format with f-strings

Control Flow4

Make decisions with if/elif/else
Iterate with for loops
Repeat with while loops
Control loop execution

Functions5

Define and call functions
Use parameters
Return values
Document with docstrings
Understand scope

Modules & Imports4

Import standard library
Create custom modules
Understand Python path
Create packages

Lists & Tuples5

Create and access lists
Modify lists
Slice lists
Use list comprehensions
Work with tuples

Dictionaries & Sets5

Create and access dicts
Modify dictionaries
Iterate over dicts
Work with nested dicts
Use sets

Classes & Dataclasses5

Understand class basics
Create dataclasses
Add methods
Use default values
Basic inheritance

Files, JSON & Error Handling5

Read and write files
Work with JSON
Use pathlib
Handle exceptions
Create custom exceptions

Basic Testing4

Use assert statements
Create test functions
Run pytest
Test classes

Environment Variables & Configuration5

Understand environment variables
Use .env files
Load with python-dotenv
Handle missing variables
Organize configuration

Decorators & Context Managers5

Understand decorators
Write simple decorators
Use context managers
Write context managers
Combine patterns

LLM Foundations for Agent Builders651.9%

Generators & Iterators5

Understand iteration
Create generators
Use generator expressions
Build data pipelines
Use itertools

Async Programming Basics5

Understand async concepts
Write async functions
Run concurrent operations
Use async context managers
Handle async exceptions

Type Hints & Pydantic5

Add basic type hints
Use typing generics
Create Pydantic models
Validate API data
Configure Pydantic

Data Pipelines & Transformations5

Build functional pipelines
Work with tabular data
Transform data shapes
Process LLM data formats
Optimize for performance

HTTP Clients & httpx5

Make GET requests
Make POST requests
Use async httpx
Handle errors
Use sessions

Your First LLM Call5

Set up credentials
Install Gemini SDK
Make first API call
Parse response
Handle API errors

Sampling Parameters & Output Control5

Understand temperature
Use top-p sampling
Implement determinism
Control output length
Use structured output

Multi-Provider & Prompt Engineering5

Build provider abstraction
Structure conversations
Use few-shot prompting
Implement chain-of-thought
Build prompt templates

Function Calling Fundamentals5

Understand tool use concept
Define tool schemas
Make function calls
Handle tool responses
Compare provider patterns

Embeddings & Semantic Search5

Understand embeddings
Generate embeddings
Calculate similarity
Build simple search
Compare embedding models

RAG Fundamentals5

Understand RAG pattern
Chunk documents
Build retrieval pipeline
Compose RAG prompts
Evaluate RAG quality

Cost Awareness & Token Economics5

Understand pricing models
Calculate request costs
Compare provider costs
Identify cost drivers
Basic cost optimization

Retry Patterns with Tenacity5

Understand retry need
Use tenacity basics
Implement exponential backoff
Handle specific exceptions
Combine with async

Kubernetes Essentials for GenAI663.5%

Containerizing LLM Applications6

Write a Python app that calls the Gemini API and returns structured responses
Write a Dockerfile and build a container image for the LLM app
Run the containerized LLM app with environment-based configuration
Use Docker Compose to run the LLM app with supporting services
Tag images with semantic versions and push to a container registry
Debug containers with exec, logs, and inspect

Your Kubernetes Cluster & First LLM Pod6

Understand K8s architecture and connect to your vCluster
Deploy the LLM app as your first Kubernetes pod
Organize workloads with namespaces
Use labels and selectors to organize and query resources
Understand pod lifecycle and restart policies
Master kubectl debugging: exec, logs, describe, port-forward

Services & the LLM Chat Backend6

Create a ClusterIP service to expose the LLM chat API internally
Deploy a multi-tier LLM chat application
Compare service types: ClusterIP, NodePort, LoadBalancer
Master DNS-based service discovery in Kubernetes
Understand endpoints and traffic routing
Debug service connectivity problems

Deployments, Scaling & Rolling Updates6

Create a Deployment for the LLM chat API
Scale LLM app replicas to handle concurrent requests
Perform a rolling update with zero downtime
Roll back a broken deployment
Compare deployment strategies: RollingUpdate vs Recreate
Manage deployment lifecycle with kubectl rollout

ConfigMaps & Secrets for LLM Apps6

Create ConfigMaps for LLM app settings
Mount ConfigMaps as files for complex configuration
Store LLM proxy credentials securely in Secrets
Manage per-environment configuration for dev, staging, and prod
Handle configuration updates and rolling restarts
Debug configuration issues in LLM app pods

Persistent Storage & StatefulSets6

Create PersistentVolumeClaims for durable storage
Deploy PostgreSQL as a StatefulSet
Connect the LLM chat API to PostgreSQL for conversation persistence
Deploy Redis as a StatefulSet for LLM response caching
Understand StatefulSet scaling and ordering guarantees
Manage PVC lifecycle: expansion, snapshots, and cleanup

Resource Management & Cost Optimization6

Set resource requests and limits for the LLM chat API
Understand QoS classes and their impact on eviction
Enforce resource defaults with LimitRanges
Cap namespace resource usage with ResourceQuotas
Right-size LLM app containers based on actual usage
Diagnose OOMKilled and CPU throttling issues

Packaging with Helm & Kustomize6

Create a Helm chart for the LLM chat application
Parameterize the chart with values.yaml for each environment
Manage Helm release lifecycle: install, upgrade, rollback
Use Kustomize bases and overlays for the LLM app
Use Kustomize patches and generators
Compare Helm vs Kustomize for different deployment scenarios

Networking, Ingress & TLS6

Expose the LLM chat API via an Ingress resource
Add TLS to the Ingress for HTTPS access
Isolate services with NetworkPolicies
Configure Ingress annotations for production traffic
Understand K8s networking: pod IPs, CNI, and service routing
Debug networking and connectivity issues

Health Probes, Autoscaling & Self-Healing6

Add liveness and readiness probes to the LLM chat API
Configure startup probes for containers with slow initialization
Scale the chat API automatically with HPA based on CPU
Create PodDisruptionBudgets for safe maintenance
Implement health check patterns for LLM-dependent services
Combine autoscaling, probes, and PDBs for a resilient LLM service

