Tendril — AI Lessons for Real Life

Tendril

Pick a model that matches usage shape

Per-seat: great when usage is predictable and bounded (daily summaries)

Per-use / metered: best when usage is spiky or power-law (video generation)

Credits: hybrid — users feel in control, you protect margin with expiry

Freemium with hard rate limits: use only if free users drive real virality

Always model gross margin at 60%+ AFTER inference cost, not before

Watch your 90th-percentile user. If their inference cost exceeds your plan price, either raise the ceiling, switch to credits, or cap the feature.

# Simple margin math Plan price: $29/user/month Avg inference cost: $4/user/month P90 inference cost: $22/user/month <-- danger zone Stripe + infra: $3/user/month Gross margin (avg): ($29 - $4 - $3) / $29 = 76% OK Gross margin (P90): ($29 - $22 - $3) / $29 = 14% NOT OK Fix: add a 500-credit cap, overage at $0.05/credit.

You're pricing right when 80%+ of customers feel the plan is fair, your P90 user still pays more than they cost, and you don't panic when Anthropic has a latency spike.

End-of-lesson check

8 questions · take it digitally for instant feedback at tendril.neural-forge.io/learn/quiz/end-biz2-ai-seat-pricing-adults

What is the main idea of "Pricing an AI Feature: Per-Seat vs. Per-Use vs. Credits"?

Choose a pricing model that survives when your COGS is a variable OpenAI or Anthropic bill.
Use AI as the final authority for the whole decision
Avoid checking the answer once it sounds polished
Focus only on speed instead of judgment

Which concept is most central to "Pricing an AI Feature: Per-Seat vs. Per-Use vs. Credits"?

COGS
pricing strategy
usage-based billing
gross margin

Which use of AI fits this topic best?

Let the AI decide what matters without your review
Use the answer before checking whether it fits the situation
Per-seat: great when usage is predictable and bounded (daily summaries)
Treat the AI output as automatically correct

What should a careful learner remember about "Don't copy ChatGPT's $20/month"?

OpenAI subsidizes inference to win the platform war. You can't. Price from YOUR unit economics, not theirs.
Skip the context so the tool can guess faster
Treat the output as private even after sharing it online
Use the answer without checking the source

You want to use AI after this lesson. What is the safest next step?

Act immediately because the AI answer is written clearly
Use AI as a workflow assistant, with human review for decisions that carry risk.
Hide uncertainty so the final answer looks cleaner
Use private or sensitive details before checking permission

How should AI output about pricing strategy be treated?

As proof that no other source is needed
As a replacement for context, consent, or expert review
As a draft or helper output that still needs human judgment and verification
As something that becomes correct when it sounds confident

Name one way to verify an AI answer about pricing strategy.

Which action would help you apply "Pricing an AI Feature: Per-Seat vs. Per-Use vs. Credits" responsibly?

Use the tool to avoid thinking through the tradeoff
Keep going even if the output conflicts with a trusted source
Treat the AI output as automatically correct
Per-use / metered: best when usage is spiky or power-law (video generation)

Pick a model that matches usage shape

Per-seat: great when usage is predictable and bounded (daily summaries)

Per-use / metered: best when usage is spiky or power-law (video generation)

Credits: hybrid — users feel in control, you protect margin with expiry

Freemium with hard rate limits: use only if free users drive real virality

Always model gross margin at 60%+ AFTER inference cost, not before

Watch your 90th-percentile user. If their inference cost exceeds your plan price, either raise the ceiling, switch to credits, or cap the feature.

You're pricing right when 80%+ of customers feel the plan is fair, your P90 user still pays more than they cost, and you don't panic when Anthropic has a latency spike.

End-of-lesson check

8 questions · take it digitally for instant feedback at tendril.neural-forge.io/learn/quiz/end-biz2-ai-seat-pricing-adults

What is the main idea of "Pricing an AI Feature: Per-Seat vs. Per-Use vs. Credits"?

Choose a pricing model that survives when your COGS is a variable OpenAI or Anthropic bill.
Use AI as the final authority for the whole decision
Avoid checking the answer once it sounds polished
Focus only on speed instead of judgment

Which concept is most central to "Pricing an AI Feature: Per-Seat vs. Per-Use vs. Credits"?

COGS
pricing strategy
usage-based billing
gross margin

Which use of AI fits this topic best?

Let the AI decide what matters without your review
Use the answer before checking whether it fits the situation
Per-seat: great when usage is predictable and bounded (daily summaries)
Treat the AI output as automatically correct

What should a careful learner remember about "Don't copy ChatGPT's $20/month"?

OpenAI subsidizes inference to win the platform war. You can't. Price from YOUR unit economics, not theirs.
Skip the context so the tool can guess faster
Treat the output as private even after sharing it online
Use the answer without checking the source

You want to use AI after this lesson. What is the safest next step?

Act immediately because the AI answer is written clearly
Use AI as a workflow assistant, with human review for decisions that carry risk.
Hide uncertainty so the final answer looks cleaner
Use private or sensitive details before checking permission

How should AI output about pricing strategy be treated?

As proof that no other source is needed
As a replacement for context, consent, or expert review
As a draft or helper output that still needs human judgment and verification
As something that becomes correct when it sounds confident

Name one way to verify an AI answer about pricing strategy.

Which action would help you apply "Pricing an AI Feature: Per-Seat vs. Per-Use vs. Credits" responsibly?

Use the tool to avoid thinking through the tradeoff
Keep going even if the output conflicts with a trusted source
Treat the AI output as automatically correct
Per-use / metered: best when usage is spiky or power-law (video generation)