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Documentation Index

Fetch the complete documentation index at: https://docs.aiparlance.org/llms.txt

Use this file to discover all available pages before exploring further.

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Development cost impact

This chapter covers the economic argument for AI Parlance. Overview: Introduction. Spec: Specification.

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Where cost shows up today

LLMs spend tokens on:
  • context from already-generated code (models, handlers, routes, tests)
  • fixing cross-layer inconsistencies
  • structural repetition for each new endpoint or entity
Most of that is repeated infrastructure, not business logic.

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Honest comparison (same scope)

Scope: User entity with REST CRUD + validation + PostgreSQL migration.

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AI Parlance (source edited by the AI)

app Demo @0.1 {
  database postgres
}

entity User {
  name: string required
  email: email required unique
}

crud User
~6 lines in the spec; id, created_at, updated_at are implicit (spec).

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Go (illustrative transpiler output)

Beyond the struct, a full stack often includes repository, service, handler, routes, validation, and migration — commonly 150–400+ lines for an idiomatic CRUD. Token savings are in generating and reviewing the model (.aip), not transpilation (offline, deterministic).

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TypeScript / Python / PHP

Isolated interfaces or classes are short (~10–20 lines) but do not equal full CRUD — comparing only a struct to crud User is misleading.

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Smaller context for the AI

Working on .aip keeps in context:
  • entities and relations
  • policies and workflows
  • rules in ai_context
Instead of thousands of lines of framework-specific implementation.

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Multi-target without manual duplication

The same spec in crm-reference.aip feeds N transpilers — a change to Lead propagates to SQL, API, and guards without rewriting each stack.

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Financial impact (inference)

Variables: generations per month, average diff size, price per token. High CRUD / low custom logic → higher ROI. Heavy UI or unique integrations → smaller gain on the .aip layer; AI Parlance does not replace that work.

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Limits of the cost argument

  • Transpilers must exist and be reliable — upfront engineering cost.
  • Complex workflow logic can approach imperative code size.
  • Future custom blocks reintroduce manual code outside compact metrics.

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Summary

MetricExpected effect
Tokens when editing domainStrong reduction
Architectural consistencyImproves
Transpilation costOffline, amortized
UI / exotic integrationsOutside main scope