RBAC, Security & K8s Troubleshooting6

Create RBAC roles for the LLM chat application
Enforce Pod Security Standards
Apply SecurityContext for defense in depth
Debug CrashLoopBackOff and OOMKilled failures
Use kubectl debug and ephemeral containers for live debugging
Troubleshoot LLM-specific issues: timeouts, proxy errors, stale connections

Web APIs for GenAI Engineers602.6%

FastAPI Fundamentals6

Create a FastAPI application with path operations
Define Pydantic request and response models
Implement dependency injection for shared resources
Build CRUD endpoints with proper HTTP semantics
Configure OpenAPI documentation with examples
Handle errors with custom exception handlers

Async Python for APIs6

Convert sync endpoints to async with proper await patterns
Implement background tasks for non-blocking operations
Execute concurrent API calls with asyncio.gather
Manage application lifecycle with lifespan handlers
Build async generators for streaming responses
Control concurrency with semaphores and throttling

Database Integration6

Configure SQLAlchemy async engine with connection pooling
Define ORM models with relationships and constraints
Create and manage database migrations with Alembic
Implement repository pattern for data access
Build transactional endpoints with session lifecycle
Implement filtering, sorting, and full-text search

Authentication & Authorization6

Implement user registration with password hashing
Build OAuth2 password flow with JWT tokens
Implement API key authentication for services
Enforce role-based access control with permissions
Build token refresh and revocation
Compose multiple auth strategies into dependencies

Real-time Streaming6

Build SSE endpoint for streaming LLM responses
Implement WebSocket endpoint with connection lifecycle
Build WebSocket connection manager for broadcasting
Handle backpressure and slow clients
Implement heartbeat and automatic reconnection
Build real-time notification system with Redis pub/sub

Resilience Patterns6

Implement rate limiting with Redis sliding window
Build circuit breaker for LLM provider calls
Configure retry logic with tenacity
Isolate critical paths with bulkhead semaphores
Build fallback responses for degraded mode
Combine resilience patterns into middleware stack

API Gateway & Routing6

Build reverse proxy with path-based routing
Implement load balancing across backend instances
Transform requests and responses through the gateway
Aggregate responses from multiple backends
Implement service discovery with health checking
Build gateway authentication and request enrichment

Testing & Documentation6

Write async endpoint tests with httpx.AsyncClient
Build database fixtures with transaction rollback
Mock external services for deterministic tests
Implement contract tests for API consumers
Measure test coverage and set quality gates
Generate rich OpenAPI documentation with examples

API Versioning & Evolution6

Implement URL-based API versioning with routers
Build header-based version negotiation
Manage deprecation with Sunset and Warning headers
Build request and response adapters for version translation
Detect breaking changes automatically
Generate API changelogs from schema diffs

Deployment & Observability6

Build production Docker images with multi-stage builds
Deploy to Kubernetes with health check probes
Instrument endpoints with Prometheus metrics
Implement distributed tracing with OpenTelemetry
Build structured logging with correlation IDs
Create Grafana dashboards for API monitoring

Agent Hosted Models31118.2%

The LLM Client7

OpenAI client setup
Anthropic client setup
Google Gemini client setup
Build a unified LLM client interface
Error handling and provider fallback
Async LLM client patterns
Practical use cases — security, parameters, observability

Token Economics7

Understand tokenization
Count tokens across providers
Cost forecasting and budgeting
Track LLM API usage in production
Implement budget controls
Optimize tokens
Advanced context engineering

Prompt Caching4

Implement Anthropic cache_control
Leverage OpenAI automatic caching
Design cache-friendly prompt architectures
Build cache monitoring systems

The Function Caller7

OpenAI function schemas
Anthropic function schemas
Gemini function schemas
Handle tool call responses
Execute tools safely with Pydantic validation
Handle parallel tool calls
Framework integration with LangGraph

The Tool Definer7

Write clear tool descriptions for LLMs
Define parameter schemas
Use Pydantic for tool schemas
Implement tool decorators
Handle complex parameter types
Validate tool inputs at runtime
Framework tool patterns — LangGraph, CrewAI, OpenAI, Gemini, Anthropic

The Raw Agent Loop7

The core agent while-loop
Manage context as a mutable list
Handle stop sequences
Track iteration limits
Tool execution in the loop
Build a conversation state tracker
Build with LangGraph StateGraph

The Prompt Engineer (Dynamic)6

Master Jinja2 templating for prompts
Implement dynamic few-shot example selection
Enforce Chain-of-Thought reasoning
Structure system prompts with a builder pattern
Inject dynamic context into prompts safely
Build prompt versioning and A/B testing

The ReAct Pattern (Manual)6

Build the Thought-Action generator
Tool execution and observation injection
Complete ReAct agent implementation
Advanced ReAct patterns — validation, retry, confidence
Optimize ReAct performance
Common ReAct pitfalls and solutions

The Planner Pattern7

Plan generation
Step execution
Dynamic replanning
Hierarchical planning
Plan optimization
Monitoring and observability
Practical considerations — strategy selection

The Pydantic Tool7

Pydantic fundamentals for tool definitions
Generate JSON Schema from Pydantic models
Input validation with custom validators
Build a Pydantic tool library
Advanced Pydantic patterns
Integrate Pydantic tools with agent frameworks
Common pitfalls and solutions

The Safe Executor (Sandboxing)5

Understand code execution risks
Static code analysis
Sandboxed execution
Apply resource limits
Build a complete safe executor

The Web Navigator5

Web navigation fundamentals
Web navigation tools — locating elements and forms
Browser automation with Playwright
Session management
Complete web navigator system

The MCP Protocol (Basics)4

JSON-RPC 2.0 message format and handler
Transport mechanisms — stdio and HTTP/SSE
Protocol lifecycle — initialization, runtime, shutdown
Capability negotiation

