You've got the mental model — the cognitive loop, MCP, Skills, memory, guardrails. Now the question is: what do you build with? 30+ tools across 7 layers, from brainstorming to enterprise deployment. But picking a tool first is the most expensive mistake you can make.
The stack covers every stage. Each layer is a distinct type of thing. Know what each one IS — and where it fits in your journey.
Anthropic's frontier AI. Extended thinking, artifacts for instant apps, project knowledge, web search. The thinking partner behind this page.
OpenAI's conversational AI. GPT-4o multimodal, Canvas, DALL-E, plugins. 200M+ weekly users.
Google's AI. 2M token context, Workspace integration, multimodal. Strongest in Gmail, Docs, Sheets.
AI research engine. Cited, sourced answers. Deep Research writes full reports. Replaces "let me Google that."
Describe what you want. Get a working app in minutes. This is where passion projects become real.
Market leader. React + TypeScript, Supabase backend, GitHub sync, 100+ integrations. Design-first.
Full-stack with real in-browser IDE. File tree, terminal, NPM. Open-source engine. Fastest for prototyping.
Zero-setup backend. Auto-generates DB, auth, RBAC, hosting. Multi-model. Acquired by Wix for $80M.
Cloud IDE + Agent 3 autonomous build/test/deploy. Design Mode. Connectors for 20+ services.
Text-to-UI for React + Tailwind. Cleanest frontend code. Components for Next.js projects.
When prototypes need real engineering. AI-native IDEs and autonomous coding agents.
VS Code fork. Composer for multi-file generation, 8 parallel agents, Plan Mode, visual editor.
#1 AI IDE. Cascade flow, Arena Mode. Merging with Devin for fully AI-driven development.
Terminal-native agent. Reads codebase, runs commands, manages Git, spawns sub-agents. 1M context.
Most adopted. Inline completions, chat, agent mode. VS Code, JetBrains, Vim. 26M+ users, $10/mo.
Autonomous software engineer. Plans, writes, tests, deploys via Slack. Sandboxed. $4B valuation.
Libraries for AI agents that reason, use tools, execute multi-step tasks. Open-source orchestration + cloud provider SDKs.
Graph-based state machine. Nodes, edges, loops. Durable execution. Human-in-the-loop. Strong Planning + Observe loop from the cognitive architecture.
Role-based multi-agent. Agents with roles, goals, backstories collaborate as a team. The A2A delegation pattern in action. 40% faster to prod.
Microsoft's multi-agent framework. Conversational agent patterns, code execution, group chat orchestration. Strong Reasoning layer.
Microsoft's SDK for AI integration. C#/Python/Java. Deep Azure + M365 + Copilot integration. Enterprise-first.
Agent Development Kit. Build agents with Gemini, deploy to Vertex AI Agent Engine. Native A2A support.
AWS's agent SDK. Model-driven, built for Bedrock. MCP-native tool connectivity. Open-source.
Open-source agent runtime. Runs locally, connects via chat apps. 250K+ stars. All 8 building blocks running on your machine — MCP native, 100+ Skills, dual-layer memory.
Observability for agents. Trace every decision, tool call, token. Debug why agents do what they do.
Not products — open specifications. The reason all tools above work together.
Model Context Protocol. Connects AI to tools, databases, APIs. Anthropic, OpenAI, Google, Microsoft. The USB of AI.
Google's Agent-to-Agent. MCP = agents to tools. A2A = agents to agents. Communication backbone.
Modular capabilities. SKILL.md files with instructions and tool definitions. Build once, share everywhere.
SSO, compliance, audit trails, VPC isolation. Managed services from cloud providers.
Azure unified AI. 11K+ models, 1,400+ connectors, MCP, Entra ID. Agent Service GA. Deploy to M365 Copilot.
Fully managed agents. Select model, write instructions. IAM/VPC/CloudWatch native. AgentCore for scale.
Google's agent platform. ADK in <100 lines Python. A2A interop. Agent Engine managed deploy.
Enterprise OpenClaw + Nvidia guardrails. Nemotron models, DGX Spark/Station. Always-on local agents.
