Workflow stack maps

Decide the AI stack your team can actually roll out by workflow

Each workflow connects stages, recommended stack templates, cost overlap, alerts, and decision memos into the existing comparison, pricing, and alternatives evidence layer.

01 / Team

AI workflow stack for engineering coding teams

Most teams should start with GitHub Copilot as the governed baseline, add Cursor only for developers who will use the agentic workspace heavily, evaluate Windsurf 2.0 when local Cascade plus cloud Devin operations are the thesis, use ChatGPT Codex or Claude Code plugins for reusable workflow packages, and keep Grok Build as an early-beta pilot. Copilot review usage now needs explicit AI Credit and Actions-minute budgets.

GitHub Copilot · Cursor

Best for
Teams standardizing AI help across many developers
Cost signal
Controls premium workspace spend by avoiding specialist seats for light users.
Rollout risk
Do not buy Cursor for everyone until heavy workspace usage is visible.
4 stages2 stack archetypesNext compare: Cursor vs GitHub Copilot

Open stack map

02 / Team

AI workflow stack for research to decision memo

Use Perplexity for web-grounded discovery, NotebookLM when the corpus is fixed, and ChatGPT or Claude when the output must become a clear decision memo.

Perplexity · NotebookLM

Best for
Teams that need source visibility before they trust recommendations
Cost signal
Avoid paying for every broad assistant if research seats only need source-backed discovery.
Rollout risk
Perplexity and NotebookLM overlap only partially; one searches the web, the other reasons over a bounded corpus.
4 stages1 stack archetypesNext compare: ChatGPT vs Perplexity

Open stack map

03 / Team

AI workflow stack for meeting to action

Meeting-heavy teams should choose around the workspace where actions actually live: Microsoft 365 Copilot Business for Microsoft teams, Gemini for Google teams, and ChatGPT or Notion AI when the action memo needs synthesis beyond the meeting.

Microsoft 365 Copilot Business

Best for
Teams living in Teams, Outlook, Office, and Microsoft governance
Cost signal
The suite seat is easier to defend when it replaces separate meeting and writing seats.
Rollout risk
Avoid duplicating meeting summary tools if Copilot already covers the workspace job.
4 stages1 stack archetypesNext compare: Microsoft 365 Copilot Business vs ChatGPT

Open stack map

04 / Team

AI workflow stack for document-heavy writing teams

Use Claude or ChatGPT for high-quality drafting, NotebookLM or Perplexity when evidence must stay visible, and Notion AI when the workflow has to live inside team docs.

Claude · Perplexity

Best for
Teams producing memos, proposals, and launch docs with review pressure
Cost signal
Do not duplicate broad writing seats if the team already has a suite assistant that covers light editing.
Rollout risk
ChatGPT and Claude overlap heavily for drafting; keep both only if different teams use them for distinct review styles.
4 stages1 stack archetypesNext compare: ChatGPT vs Claude

Open stack map

05 / Team

AI workflow stack for content production teams

Start with ChatGPT or Claude for brief and script work, add Perplexity or NotebookLM when claims need visible sources, use Zebracat for fast blog-to-video and social variants, and choose Synthesia when the buying case is governed avatar-led business video with localization and approval needs.

ChatGPT · Zebracat · Synthesia · Perplexity

Best for
Small teams turning briefs, scripts, or blog posts into frequent social and product video variants
Cost signal
Keeps the video seat narrow and avoids paying for enterprise avatar governance before repeatable social output is proven.
Rollout risk
Do not add Synthesia until the team needs avatar-led business video, localization, API, or formal approval controls.
5 stages3 stack archetypesNext compare: Synthesia vs Zebracat

Open stack map

06 / Team

AI workflow stack for design to prototype to deploy

Start with Figma Make when design-system context is the source of truth, use v0 when the team already wants a Vercel-native front-end path, choose Bolt or Lovable for faster prompt-to-app iteration, and keep Replit in the stack when hosted execution and handoff matter more than design fidelity.

Figma Make · v0 · Replit

Best for
Product teams that start from Figma context and need a credible prototype before engineering commits
Cost signal
Do not buy every builder seat by default. Assign Figma Make to design-led starts, v0 to front-end/Vercel owners, and Replit or Bolt only where runnable app iteration is part of the weekly workflow.
Rollout risk
Figma Make, v0, Bolt, Lovable, and Replit can all generate prototype surfaces; paying for all of them usually creates duplicated experimentation seats.
4 stages1 stack archetypesNext compare: Figma Make vs v0

Open stack map