The MCP Server6

Create an MCP server with lifecycle management
Define MCP tools
Implement MCP resources
Create prompt templates
Error handling in MCP servers
Composable MCP server architecture

The MCP Client6

MCP client architecture and stdio transport
Discover available tools and translate schemas
Proxy tool invocation
Fetch and use MCP resources
Manage MCP server lifecycle
Build multi-server MCP clients

The Tool Router5

Tool routing architecture and implementation
Namespace-based routing
Capability-based routing
Fallback chains
Routing performance optimization

Short-Term Memory8

Sliding window memory
Token-aware memory management
Message summarization strategies
Memory persistence layers
Memory retrieval optimization
Integrate memory with agents
Memory performance considerations
Non-functional requirements (privacy + safety)

Long-Term Memory (RAG)6

Document chunking strategies
Embedding pipelines
Vector database integration
Hybrid search implementation
Retrieval optimization
RAG response generation

Agentic RAG Patterns5

Self-reflective RAG
Multi-hop retrieval
Query routing
Adaptive retrieval
Retrieval feedback loops

Semantic Memory6

Knowledge extraction pipelines
Entity and relationship extraction
Knowledge graph construction
Memory consolidation
Integrate semantic memory with agents
Build semantic memory with LangGraph

Context Optimizer6

Context economics
Dynamic context prioritization
Context compression techniques
Prompt optimization
Context utilization metrics
Complete context optimizer

The State Graph5

StateGraph fundamentals — config and lifecycle
Design state schemas with TypedDict
Add nodes to StateGraph
State initialization patterns
Tracing, debugging, validation

The Conditional Edge5

Understand conditional edges
Design routing functions
Fan-out and fan-in patterns
Handle unknown routes and errors
Multi-stage routing

The Checkpointer (Time Travel)4

Resumable workflows
Inspect, replay, and time-travel
Retention, large state, and performance
Thread management — IDs and namespaces

Human-in-the-Loop6

LangGraph interrupt patterns
Approval workflow patterns
Interactive agent conversations
Feedback integration
State management for HITL
Practical use cases — escalation and analytics

The Streaming Agent6

Streaming modes in LangGraph
Token streaming from LLMs
Custom events with `astream_events`
Build streaming APIs
Error handling in streams
Backpressure and flow control

The Subgraph (Composition)7

Subgraph fundamentals — compile + test in isolation
State schema mapping
Subgraph checkpointers + namespace isolation
Compose subgraphs into a parent
Catch subgraph exceptions and recover
Define subgraph interfaces and build a registry
Build a multi-agent orchestrator

The Supervisor Pattern7

Design supervisor architectures
Worker agent specialization
Build the complete supervisor graph
Manage inter-agent communication
Handle failures and edge cases
Implement task aggregation
Build the supervisor pattern with CrewAI

The Hierarchical Pattern4

Design hierarchical agent architectures
Implement team-lead agents
Build cross-team coordination
Build the complete hierarchical graph

The Reflector Pattern (Critique)6

Design reflection architectures
Implement critic agents
Build the evaluation and convergence system
Build the complete reflection graph
Handle reflection edge cases
Practical use cases for reflection

Input Guardrails6

Design layered guardrail architectures
Format and schema validation
Build content filtering systems
Create injection / jailbreak detection
Implement policy-based guardrails
Assemble the complete guardrail system

Output Guardrails6

Design output validation architectures
Implement factual validation (hallucination detection)
Build content safety filters
Create PII redaction
Implement policy compliance
Assemble the complete output guardrail system

Prompt Injection Defense7

Identify injection vulnerabilities
Detect direct injections
Detect indirect injections
Implement defense layers
Build red-team suites
Implement canary tokens
LangGraph injection defense pipeline

Evaluations (Evals)6

Design evaluation frameworks
Implement automated evaluation pipelines
Create task-specific metrics
Human evaluation protocols
Regression testing
Set baselines and track progress

Agent Benchmarking6

Understand the GAIA benchmark
Implement ToolBench evaluation
Use AgentBench
Design domain-specific benchmarks
Cross-model performance comparison
Build benchmark dashboards

Tracing & Observability6

Understand distributed tracing
Add tags and metadata
Context propagation
Build feedback collection
Integrate with Langfuse
Trace visualization

Tool Use Debugging6

Tool selection failures and solutions
Argument validation systems
Build tool use dashboards and visualization
Schema mismatch detection
Tool call replay
Interactive tool debugger

Serving Agents (FastAPI)7

Async endpoints, request validation, error handling
Server-Sent Events (SSE) streaming
Background tasks
Design request and response schemas
Authentication — API keys, middleware, errors
OpenAPI metadata and documentation
FastAPI + LangGraph + uvicorn deployment

Podman & Containerization for K8s5

Build optimized container images
Container health checks
Advanced image optimization
Security best practices
Build multi-container agent pods

Production Databases (Postgres/Redis)6

Async PostgreSQL configuration
Connection pool management
Redis caching for LLM responses
Database migrations for agent stacks
Backup and disaster recovery
Monitoring database health

Scaling & Load Balancing7

Stateless service design
Session externalization
Load balancing algorithms
Scaling metrics for LLM workloads
Horizontal Pod Autoscaler configuration
Load testing your scaling design
Rate limiting at the load balancer

Multi-Tenant Agents6

Tenant context middleware
Database-level tenant isolation
Tenant-specific rate limiting and quotas
Per-tenant configuration templates
Usage metering for billing and SLA
Enforcing tenant data segregation at the API

Kubernetes (K8s) Basics8

Creating Kubernetes Deployments
Resource management for LLM workloads
Kubernetes Services
ConfigMaps and Secrets
Rolling updates and CronJobs
Cluster planning and scheduling
Deployment planning synthesis
NetworkPolicies and prompt-injection defense at the edge

CI/CD for Agents7

GitHub Actions for agent testing
Agent evaluation scripts in CI
Kubernetes deployment pipeline
GitOps deployment pattern
Quality gates and pipeline optimization
Rollback mechanisms
Pipeline observability and notifications