Workflow platforms connecting agents to SAP, Salesforce, Slack, Dynamics, 1,000+ more.
Enterprise iPaaS. 1,000+ connectors, recipe-based automation, governance. Bridge to enterprise systems.
Microsoft low-code. Visual flows, Copilot integration, SharePoint/Teams/Dynamics. Best for M365 orgs.
Lightweight SaaS automation. No-code, fast, cheap. Simple triggers and app-to-app glue.
Open-source workflow automation. Self-hosted, full data control, visual node editor. AI nodes built in.
That stack you just saw? It's intoxicating. Thirty-plus tools, each more impressive than the last. You can go from a sentence to a deployed app in four minutes. You can run a personal AI agent from your laptop that manages your email while you sleep. The temptation is overwhelming: grab a tool and start building.
Don't.
The pattern: Someone discovers OpenClaw or Claude Code or Lovable, asks "what can I build?" Weeks of technically impressive work nobody wants. Applause at the demo. Zero users after.
Tool-first = demos, not products. Solutions looking for problems. Features nobody asked for. Architectures chosen because they're interesting. The nineteen out of twenty agent pilots that never reach production? Most of them started here.
Building the wrong thing is now faster too. Speed amplifies good decisions and bad ones equally. A tool that lets you ship in 4 minutes also lets you waste 4 months on the wrong problem in 4 minutes.
The discipline: Start with a problem — a real person with a real pain point they'd pay to solve. Validate the use case. Calculate the ROI. Then — only then — pick the tool from the stack. That sequence is the difference between the 1 in 20 that makes it to production and the 19 that don't.
Flip the sequence. Start with a real problem. Validate the use case. Calculate ROI. Then pick the tool. Every step earns the right to take the next one.
Talk to 20 people. Actual pain — wasted time, lost money, missed opportunities. Not what you think is cool — what they'd pay to fix.
One sentence: "[Person] wastes [cost] doing [workaround]." If you can't say it in one sentence, you don't understand it yet.
Impact × feasibility × risk. Not gut feel — structured evaluation. The Use Case Discovery Workbook scores across 10 dimensions with risk-adjusted recommendations.
Time saved + errors avoided + revenue unlocked = value. API + infra + your time = cost. Aim for 5x+ ROI. If below 3x, you need a bigger problem, not a better tool.
Now — only now — match requirements to the right path and layer from the stack. Your maturity level determines your path.
Prototype in days, not months. Show to those 20 people. Iterate on reality, not assumptions.
Think of the last time you saw someone doing manual, repetitive work:
You just found a use case — and the start of an ROI calculation.
Not every problem needs AI. Focus where agents have a genuine advantage. The Use Case Discovery & Prioritization Workbook in the Toolkit systematizes this with 10 agent-specific patterns and a risk-adjusted scoring framework.
Manual processes. Copying data between systems, following checklists, pattern recognition on unstructured data — agent opportunities. Think of the O2C cycle from the Primer: 4 cognitive loops across order entry, fulfillment, invoicing, and cash collection.
Domain expertise bottlenecks. One expert reviewing contracts or triaging tickets — encode that knowledge into Skills so the agent can handle the 80% and escalate the 20%.
Integration nightmares. Data in silos, disconnected tools. MCP was built for this — one protocol connecting your agent to every system.
Vertical opportunities. Specific industry + core workflow rebuilt with agents = products incumbents can't replicate. Healthcare, SLED, financial services, SaaS — see the Agent Showcase for 11 patterns.
You've identified the problem and validated the ROI. Now — which layers of the stack do you actually need? Nobody uses all 7. Mapped to the maturity levels from the Primer.
"I want it live this weekend." Claude.ai → Lovable/Bolt → Zapier (optional). 2–3 layers only. Information agents, simple prototypes.
"Automate invoices, onboarding." Claude → Cursor/CC → MCP → Workato/n8n. Action agents with read + write. Add governance.
"Build a testing/evaluation agent." Claude → Claude Code → CrewAI/LangGraph → MCP → Cloud deploy. Full cognitive loop with Skills.
"Manage my calendar, email, tasks." Claude → OpenClaw → Skills/MCP. All 8 building blocks running locally. Memory + cron.
