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ChatGPT/Claude Prompt to Design Token Economics

Design a token economic model with supply mechanics, vesting, utility, staking incentives, governance, and multi-year sustainability analysis.

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Your Prompt
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What this prompt does

This prompt designs token economics that create real demand instead of pure speculation. You name [project_name], its [project_type], [user_base], and the [token_symbol] with its [token_purpose], and it designs supply mechanics ([supply_type] of [total_supply], with an [emission_curve] or [burn_mechanism]), distribution across [distribution_categories] with vesting, utility, staking, governance, and a multi-year sustainability analysis.

The structure works because token failures usually come from ignoring the gap between selling pressure and buying pressure. By forcing vesting schedules ([team_vesting] with [cliff_period], [investor_vesting]), [utility_mechanisms] that map user actions to token flows, a [staking_type] model with a sustainable [yield_source], governance via [voting_mechanism], and a model over [model_years] years that projects unlock-driven selling against utility-driven buying with [risk_periods] flagged, the prompt keeps the design honest to real supply dynamics. The [token_purpose] anchors everything, because a token that earns its place in the [project_type] behaves very differently from one bolted on for fundraising.

When to use it

  • You are designing a token and want utility-driven demand, not just speculation
  • You need vesting and an unlock chart that shows where selling pressure clusters
  • You want a staking model with a clearly identified [yield_source]
  • You need governance that resists plutocracy via [voting_mechanism]
  • You want a multi-year flow model that flags [risk_periods] like unlock cliffs
  • You want lock-up tiers that reward longer commitments with more weight
  • You want a comparison against [comparable_tokens] to clarify differentiators

Example output

Expect a tokenomics document: supply mechanics with an emission schedule following [emission_curve] or [burn_mechanism] rules, a distribution table across [distribution_categories] with vesting and a generated unlock chart, a utility section mapping [utility_mechanisms] to the [token_flow_diagram], a staking model with [lock_tiers] and [staking_apy] tied to [yield_source], a governance design using [voting_mechanism] scoped to [governance_scope], a sustainability analysis over [model_years] years projecting selling versus buying pressure and identifying [risk_periods], and a comparison against [comparable_tokens]. The unlock chart and flow diagram make the supply dynamics visual rather than buried in text.

Pro tips

  • Be honest about [total_supply] and [distribution_categories] percentages, since the unlock model is only as truthful as those inputs
  • Pin down [yield_source] for staking; if rewards come only from new emissions, the APY is inflationary dilution dressed up as yield
  • Use the [model_years] projection to find the [risk_periods] where investor and team unlocks stack, and design around them rather than hoping
  • Make [utility_mechanisms] create genuine recurring demand — a token only used to speculate has no buying pressure to offset unlocks
  • Tier [lock_tiers] so longer locks earn meaningfully more weight, giving holders a reason to reduce circulating supply voluntarily
  • Compare honestly against [comparable_tokens] like FIL or AR; differentiators that do not survive that comparison are marketing, not design
  • Treat the sustainability analysis as a model with assumptions, not a forecast — adoption and price are uncertain, so stress-test the inputs

Frequently Asked Questions

Does it model token price?
Not directly. It models selling pressure from unlock schedules against buying pressure from `[utility_mechanisms]` over `[model_years]` years, flagging `[risk_periods]`. Price depends on adoption and market conditions it cannot predict, so treat the output as a structural sustainability check, not a price forecast.
How does it ensure staking yield is sustainable?
By forcing you to define `[yield_source]` explicitly. If yield comes only from newly minted tokens, that is inflationary dilution, which the analysis surfaces. Sustainable designs draw `[staking_apy]` from real protocol fees, and the prompt distinguishes the two rather than assuming.
Can it handle both inflationary and deflationary tokens?
Yes. Set `[supply_type]` accordingly: inflationary designs get an `[emission_curve]` from `[initial_emission]` to `[terminal_emission]`, while deflationary designs define `[burn_mechanism]` rules. You can also combine a capped supply with deflationary burn pressure, as the default example does.
Why does it compare against other tokens?
Comparing against `[comparable_tokens]` such as FIL, AR, and STORJ grounds the design in existing models and forces you to articulate real differentiators. A design that looks identical to established tokens without a clear distinction is unlikely to attract demand it does not earn.
Engr Mejba Ahmed

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Engr Mejba Ahmed

AI Developer · Software Engineer

I'm Mejba — I design and ship production AI systems, automations, and full-stack apps. If you want this turned into a working solution for your team, let's talk.

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Engr Mejba Ahmed

Engr Mejba Ahmed

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