Monitoring & Alerting7

Prometheus metrics for agents
Grafana dashboards
Alerting configuration
SLOs and SLIs
Runbook creation for agent incidents
Tracking business KPIs for agent platforms
Agent-specific monitoring patterns (RED, USE, golden signals)

Model Routing & Fallbacks7

Cost-optimized routing
Latency-optimized routing
Building the resilient LLM client
Provider health checking
Cost tracking and optimization
Capability-based routing
Multi-model routing inside LangGraph

Long-Running Agents7

Cross-session persistence
Checkpoint serialization
Workflow resumption
Task queue integration with Celery
Progress tracking and SSE streaming
Timeout handling and graceful shutdown
Long-running agents with CrewAI — synthesis

Production Architecture Patterns7

System components, interfaces, and integration points
Cost modeling and projection
Production checklists and audit
Architecture Decision Records (ADRs)
Disaster recovery planning
System component diagrams
Architecture pattern evaluation — synthesis

Alternative Frameworks (CrewAI/AutoGen)6

CrewAI core concepts and agent personas
AutoGen conversational architecture
Framework comparison and integration patterns
Framework migration strategies and validation
Hybrid multi-framework systems
Picking a framework for a real use case

Deep Memory (GraphRAG)7

Knowledge graph fundamentals
Graph traversal patterns
Entity extraction with LLMs
Hybrid retrieval strategies (vector + graph)
Entity resolution and de-duplication
Incremental graph updates and provenance
Graph export, embeddings, and summarization

Agent Swarms & Collaboration4

Swarm architecture patterns
Agent communication and pub/sub
Consensus and weighted voting
Emergent behavior and stigmergy

Enterprise LLM Customization24021.9%

Enterprise Data Pipeline6

Build DataPipeline with Instructor
Implement distillation data generation
Build a data quality dashboard
Build a data validation pipeline
Optimize data pipeline throughput
Build a data lineage tracker

Synthetic Data Factory6

Build SyntheticFactory with DSPy
Use OpenAI Batch API for bulk generation
Filter and validate synthetic data
Build synthetic data quality evaluator
Optimize Batch API cost and throughput
Build synthetic data versioning

Fine-Tuned Enterprise Model6

Fine-tune with OpenAI
Tune with Vertex AI
Build model comparison framework
Build fine-tuning hyperparameter search
Implement model distillation pipeline
Build model comparison report generator

RLVR-Trained Reasoning Model6

Build programmatic graders
Train via RFT API
Analyze training dynamics
Build grader reliability testing
Optimize RFT training cost
Build training run monitoring dashboard

Reward Engineering Toolkit6

Build composite reward functions
Build LLM-as-judge graders
Validate grader reliability with Promptfoo
Build reward function A/B testing
Optimize composite reward weighting
Build reward engineering documentation generator

Model Eval Dashboard6

Configure Promptfoo eval suites
Use Batch API for bulk eval
Build regression detection
Build eval suite versioning and management
Optimize eval pipeline cost with sampling
Build eval regression root cause analyzer

Model Selection Engine6

Build ModelSelector
Build cost-quality optimizer
Benchmark HuggingFace open models
Build model selection test harness
Optimize model selection latency
Build model catalog and recommendation engine

Reasoning Model Benchmark6

Benchmark reasoning across providers
Analyze reasoning patterns
Build task-specific reasoning profiles
Build testing and validation for reasoning model benchmark
Optimize performance for reasoning model benchmark
Build operational runbook for reasoning model benchmark

TTC Controller6

Build TTC scaling curves
Implement compute-aware routing
Build TTC cost savings dashboard
Build testing and validation for ttc controller
Optimize performance for ttc controller
Build operational runbook for ttc controller

Best-of-N Inference Engine6

Build BestOfN engine
Optimize N and cost tradeoff
Build BestOfN + RLVR hybrid strategy
Build testing and validation for best-of-n inference engine
Optimize performance for best-of-n inference engine
Build operational runbook for best-of-n inference engine

Self-Refining Agent6

Build SelfRefiner
Implement long-horizon planning
Build refinement convergence analysis
Build testing and validation for self-refining agent
Optimize performance for self-refining agent
Build operational runbook for self-refining agent

Compute-Optimal Router6

Build ComputeRouter
Evaluate routing performance
Build routing feedback loop with learning
Build testing and validation for compute-optimal router
Optimize performance for compute-optimal router
Build operational runbook for compute-optimal router

DSPy Enterprise Modules6

Build 5 enterprise DSPy modules
Compare DSPy vs hand-written
Test DSPy modules with Promptfoo
Build testing and validation for dspy enterprise modules
Optimize performance for dspy enterprise modules
Build operational runbook for dspy enterprise modules

DSPy Optimizer as Meta-RL6

Run MIPROv2 optimization
Analyze optimization dynamics
Compare cross-provider optimization
Build testing and validation for dspy optimizer as meta-rl
Optimize performance for dspy optimizer as meta-rl
Build operational runbook for dspy optimizer as meta-rl

DSPy + Skills Pipelines6

Build multi-stage pipeline
Test pipeline reliability
Build pipeline monitoring and alerting
Build testing and validation for dspy + skills pipelines
Optimize performance for dspy + skills pipelines
Build operational runbook for dspy + skills pipelines

Structured Extraction with Citations6

Build CitedExtractor
Validate extraction with Promptfoo
Compare multi-provider extraction
Build testing and validation for structured extraction with citations
Optimize performance for structured extraction with citations
Build operational runbook for structured extraction with citations

LiteLLM Gateway6

Deploy LiteLLM proxy
Implement failover and circuit breakers
Load test and capacity plan
Build testing and validation for litellm gateway
Optimize performance for litellm gateway
Build operational runbook for litellm gateway

Smart Router6

Build intelligent routing
Implement context caching
Build routing analytics dashboard
Build testing and validation for smart router
Optimize performance for smart router
Build operational runbook for smart router

Provider Caching Comparison6

Implement all caching systems
Build caching strategy recommender
Build cache invalidation and consistency
Build testing and validation for provider caching comparison
Optimize performance for provider caching comparison
Build operational runbook for provider caching comparison