"Clinical trials, compliance, O2C." Claude → Cursor/CC → LangGraph → MCP+A2A → Foundry/Bedrock → Workato. All 7 layers. Full governance required.
This is where most teams jump straight to the IDE. The ones that succeed don't. They start with the Agentic Engineering lifecycle — a 6-stage operational framework: Justify → Architect → Govern → Build → Gate → Operate. And the first tool in that lifecycle is the Use Case Discovery & Prioritization Workbook — 10 agent-specific evaluation dimensions, risk-adjusted scoring, and a Selection Brief that tells you whether the math supports building.
The Primer gave you the mental model. This page gave you the tool selection discipline. The Toolkit gives you the operational playbooks. Here's the full sequence.
Real humans, real problems, real budgets. Not what you think is cool — what they'd pay to fix.
One sentence. Napkin math. Use the Prioritization Workbook to score across 10 dimensions. If ROI isn't 5x+, find a bigger problem.
Match problem to maturity level. Choose from the 5 paths. You don't need all 7 layers.
Governance Policy Template (32 pre-production gates) and Identity & Trust Template (49 security controls) — before the first line of code.
Now open the IDE. Select your framework from the reference table below. Connect MCP servers. Encode expertise into Skills.
Pre-production review. Does the agent do what it should? Does it NOT do what it shouldn't? The observation step from the cognitive loop — applied to your release process.
Incident response, monitoring, continuous improvement. The same Sense → Think → Plan → Act → Observe loop — applied to your operations.
The Primer gave you the mental model — the noise filter for evaluating every agent product and framework. This page gave you the discipline — problem first, tool second. The Toolkit gives you the operational playbooks to execute — 28 tools organized across the 6-stage Agentic Engineering lifecycle. 9 available for download today. Start with the Use Case Discovery & Prioritization Workbook.
Problem. Use Case. ROI. Path. Governance. Then Build.
That's the sequence. The Toolkit has the playbooks for every step.
You've chosen your path and started the Toolkit lifecycle. When you reach the Build & Integrate stage, this is your framework selection reference — the tools mapped to use cases, with the building blocks each one emphasizes.
Problem identified, ROI validated. Map requirements to the stack.
| If you need... | Consider | Why | Best for |
|---|---|---|---|
| Brainstorming | Claude.ai / ChatGPT / Gemini | Reasoning, search, artifacts | Ideas, planning |
| First prototype | Lovable / Bolt.new / Base44 | Prompt → app in minutes | MVPs, validation |
| UI components | v0 by Vercel | React + Tailwind from text | Dashboards, pages |
| Scaling past MVP | Cursor + Claude Code | AI IDE + terminal agent | Production code |
| Tool connectivity | MCP Servers | One protocol, all models | Data & API integration |
| Personal agents | OpenClaw | Local, extensible, chat-native | Productivity |
| Complex workflows | LangGraph | State graphs, durable execution, loops | Finance, healthcare, logistics |
| Fast multi-agent | CrewAI | Role-based, 40% faster to prod | Content, triage, research |
| Conversational agents | AutoGen | Multi-agent chat, code execution | Collaborative reasoning |
| Microsoft ecosystem | Semantic Kernel | C#/Python/Java, M365 + Copilot native | .NET enterprise shops |
| Google ecosystem | Google ADK | Gemini-native, A2A built-in | GCP-first organizations |
| AWS ecosystem | Strands SDK | Bedrock-native, MCP built-in | AWS-first organizations |
| Enterprise Azure | Azure AI Foundry | 1,400 connectors, Entra ID | Regulated industries |
| Enterprise AWS | Bedrock + AgentCore | IAM, VPC, CloudWatch | AWS organizations |
| Enterprise GCP | Vertex AI + Agent Engine | ADK, A2A, Agent Garden | Google Cloud orgs |
| Agent observability | LangSmith / LangFuse | Trace, debug, evaluate agents | Any framework |
| Enterprise iPaaS | Workato / Power Automate | 1,000+ connectors | SAP, Salesforce |
| Simple automations | Zapier / Make / n8n | No-code, fast, cheap | Triggers, flows |