A spreadsheet-analysis stack for teams deciding between one-off AI file analysis, suite-native spreadsheet help, and a repeatable AI spreadsheet workspace.
Recommended: Use ChatGPT for one-off CSV or Excel analysis and charts, Gemini when Google Sheets and Drive are the source of work, Microsoft 365 Copilot when Excel and Microsoft tenant permissions matter most, Quadratic when analysis needs to become a repeatable shared spreadsheet with Python, SQL, formulas, charts, scheduled work, or live data connections, and NotebookLM only for source-grounded narrative synthesis around reports.
▸Must-have & avoid-for-now
Must-have
ChatGPT or an approved suite assistant
Avoid for now
Uploading sensitive customer, finance, HR, or regulated exports to unapproved personal AI accounts, Live database connections before owner, access, retention, and audit expectations are clear, Charts, forecasts, or metric definitions accepted without reviewing formulas, code, assumptions, and source rows
A starter AI stack for engineering managers balancing planning, code context, research, and team communication.
Recommended: Use ChatGPT for planning and stakeholder communication, Granola for approved meeting notes, Cursor or Codex for approved code-context work, Perplexity for source-backed research, and Linear AI only when engineering delivery already runs through Linear.
▸Must-have & avoid-for-now
Must-have
ChatGPT, Cursor, Claude Code
Avoid for now
Unreviewed autonomous coding agents, Tools without clear privacy, retention, or admin controls, AI meeting notes for sensitive people, legal, security, or customer escalation conversations before policy approval, Premium inbox AI unless email response time is a measured manager bottleneck, ZoomMate before licensing, credits, connector access, and meeting-data controls are reviewed, Prompt-built apps published from Replit before engineering ownership, tests, security review, and budget controls are clear, Workflow agents that touch production, customer, incident, or security systems without owner review and rollback paths
A code-review summary stack for engineering teams that want clearer pull request context without weakening review standards.
Recommended: Use GitHub Copilot for GitHub-native review help, Cursor for repository-aware explanation before review, Codex for bounded agent tasks, and ChatGPT only for non-sensitive release or stakeholder summaries.
▸Must-have & avoid-for-now
Must-have
GitHub Copilot, Cursor, Claude Code
Avoid for now
Autonomous code changes merged without reviewer ownership, Pasting proprietary diffs into unapproved general assistants, Higher-autonomy coding agents until source-code policy, tests, branch protection, and review ownership are ready
A suite and inbox productivity stack for teams choosing where AI belongs across email, docs, meetings, and internal knowledge.
Recommended: Use Microsoft 365 Copilot if the company runs on Microsoft 365, Gemini if it runs on Google Workspace, NotebookLM for source-grounded research packets, and Superhuman only for roles where email throughput is a real bottleneck.
▸Must-have & avoid-for-now
Must-have
Microsoft 365 Copilot or Gemini, NotebookLM, Slite
Avoid for now
Suite AI rollout before file, mailbox, and group permissions are cleaned up, Paid seats for casual users who only need occasional free-plan drafting, Skip premium mailbox AI for roles where email is not a measurable bottleneck, Mailbox AI connected to sensitive inboxes without security approval, Cross-app AI agents that can update sensitive systems before app permissions, approvals, and rollback paths are clear
A support-automation stack for teams deciding when to use AI agents, how to price automated resolutions, and where to put escalation and action controls.
Recommended: Use Fin when the main purchase is an AI customer agent that can work with Intercom or an existing helpdesk. Use Zendesk AI Agents when the buyer also needs the broader Zendesk service platform, omnichannel support, admin controls, knowledge, QA, and ticket operations. Use Zapier or n8n only for approved back-office handoffs with human review.
▸Must-have & avoid-for-now
Must-have
Fin or Zendesk AI Agents, A maintained support knowledge base
Avoid for now
AI agents that can issue refunds, change subscriptions, update accounts, or touch identity workflows without human approval, Support automation before escalation categories, QA ownership, and customer-impact monitoring are defined, Uploading raw support conversations or customer records to unapproved general assistants, Outcome-priced automation without tracking resolution quality and cost per resolved category, Deploying a voice agent for account, billing, refund, or identity actions before escalation, disclosure, and consent controls are written down
A meeting-notes stack for teams that need better follow-up without turning every meeting into an unmanaged transcript archive.
Recommended: Use Granola for lightweight meeting notes, Notion AI for shared follow-up docs, and Fireflies only when transcripts and searchable call history are worth the extra governance.
▸Must-have & avoid-for-now
Must-have
Granola, Notion AI, Fathom
Avoid for now
Always-on recording for sensitive people conversations, Transcript archives without retention, access, and consent rules
A PRD-writing stack for turning research, decisions, and prototype direction into clearer product specs.
Recommended: Use Claude for long-form PRD drafting, ChatGPT or Gemini for option generation and stakeholder-ready rewrites, NotebookLM for source-grounded research packets, and Notion AI to keep the final spec connected to workspace context.