FinOps Controller6

Build budget and spend tracking
Auto-route to Batch API
Build cost anomaly detection
Build testing and validation for finops controller
Optimize performance for finops controller
Build operational runbook for finops controller

Langfuse Observability6

Deploy and integrate Langfuse
Build drift detection and alerts
Build custom eval pipelines in Langfuse
Build testing and validation for langfuse observability
Optimize performance for langfuse observability
Build operational runbook for langfuse observability

A/B Testing + Prompt CI/CD6

Build prompt CI/CD pipeline
Build model deployment lifecycle
Build multi-environment promotion pipeline
Build testing and validation for a/b testing + prompt ci/cd
Optimize performance for a/b testing + prompt ci/cd
Build operational runbook for a/b testing + prompt ci/cd

Agent Mesh: A2A + ADK6

Build A2A agent mesh
Build AI governance framework
Build agent mesh observability dashboard
Build testing and validation for agent mesh: a2a + adk
Optimize performance for agent mesh: a2a + adk
Build operational runbook for agent mesh: a2a + adk

Guardrails Pipeline6

Build guardrails pipeline
Test guardrails under adversarial input
Benchmark guardrail performance
Build security testing for guardrails pipeline
Optimize throughput for guardrails pipeline
Build compliance reporting for guardrails pipeline

Prompt Injection Red Team6

Run OWASP LLM Top 10 attacks
Build security assessment report
Build automated security regression pipeline
Build security testing for prompt injection red team
Optimize throughput for prompt injection red team
Build compliance reporting for prompt injection red team

Data Classification Router6

Build DataClassifier
Integrate DLP controls
Build data lineage tracking
Build security testing for data classification router
Optimize throughput for data classification router
Build compliance reporting for data classification router

Compliance Audit Trail6

Build audit logging system
Build compliance reporting
Build audit data retention and archival
Build security testing for compliance audit trail
Optimize throughput for compliance audit trail
Build compliance reporting for compliance audit trail

Compliance Test Suite6

Build regulatory compliance tests
Build bias and fairness tests
Build continuous compliance monitoring
Build security testing for compliance test suite
Optimize throughput for compliance test suite
Build compliance reporting for compliance test suite

Production RAG Pipeline6

Build EnterpriseRAGPipeline
Build RAGEvaluator with RAGAS
Build HybridRetriever with reranking
Build testing and evaluation for production rag pipeline
Optimize performance for production rag pipeline
Build operational monitoring for production rag pipeline

Vector Database Engineering6

Build VectorDBBenchmark
Build MultiIndexManager
Build EmbeddingOptimizer
Build testing and evaluation for vector database engineering
Optimize performance for vector database engineering
Build operational monitoring for vector database engineering

LangGraph Agentic Orchestration6

Build LangGraphAgent with stateful workflows
Build OrchestrationComparator
Build LangGraphRAGAgent
Build testing and evaluation for langgraph agentic orchestration
Optimize performance for langgraph agentic orchestration
Build operational monitoring for langgraph agentic orchestration

GraphRAG & Knowledge Graphs6

Build KnowledgeGraphBuilder
Build GraphRAGRetriever
Build HybridKnowledgeSearch
Build testing and evaluation for graphrag & knowledge graphs
Optimize performance for graphrag & knowledge graphs
Build operational monitoring for graphrag & knowledge graphs

Agent Memory & Stateful Systems6

Build AgentMemorySystem
Build MemoryManager
Build StatefulAgentBenchmark
Build testing and evaluation for agent memory & stateful systems
Optimize performance for agent memory & stateful systems
Build operational monitoring for agent memory & stateful systems

Advanced RAG Patterns6

Build AdaptiveRAG
Build RAGCIPipeline
Build ProductionRAGDashboard
Build testing and evaluation for advanced rag patterns
Optimize performance for advanced rag patterns
Build operational monitoring for advanced rag patterns

Healthcare: Clinical Advisor6

Build clinical advisory pipeline
Implement HIPAA compliance
Build clinical accuracy validation
Build end-to-end testing for healthcare: clinical advisor
Optimize cost and performance for healthcare: clinical advisor
Build production operations for healthcare: clinical advisor

Finance: Deal Analyzer6

Build deal analysis pipeline
Build FinOps controls
Build cross-department usage analytics
Build end-to-end testing for finance: deal analyzer
Optimize cost and performance for finance: deal analyzer
Build production operations for finance: deal analyzer

Legal: Regulatory Monitor6

Build regulatory monitoring mesh
Validate legal accuracy
Build regulatory change impact scoring
Build end-to-end testing for legal: regulatory monitor
Optimize cost and performance for legal: regulatory monitor
Build production operations for legal: regulatory monitor

Customer Ops: Resolution6

Build customer resolution system
Security and observability
Build resolution quality feedback loop
Build end-to-end testing for customer ops: resolution
Optimize cost and performance for customer ops: resolution
Build production operations for customer ops: resolution

Multimodal Enterprise6

Build multimodal processor
Validate multimodal accuracy
Build document type router with fallbacks
Build end-to-end testing for multimodal enterprise
Optimize cost and performance for multimodal enterprise
Build production operations for multimodal enterprise

Capstone: Enterprise AI Platform6

Build enterprise AI platform
Run production readiness assessment
Build disaster recovery and runbook
Build end-to-end testing for capstone: enterprise ai platform
Optimize cost and performance for capstone: enterprise ai platform
Build production operations for capstone: enterprise ai platform

GenAI Operations10211.9%

GenAI SLI Framework6

Define latency SLIs: TTFT, tokens-per-second, end-to-end response time across providers
Define quality SLIs: faithfulness, hallucination rate, format compliance, retrieval precision
Define cost SLIs: cost-per-request, cost-per-token, cache hit rate, budget burn rate
Instrument all SLIs with Prometheus metrics and Langfuse traces
Build SLI aggregation and reporting API
Implement SLI validation and testing

