Coverage Roadmap

GenAI Coverage Roadmap

This map shows the documentation scope this hub is aiming for: what is already covered well, what is only partially covered today, and which GenAI and agent topics should be added next.

Covered28

Substantive content already exists in the hub.

Partial0

Covered indirectly, but still missing dedicated depth.

Planned0

Identified as an important topic for future expansion.

Recommended Sequence

Learn this hub in four passes: GenAI foundations first, then application engineering, then agent systems, then production operations. That order reduces confusion and makes later agent topics much easier to understand.

Implementation Backlog

This is the concrete next-work plan for the repo: prioritized chapters, what each chapter should deliver, and the main files that need to change.

Core Expansion Backlog Cleared

The planned core documentation chapters have been completed. Further work can now focus on incremental updates, framework refreshes, or new case studies as the ecosystem changes.

GenAI Foundations

The core mental models every developer should understand before building agents or GenAI applications.

What Are AI Agents?

Covered

Core definitions, the agent loop, and when an agent is the right abstraction.

Open current coverage

Prompt Engineering

Covered

System prompts, tool instructions, output shaping, and prompt anti-patterns.

Open current coverage

Model Selection & Routing

Covered

How to choose models by capability, latency, cost, and reliability, then route workloads between them.

Open current coverage

Structured Outputs

Covered

Schema-first generation, validation, typed results, and constrained output patterns.

Open current coverage

Context Engineering

Covered

How prompts, retrieved context, tool results, and memory should be assembled for each run.

Open current coverage

Multimodal GenAI

Covered

Working with documents, images, audio, and mixed-modal pipelines.

Open current coverage

Application Engineering

The application-layer patterns that turn model calls into useful products and internal systems.

RAG & Agentic RAG

Covered

Retrieval pipelines, corrective retrieval, and agent-driven document interaction.

Open current coverage

Model Context Protocol

Covered

Standardizing tools, resources, and prompts across applications and agents.

Open current coverage

Fine-Tuning vs RAG vs Tools vs Workflows

Covered

A practical decision framework for choosing the right capability layer for a use case.

Open current coverage

Human-in-the-Loop Design

Covered

Approval checkpoints, escalation patterns, and where to keep humans in the control loop.

Open current coverage

GenAI Product UX

Covered

Streaming, partial results, confidence cues, and graceful failure handling in user-facing apps.

Open current coverage

Auth, Tenancy, and Data Boundaries

Covered

RBAC, tenant isolation, secrets handling, and access control for enterprise GenAI systems.

Open current coverage

Agent Systems

The patterns, reasoning strategies, and orchestration approaches used to build capable agentic workflows.

Planning & Reasoning

Covered

Chain-of-thought, ReAct, plan-and-execute, reflection, and tree-based reasoning.

Open current coverage

Design Patterns

Covered

Battle-tested architectures for routing, delegation, collaboration, and tool use.

Open current coverage

Choosing Your Stack

Covered

Framework and runtime tradeoffs across Python, TypeScript, single-agent, and multi-agent systems.

Open current coverage

Workflow Reliability

Covered

Retries, fallback chains, idempotency, compensation logic, and bounded autonomy.

Open current coverage

Computer Use & Browser Automation

Covered

When agents should act through UIs, and the guardrails needed for those systems.

Open current coverage

Agent Evaluation Flywheel

Covered

How agent behavior improves through datasets, regression tests, reviews, and operational feedback.

Open current coverage

Production Operations

The operational capabilities required to run GenAI and agent systems safely, reliably, and cost-effectively.

Guardrails & Safety

Covered

Validation, filtering, approval gates, PII handling, and prompt-injection defenses.

Open current coverage

Observability & Monitoring

Covered

Tracing, structured logs, operational metrics, and alerting for model-driven workflows.

Open current coverage

Evaluation & Testing

Covered

Unit tests, integration tests, benchmark suites, and LLM-as-judge workflows.

Open current coverage

Production Deployment

Covered

Scaling, deployment topology, graceful degradation, and runtime concerns.

Open current coverage

Cost Engineering

Covered

Caching, model routing, token budgets, attribution, and spend control.

Open current coverage

Governance & Compliance

Covered

Auditability, approvals, policy enforcement, and compliance-aware GenAI design.

Open current coverage

Dataset & Prompt Versioning

Covered

Managing evaluation sets, prompt revisions, and reproducible rollout changes over time.

Open current coverage