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Decision examples for the role you bring

Original voices, evidence, and key variables to help you find a starting point in your own decision context.

Start with your role

Investors

What evidence distinguishes AI product revenue from services revenue disguised as software?

Test whether end customers buy it repeatedly and independently, and whether it scales without matching growth in human delivery. Outcome-based pricing is not inherently a service business.

  • Retention & repeat use
  • Human-delivery share
  • Customer customization
Open insight brief

Founders

As foundation models improve, what becomes the real moat for vertical AI startups: industry data, workflow integration, or distribution?

A durable moat combines a continuing data loop, deep workflow integration, and distribution or ecosystem reach. Data in isolation is not enough.

  • Ongoing data loop
  • Workflow embed
  • Ecosystem lock-in
Open insight brief

Research leaders & investment researchers

For research leaders using AI, when is a conclusion reliable enough to inform a formal decision: traceable sources, independent corroboration, or expert review?

Traceable sources are only the starting point. Independent corroboration and risk-calibrated expert review determine whether a conclusion can enter a formal process.

  • Source traceability
  • Independent corroboration
  • Expert-review threshold
Open insight brief

AI-for-Science founders & R&D leaders

For AI-for-Science companies, what creates the most durable closed loop between model capability and validated scientific outcomes: proprietary experimental data, automated wet labs, or faster model-to-experiment iteration?

The moat is a full prediction–experiment–feedback flywheel: data, lab automation, and iteration reinforce each other, but the outcome must be reproducible scientific validation.

  • Experimental data loop
  • Wet-lab automation
  • Validation & iteration speed
Open insight brief

Business leaders

For a CFO, should AI investment be evaluated primarily by headcount savings, revenue growth, or cycle-time reduction?

Prioritize durable business value and growth over time. Cycle-time reduction can be a strong leading signal; headcount efficiency depends heavily on context.

  • Revenue or retention
  • Decision-quality gain
  • Workforce redeployment
Open insight brief

CIOs & digital leaders

Will enterprise adoption of AI agents be bottlenecked more by reliability, data access, or change management?

Trust, habit, and change management are the most common bottlenecks. In regulated, legacy, or sensitive-data environments, access and governance can become decisive.

  • Data access & standardization
  • Risk & compliance level
  • Workflow-owner adoption
Open insight brief

Growth leaders

As AI search grows, should brands and publishers keep investing in SEO or shift to answer-engine optimization?

SEO remains the foundation for content to be crawled, cited, and recommended by models. The goal expands from ranking and clicks to becoming part of the answer.

  • AI-search share
  • Citation measurability
  • Funnel position
Open insight brief

Public-market & industry observers

Over the next three years, will humanoid robots commercialize first as general-purpose systems or in specialized, structured industrial settings?

Over the next three years, factories, logistics, and automotive manufacturing are the more credible path. General humanoids in open environments still face limits in safety, dexterity, energy, cost, and proven value.

  • Deployment duration
  • Unit economics
  • Repeatable task scope
Open insight brief

Bring research back to work

Move an insight brief into the tools you already use.

Export to Obsidian, or use a Share link / PDF to bring sourced judgement into ChatGPT, Codex, Claude Code, Work Buddy, and the conversations where work moves forward.See export and collaboration
  1. 01Create a sourced insight brief
  2. 02Export it or create a Share link
  3. 03Continue in your workflow
  • Obsidian
  • ChatGPT
  • Codex
  • Claude Code
  • Work Buddy

How STANCES unpacks a judgement

Consensus

What most credible voices support.

Where views diverge

Where the conclusion changes.

Perspective differences

What each role actually values.

Key variables

What to test next.

Have a decision you want to see more clearly?

Tell STANCES the decision and the question behind it. We organize real voices into consensus, divergence, and the variables worth testing next.

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