GenAI SLO Engine6

Define SLO targets for latency, quality, and cost SLIs with business-justified thresholds
Compute error budgets and track consumption over rolling windows
Build multi-window burn-rate alerts that detect SLO violations before budget exhaustion
Create SLO status dashboards showing budget remaining and projected exhaustion
Implement SLO negotiation framework
Build cross-SLO dependency tracking

GenAI Launch Readiness6

Define operational readiness criteria specific to GenAI services
Build automated readiness checks that verify infrastructure, monitoring, and runbook completeness
Implement launch gate enforcement that blocks deployment without readiness sign-off
Create readiness dashboards and historical tracking for continuous improvement
Implement progressive readiness rollout
Create readiness automation toolkit

AI Incident Commander6

Define LLM-specific incident severity classification with impact-based criteria
Build incident lifecycle management with role assignments and status tracking
Create communication templates for AI-specific incidents targeting different audiences
Track incident metrics with MTTD, MTTA, MTTR and trend analysis
Implement performance optimization for llm incident response framework
Build operational documentation for llm incident response framework

Runbook Automation Engine6

Build alert-to-runbook routing that triggers automated remediation workflows
Implement human approval gates for high-impact remediation steps
Create runbook execution auditing with step-by-step logging and outcome tracking
Track automation coverage and success rates across all runbook types
Implement performance optimization for automated runbook execution
Build operational documentation for automated runbook execution

AI Post-Mortem Engine6

Build structured post-mortem templates for GenAI failure modes
Implement timeline reconstruction from Langfuse traces and Prometheus metrics
Create action item tracking with follow-through verification
Analyze post-mortem trends to identify systemic issues
Implement performance optimization for post-mortems for ai failures
Build operational documentation for post-mortems for ai failures

Cost Attribution Engine6

Instrument per-request cost tracking across all pipeline stages
Build cost attribution to teams, projects, and use cases
Create cost allocation models for shared infrastructure components
Implement cost anomaly detection with automated investigation
Implement performance optimization for full-stack cost attribution
Build operational documentation for full-stack cost attribution

Token Budget Controller6

Configure LiteLLM Virtual Keys with Per-Team Budget Limits
Implement Per-Request Token Limits
Build Budget Alerting at 50%, 80%, and 100% Thresholds with Escalation
Create Budget Override Workflows for Emergency Usage Beyond Limits
Implement performance optimization for token budget enforcement
Build operational documentation for token budget enforcement

Cache Economics Analyzer6

Deploy Redis Semantic Cache and Measure Hit Rate vs Cost Savings
Compare Provider Caching Strategies for OpenAI, Anthropic, and Google
Build Cost-Benefit Analysis with Break-Even Calculations
Recommend Optimal Caching Mix Per Use Case
Implement performance optimization for caching roi analysis
Build operational documentation for caching roi analysis

Batch API Scheduler6

Implement workload classification: real-time vs batch-eligible based on latency requirements
Build Batch API job scheduling with priority queues and SLA tracking
Create batch job monitoring with completion time SLAs and failure handling
Measure and report cost savings from batch routing vs synchronous requests
Implement performance optimization for batch api optimization
Build operational documentation for batch api optimization

Capacity Forecaster6

Build token demand forecasting using historical usage patterns and trend analysis
Implement embedding volume projection for storage and compute planning
Create cost projection models for budget planning cycles
Track forecast accuracy and improve models over time with feedback loops
Implement performance optimization for capacity forecasting
Build operational documentation for capacity forecasting

FinOps Governance Platform6

Build Showback and Chargeback Reports per Team and Project with Full Cost Transparency
Create Executive FinOps Dashboards with Trend Analysis for Leadership
Implement Cost Governance Policies with Automated Enforcement
Generate Monthly FinOps Reviews with Optimization Recommendations
Implement performance optimization for finops reporting and governance
Build operational documentation for finops reporting and governance

Multi-Tenant GenAI Platform6

Automate tenant onboarding with namespace provisioning and secret management
Implement namespace isolation with network policies and resource quotas
Build noisy-neighbor detection that identifies tenants causing resource contention
Create tenant operations dashboards with per-tenant health visibility
Implement performance optimization for multi-tenant platform operations
Build operational documentation for multi-tenant platform operations

AI Developer Platform6

Build self-service deployment workflows with approval gates for AI artifacts
Create golden path templates for common GenAI patterns
Implement internal tool marketplace for reusable AI components
Build developer experience metrics and platform analytics
Implement performance optimization for internal developer platform for ai
Build operational documentation for internal developer platform for ai

GenAI Ops Maturity Assessor6

Define GenAI operational maturity model with five levels across eight capability areas
Build automated maturity assessment that evaluates current operational state
Generate improvement roadmaps with prioritized actions based on assessment results
Track maturity progression over time with milestone tracking
Implement performance optimization for operational maturity model
Build operational documentation for operational maturity model

AI Incident Response6

AI Incident Taxonomy
Automated Detection
AI Incident Runbooks
Post-Incident Review
Escalation Path Design
Incident Response Capstone

AI Governance Compliance Ops6

EU AI Act Controls
NIST AI RMF Implementation
SOC2 AI Controls
Compliance Dashboard
Audit Preparation Workflow
Compliance Ops Capstone

GenAI Architecture Design Patterns15628.9%

GenAI ADR Engine6

Build ADR schema and decision taxonomy for GenAI technology choices
Implement multi-provider model selection ADR workflow
Validate ADR decisions against production telemetry
Build ADR dependency graph across system decisions
Implement ADR recommendation engine using historical outcomes
Create ADR governance dashboard and compliance audit

Reference Architecture Registry6

Build reference architecture schema with C4 model layers
Catalog five canonical GenAI reference architectures
Validate architecture blueprints against quality fitness functions
Build architecture pattern matching for requirements-to-blueprint selection
Implement architecture evolution planner for incremental migration
Create architecture registry dashboard with adoption tracking

Compound AI System Designer6

Build compound AI system topology modeler
Implement cascade routing with cost-aware model selection
Validate compound system against end-to-end quality requirements
Model failure propagation and blast radius in compound systems
Optimize compound system for cost-quality Pareto frontier
Create compound system architecture review checklist and report