▸Must-have & avoid-for-now
Must-have
Claude, ChatGPT, Notion AI
Avoid for now
Auto-generated PRDs accepted without product and engineering review, Prototype output treated as requirements before constraints are written down
An SEO content stack focused on research, briefs, editing, and content operations instead of generic AI-tool listicles.
Recommended: Use Perplexity for source discovery, NotebookLM for synthesis from approved source packs, Claude for briefs and editorial review, Canva AI for lightweight visuals, and Descript only when audio/video repurposing is a real workflow.
▸Must-have & avoid-for-now
Must-have
Perplexity, NotebookLM, Claude, Google Search
Avoid for now
Publishing AI drafts without subject-matter review, Mass-generated pages targeting generic keywords instead of workflow, comparison, or buyer intent, Using scientific-literature summaries as publishable claims without checking the underlying papers and study limitations, Generated explainer videos or social clips that make product or pricing claims without source and approval review
A practical AI stack for product designers moving from research signals to prototypeable product ideas.
Recommended: Use Figma AI for design exploration, v0 for React-oriented UI prototypes, Perplexity for source-backed product context, and Canva AI only for marketing or presentation assets that are not product-system work.
▸Must-have & avoid-for-now
Must-have
Figma AI, v0, Perplexity
Avoid for now
Generated production UI without design review, Prototype builders connected to real customer data before security review, Replit Agent for production apps before engineering reviews auth, database access, dependencies, secrets, publishing visibility, and credit limits, Google Stitch as a default team standard before pricing, account controls, and data handling are clearer, Paper MCP access on confidential design files before agent permissions and source-of-truth rules are reviewed
A user-research stack for capturing interviews, finding external context, and synthesizing insights without skipping researcher review.
Recommended: Use Fireflies for interview transcripts, NotebookLM for source-grounded synthesis from approved research material, Claude for readout drafts, and Perplexity for market or competitor context that stays separate from customer evidence.
▸Must-have & avoid-for-now
Must-have
Fireflies, NotebookLM, Claude
Avoid for now
Unattributed insight summaries that cannot be traced to notes or transcripts, Uploading raw research data to tools that have not passed vendor review, Scientific or policy conclusions based on Elicit screening or extraction without checking the cited papers
A content-production stack for creating visuals, clips, briefs, and repurposed assets without drifting into generic AI publishing.
Recommended: Use Canva AI for visual assets and templates, Descript for spoken-media editing and clips, Claude for brief and copy review, and Perplexity or NotebookLM depending on whether the team needs source discovery or synthesis from known material.
▸Must-have & avoid-for-now
Must-have
Canva AI, Claude, Perplexity or NotebookLM
Avoid for now
Publishing generated claims without source, legal, or subject-matter review, Uploading customer images, recordings, or licensed creative assets without rights and consent review, Mass-generated pages or assets that do not support a real workflow or buyer intent, Generating or cloning a voice for ads, demos, or narration without the speaker’s consent, usage rights, and required disclosure, AI-generated campaign video or visuals published before brand, rights, accessibility, disclosure, and approval review, Voice-drafted customer or campaign copy published without source, brand, privacy, and final editorial review, Automations that publish, email, or update CRM records from generated content without human approval
A workflow-automation stack for teams deciding when to connect apps, add AI agents, and put human approvals around cross-system work.
Recommended: Use Zapier for broad no-code app handoffs, Make for visual scenario control across operations workflows, and n8n when technical teams need explicit logic, code steps, self-hosting options, inspectable executions, human approvals, or AI-agent workflows that need deeper control.
▸Must-have & avoid-for-now
Must-have
Zapier, Make, or n8n
Avoid for now
AI agents that can take external-facing actions without human approval, Automations using shared personal credentials instead of owned service accounts, High-volume workflows without task/activity budget monitoring, Self-hosted automation without upgrade, backup, network, and secret-management ownership, Automated spreadsheet refreshes that publish metrics or trigger downstream actions before source data, formulas, and owners are reviewed
A lean GTM stack guide for founders and small teams deciding between CRM-native AI, enrichment/outbound systems, and waiting until CRM and data-use rules are clearer.
Recommended: Start with the CRM as the source of truth. Use HubSpot Breeze first when HubSpot already owns contacts, deals, meetings, and follow-up. Use Clay when the bottleneck is account research, enrichment, buying signals, outbound lists, or CRM enrichment across multiple providers. Keep Superhuman, Fathom, Zapier, or n8n as supporting tools only after CRM ownership, consent, suppression, and approval rules are written down.
▸Must-have & avoid-for-now
Must-have
One CRM source of truth, One approved research or enrichment workflow, A suppression and approval checklist
Avoid for now
Buying enrichment credits before the ICP, owner, and data-use policy are clear, Automated outreach or CRM writes without consent, opt-out, suppression, and human approval rules, Mixing scraped, personal, customer, and CRM data without source-rights review
Workflow stacks here mean practical AI software combinations for work, not model infrastructure, MLOps, or production AI architecture. Read the glossary.