TLang is not just a code generator — it is a structural consistency tool. The core idea: write the pattern once, enforce it everywhere, forever. Below are the situations where this changes how teams work.
The standard AI-assisted development workflow has a hidden cost problem. Ask an AI to generate a Kotlin entity class: it reasons about your schema, your conventions, your annotations, and produces the file. Multiply that by 200 entities across 10 services and the cost compounds — not just in API tokens, but in time, review cycles, and subtle inconsistencies between what the model produced on Monday versus Friday. TLang changes the economics. The AI writes the template once. TLang generates everything else.
// AI writes this template once — then never touches the 200 output files
lang [kotlin] entity(pkg: String, name: String, table: String) {
pkg ${pkg}
annotation Entity
annotation Table("${table}")
annotation Cache(region = "${name}Cache", expire = 3600)
impl ${name}(
val id: Long,
val name: String,
val createdAt: LocalDateTime = LocalDateTime.now()
)
}
One template call per entity instead of one AI prompt per entity. The AI reasoning happens once; TLang enforces the result at any scale. A project with 200 entities costs the same as a project with 2.
A CVE is disclosed. Your authentication middleware logs full request headers, which can contain session tokens. You need to redact them before logging. Your codebase has 40 microservices, each with its own copy of the middleware. Without TLang: 40 pull requests, 40 code reviews, 40 deployments, and a two-week window where some services are patched and some are not. With TLang: one template change, one generation run, one pull request.
lang [kotlin] loggingFilter(pkg: String, service: String) {
pkg ${pkg}
annotation Component
impl ${service}LoggingFilter : OncePerRequestFilter() {
func doFilterInternal(req, res, chain) {
// Redact sensitive headers before logging
let safe = req.headers.filter { it.key !in SENSITIVE_HEADERS }
log.info("${service} request: {}", safe)
chain.doFilter(req, res)
}
}
}
Update the template. Regenerate. Every service gets the fix in one commit. Security patches, dependency updates, logging changes, audit trail additions — anything that must be applied uniformly across your fleet becomes a single operation.
Microservice architectures drift. One team adds structured logging. Another adds distributed tracing. A third changes the health-check contract. Over months, services that started identical become subtly incompatible. TLang makes consistency the path of least resistance. When all services share the same templates, they share the same structure by construction:
set InventoryService { name: "Inventory", port: "8081", team: "platform" }
set CatalogService { name: "Catalog", port: "8082", team: "catalog" }
set OrderService { name: "Order", port: "8083", team: "checkout" }
set NotificationService { name: "Notification", port: "8084", team: "platform" }
Every service gets the same health check, the same metrics endpoint, the same error response format, the same logging structure. When one improves, all improve. The template is the source of truth — not the individual service repositories.
Documentation and code tend to diverge. API docs go stale. READMEs fall behind. Architecture diagrams describe a system that no longer exists. The doc template solves this by generating every format from a single source. When the template changes, every output format changes together:
doc [md, html] apiReference(service: String, baseUrl: String) {
# ${service} API Reference
Base URL: ${baseUrl}
[section "authentication"
## Authentication
All requests require a Bearer token in the Authorization header.
[code "bash"
curl -H "Authorization: Bearer $TOKEN" ${baseUrl}/api/v1/items
]
]
[section "endpoints"
## Endpoints
[list "unordered"
- GET /health — liveness probe, returns 200 OK
- GET /api/v1/items — list all items
- POST /api/v1/items — create an item
- GET /api/v1/items/:id — get item by ID
- DELETE /api/v1/items/:id — delete item by ID
]
]
}
func main(): String {
File.write("docs/api.md", apiReference("md", "Inventory", "https://api.example.com"), true)
File.write("docs/api.html", apiReference("html", "Inventory", "https://api.example.com"), true)
return "ok"
}
Markdown for GitHub, HTML for the developer portal — both generated, both always current. Apply the same approach to: README files, changelogs, onboarding guides, architecture decision records, runbooks, and any content that lives in more than one place.
Renaming a field across 200 files is a mechanical task — exactly what AI is bad at reliably and exactly what TLang is built for. When your model lives in set declarations and your structure lives in templates, a rename is:
The same applies to structural changes: switching from REST to gRPC, changing your ORM annotations, adopting a new base class, restructuring your package layout. These are template changes, not file-by-file edits.
Your team decides to add distributed tracing to every service using OpenTelemetry. The change is not complex — it is repetitive. Every service needs the same dependency, the same tracer configuration, the same span wrapping on HTTP handlers. Without TLang: 40 services, 40 PRs, 6 weeks, and several services left behind. With TLang: update the service template, add the tracing annotation, regenerate.
lang [kotlin] httpHandler(pkg: String, name: String, path: String) {
pkg ${pkg}
import io.opentelemetry.instrumentation.annotations.WithSpan
annotation RestController
annotation RequestMapping("${path}")
impl ${name}Controller {
annotation GetMapping
annotation WithSpan("${name}.list")
func list(): ResponseEntity
}
}
The template guarantees that every handler gets tracing. Handlers added in the future automatically inherit it. The convention is encoded in the template — not in a wiki page that developers have to remember to read.
Design tokens — colours, spacing, typography, border radii — tend to multiply. One team uses #7c5cfc for accent colour, another hard-codes #8b5cf6 in a component. Over time the UI fragments. TLang style templates make design tokens the single source of truth:
style [css] DesignSystem(accent: String, radius: String) {
:root {
--accent: ${accent},
--accent-hover: "color-mix(in srgb, ${accent} 80%, white)",
--radius: ${radius}
}
}
func main(): String {
File.write("packages/design/tokens.css",
DesignSystem("css", "#7c5cfc", "8px"), true)
return "ok"
}
Change the accent colour: regenerate. Every component that uses var(--accent) updates. Parameterise per-brand to generate white-label variants from the same template.