Eval-First Architecture Engine6

Build eval gate component with pluggable evaluator registry
Integrate eval gates into retrieval, generation, and agent pipelines
Measure eval gate effectiveness with precision-recall tracking
Build eval cascade with tiered evaluation depth
Optimize eval gate latency overhead with async and sampling strategies
Create eval architecture audit report with coverage analysis

Cost-Optimized AI Router6

Build cost-aware request router with tiered model cascade
Implement semantic caching architecture with cache-aside pattern
Measure cost savings and quality impact per optimization strategy
Build token budget enforcement with per-tenant and per-request limits
Optimize batch processing architecture for non-real-time workloads
Create cost architecture review and FinOps governance report

AI Traffic Gateway6

Build AI-aware API gateway with provider-specific routing rules
Implement Istio service mesh for AI microservice communication
Measure gateway latency overhead and optimize hot paths
Build intelligent rate limiting with token-aware throttling
Implement circuit breaker and bulkhead patterns for provider isolation
Create gateway operations dashboard with traffic topology view

Streaming AI Pipeline6

Build streaming response pipeline with SSE as default transport
Implement streaming-aware guardrails that evaluate partial output
Measure streaming quality metrics including TTFT and token throughput
Build event-driven pipeline for streaming data transformation
Optimize streaming architecture for connection efficiency and recovery
Create streaming architecture health dashboard and SLA report

Cell-Based AI Platform6

Build cell definition schema with namespace isolation on GKE Autopilot
Implement traffic routing between cells for canary and shadow deployments
Validate cell isolation with blast radius testing
Build feature-flag-driven model rollout across cells
Optimize cell resource allocation with autoscaling policies
Create cell operations dashboard with fleet-wide topology view

AI Observability Stack6

Build OpenTelemetry instrumentation for multi-step AI pipelines
Implement AI-specific metrics collection with quality dimensions
Validate trace completeness and data quality across the pipeline
Build cross-signal correlation linking traces to quality degradation
Optimize observability cost with intelligent data reduction
Create observability architecture assessment and maturity dashboard

Layered AI Security System6

Build layered guardrail pipeline with pluggable security stages
Integrate NeMo Guardrails and LlamaFirewall for multi-layer defense
Measure guardrail effectiveness with red-team evaluation metrics
Build security event correlation across guardrail layers
Optimize guardrail latency with tiered security evaluation
Create security architecture audit report with compliance mapping

MCP Tool Mesh6

Build MCP server registry with capability discovery and health checks
Implement MCP authorization layer with per-tool permission policies
Validate MCP tool composition correctness and safety
Build MCP tool routing with load balancing and failover
Optimize MCP tool selection with intelligent pre-filtering
Create MCP ecosystem governance dashboard

A2A Agent Network6

Build A2A agent card registry with capability advertisement
Implement A2A task delegation with streaming artifact exchange
Validate A2A communication reliability with failure injection
Build A2A agent trust and authorization framework
Optimize A2A network topology for latency and reliability
Create A2A network operations dashboard with federation view

Event-Driven AI Processor6

Build event schema registry for GenAI domain events
Implement event backbone with Redis Streams for AI workloads
Validate event pipeline reliability with exactly-once semantics
Build event-sourced audit trail for AI decision traceability
Optimize event pipeline throughput with partitioning and batching
Create event architecture topology dashboard and maturity report

Multi-Modal AI Pipeline6

Build multi-modal request router with modality detection
Implement vision-language pipeline with document understanding
Validate multi-modal output quality with per-modality evaluators
Build modality-specific caching and preprocessing optimization
Optimize multi-modal pipeline for latency with parallel processing
Create multi-modal architecture capability assessment

Enterprise RAG System6

Build hybrid retrieval pipeline combining dense, sparse, and graph search
Implement multi-index federation with routing by query intent
Validate retrieval quality with RAGAS metrics and human evaluation
Build real-time document ingestion with incremental index updates
Optimize retrieval latency with query planning and result caching
Create RAG architecture health dashboard and capacity report

Agent Orchestration Platform6

Build agent pool manager with lifecycle and capability registration
Implement supervisor hierarchy with delegation and escalation policies
Validate orchestration correctness with agent trajectory evaluation
Build task queue with priority scheduling and resource-aware dispatch
Optimize orchestration for cost with agent budget management
Create agent orchestration operations dashboard

AI Developer Platform6

Build Backstage service catalog for AI components
Implement golden path templates for AI service creation
Validate platform compliance with automated standards checking
Build self-service AI environment provisioning pipeline
Optimize developer experience with platform usage analytics
Create platform engineering maturity assessment dashboard

Provider Reliability Engine6

Build provider health tracker with real-time status aggregation
Implement intelligent failover with quality-preserving model mapping
Validate failover behavior with chaos engineering experiments
Build shadow deployment for cross-provider model comparison
Optimize provider selection with cost-quality-latency Pareto routing
Create provider reliability SLA report and vendor risk assessment

Context Engineering Platform6

Build context composition engine with priority-ranked information sources
Implement context compression with summarization and pruning strategies
Validate context quality impact on generation accuracy
Build context caching with freshness-aware invalidation
Optimize context utilization with dynamic window sizing
Create context architecture audit report with optimization roadmap

AI Data Architecture6

Build unified data access layer across vector, graph, and relational stores
Implement schema evolution strategy for embedding and knowledge data
Validate data consistency across stores with reconciliation checks
Build data lifecycle manager with retention and archival policies
Optimize data access patterns with caching and pre-computation
Create data architecture health report with capacity planning

Enterprise AI Integration Hub6

Build integration adapter framework with standardized connector interface
Implement data transformation pipeline between enterprise and AI formats
Validate integration correctness with contract testing
Build integration error handling with dead letter and retry strategies
Optimize integration throughput with batching and parallel processing
Create enterprise integration architecture map and health report

AI Governance Platform6

Build data classification engine for AI input and output streams
Implement model usage policy engine with approval workflows
Validate compliance coverage with automated control testing
Build comprehensive audit trail with immutable event logging
Optimize compliance overhead with risk-based control depth
Create regulatory compliance report generator for SOC2 and GDPR

HA/DR AI Platform6

Build HA topology planner with single-point-of-failure analysis
Implement stateful failover for conversation and embedding stores
Validate DR procedures with automated failover testing
Build automated DR runbook with step-by-step failover execution
Optimize recovery speed with pre-staged failover resources
Create HA/DR architecture dashboard with readiness assessment

Multi-Tenant AI Platform6

Build tenant isolation framework with namespace and network boundaries
Implement tenant-aware routing with per-tenant model and guardrail config
Validate tenant isolation with cross-tenant data leakage testing
Build per-tenant cost management with budget enforcement
Optimize tenant resource sharing with noisy-neighbor prevention
Create multi-tenant platform operations dashboard

Architecture Review Engine6

Build architecture review checklist engine with domain-specific criteria
Implement technology selection framework with multi-criteria scoring
Validate review coverage with architecture surface area mapping
Build review knowledge base from historical architecture decisions
Optimize review process with risk-based prioritization
Create architecture governance report for leadership

Production AI Platform Capstone6

Design complete platform architecture with C4 model documentation
Implement architecture prototype with compound AI pipeline
Validate platform against quality, security, and reliability requirements
Build platform cost model with total cost of ownership projection
Conduct architecture review applying all course frameworks
Generate architecture handoff package for solution delivery team

GenAI Eval Safety Governance121.9%

EU AI Act Compliance6

Classify AI systems under EU AI Act risk categories
Implement the Feb 2025 AI literacy requirements
Build technical documentation for GPAI compliance
Implement risk management system
Build human oversight mechanisms
Track EU AI Act enforcement timeline compliance

Compliance Frameworks6

Implement NIST AI RMF Govern and Map functions
Implement NIST AI RMF Measure and Manage functions
Build ISO 42001 AI management system documentation
Create unified governance dashboard with Credo AI Agent Registry
Implement comprehensive audit trail
Build compliance automation and alerting

AI Solution Delivery607.5%

AI Use Case Discovery & Data Readiness Assessment5

Score AI use cases with weighted multi-criteria evaluation
Profile customer datasets for quality and PII exposure
Run LLM-driven discovery interviews with LangGraph state
Benchmark provider feasibility across OpenAI, Gemini, Anthropic
Generate executive discovery reports from structured assessment data

Solution Scoping & Effort Estimation5

Decompose AI projects into a hierarchical work breakdown structure
Classify project risks with DSPy-optimized prompts
Detect scope drift via embedding similarity
Plan resource allocation with constraint-based scheduling
Assemble versioned scope documents with diff tracking

SOW & Proposal Generation5

Generate milestone schedules with critical-path analysis
Extract SMART acceptance criteria from raw requirements
Estimate AI project pricing across tokens, infra, and labor
Generate full SOW proposals with LangGraph workflows
Detect risky contract language with NeMo Guardrails

Rapid AI Prototyping5

Build a RAG prototype with pgvector retrieval
Prototype LangGraph agents with MCP tools and human approval
Compare providers side-by-side with LiteLLM showcase
Score prototype demo readiness with RAGAS and LLM-as-judge
Package prototypes with Dockerfiles, Helm charts, and K8s manifests

Customer Data Integration Pipelines5

Build pluggable data connectors for SQL, REST, files, and S3
Map customer schemas to target schemas with LLM-assisted suggestions
Detect and redact PII with Presidio and LlamaGuard 4
Embed documents incrementally with content-hash dedup
Monitor data quality with OTEL throughput and precision metrics

Deploying in Customer Environments5

Generate K8s manifests from customer-parameterized Jinja2 templates
Manage K8s secrets with rotation and init-container injection
Enforce service isolation with K8s NetworkPolicy
Validate deployments with probe checks and inference smoke tests
Log compliance events as OTEL traces with structured attributes

Stakeholder Communication & Demo Engineering5

Orchestrate scripted demos with fallback scenarios
Generate technical review reports from live system data
Translate technical reports into executive briefings
Collect stakeholder feedback with sentiment analysis
Provision isolated K8s demo environments with TTL teardown

Delivery Risk Management & Governance5

Track risks in a CRUD register with LLM-enriched descriptions
Detect scope drift with embedding similarity classification
Monitor delivery health from standup notes and velocity data
Enforce governance gates with LLM-as-judge evaluation
Automate escalations with threshold-based webhooks

POC to Production Hardening5

Layer guardrails with NeMo and LlamaFirewall PromptGuard 2
Load-test LLM endpoints with Locust and SSE stream validation
Deploy with blue-green Helm charts and atomic service switching
Validate production readiness against OWASP LLM Top 10
Auto-rollback on quality regression with RAGAS monitoring

Knowledge Transfer & Training Automation5

Generate API docs and Mermaid diagrams from source code
Generate runbooks from K8s configs with LangGraph workflows
Generate training quizzes with DSPy-optimized prompts
Search a knowledge base semantically with source attribution
Score handoff readiness from quiz, runbook, and coverage signals

Post-Delivery Support & SLA Monitoring5

Track SLAs with multi-category threshold breach detection
Detect quality anomalies with OTEL sliding-window analysis
Run incident response pipelines with severity classification
Schedule maintenance from quality degradation signals
Aggregate support analytics with MTTR and cost-per-resolution

Delivery Capstone — End-to-End AI Engagement5

Orchestrate end-to-end delivery with LangGraph state
Coordinate a multi-agent delivery team with Google ADK and A2A
Validate phase transitions with quality gate pipelines
Extract retrospective lessons with Instructor and Anthropic
Track multi-engagement portfolios with health scoring

GenAI Solutions & Delivery

Verifiable skill graph

What you'll ship in production

Lead end-to-end GenAI project delivery

Design GenAI architecture

Build agent-based solutions

Customize enterprise LLM deployments

Manage FinOps

Scope project timelines and team requirements

Package solutions as deployable artifacts

Advise clients on technology roadmaps

Curriculum