Unicorn language learning

<!-- Last reviewed: 2026-03 -->

Language Learning Protocol

5-Phase Protocol

Phase	Duration	Goal	Key Deliverables
1. Exploration	30 min	Run first program	Hello World, build system, basic syntax
2. Patterns	1-2 hr	Map to known equivalents	Comparison table, pattern mapping
3. Ecosystem	1 hr	Set up toolchain	Package manager, test framework, linter, LSP
4. Idioms	2-3 hr	Learn community conventions	Style guide notes, anti-patterns list
5. Production	Ongoing	Ship production code	Logging, monitoring, deployment, security

Target: Zero to implementing small features in < 4 hours.

Run scripts/new-language.sh with the target language to execute interactively.

Phase 1: Exploration Checklist

• Install toolchain (compiler/interpreter/runtime)
• Hello World builds and runs
• Variable declaration (mutable vs immutable)
• Function definition and calling
• Control flow (if, for, match/switch)
• Error handling mechanism identified
• Entry point convention understood

Phase 2: Pattern Mapping

Complete this comparison for the new language:

Concept	Python	JavaScript	Go	New Language
Variables	x = 5	let x = 5	x := 5	?
Constants	X = 5	const X = 5	const X = 5	?
Functions	def f():	function f()	func f()	?
Error handling	try/except	try/catch	if err != nil	?
Null safety	None	null/undefined	nil	?
Iteration	for x in list:	list.forEach()	for _, x := range	?
Collections	list, dict	Array, Object	slice, map	?
Types/Classes	class Foo:	class Foo	type Foo struct	?
Imports	import foo	import foo from	import "foo"	?
Testing	pytest	jest	go test	?
Packages	pip	npm	go mod	?

For each concept, ask: "What's the equivalent in languages I know?"

Phase 3: Ecosystem Setup

identify:
  package_manager: cargo | go mod | npm | pip | ...
  test_framework:  built-in or external, conventions
  linter_formatter: clippy/rustfmt | golint/gofmt | eslint/prettier | ...
  lsp_server:      name, IDE integration

Ecosystem checklist:

• Package manager configured
• Can write, run, and get coverage for tests
• Linter and formatter installed
• IDE autocomplete working
• Official docs bookmarked

Phase 4: Idioms

1. Read official style guide
2. Study standard library patterns
3. Review top 5 popular GitHub projects
4. Capture anti-patterns from linter warnings

Phase 5: Production Readiness

• Structured logging configured
• Error handling comprehensive
• Graceful shutdown implemented
• Health check endpoint
• Metrics/monitoring integrated
• Configuration externalized
• Secrets management configured
• Resource limits set
• Deployment documented
• Rollback procedure defined

Paradigm Recognition

Language Analysis
|
+-- Object-Oriented (Java, C#, Python, Ruby)
|   Classes, inheritance, polymorphism
|
+-- Functional (Haskell, Elixir, Clojure, Scala)
|   First-class functions, immutability
|
+-- Procedural (C, Go, Pascal)
|   Functions as primary unit, explicit state
|
+-- Multi-Paradigm (Python, Rust, JavaScript, Kotlin)
|   Developer chooses approach
|
+-- Declarative (SQL, HTML, CSS, Terraform)
    Describe WHAT, not HOW

Quick Reference Template

For every new language, produce:

# [Language] Quick Reference
## Setup        — install, project init, run, test commands
## Basics       — variables, functions, control flow, errors
## Patterns     — map, filter, reduce, null handling, async
## Ecosystem    — package manager, testing, linting, formatting
## Idioms       — language-specific best practices
## Anti-Patterns — common mistakes to avoid
## Resources    — official docs, style guide, community

See references/learning-templates.md for full template.

Knowledge Transfer Format

knowledge_transfer:
  language: "[Name]"
  paradigm: "[OOP | FP | Procedural | Multi | Declarative]"
  quick_reference: "[path to cheat sheet]"
  gotchas:
    - "Common mistake 1"
    - "Common mistake 2"
  production_notes:
    - "Deployment consideration"
    - "Performance characteristic"
  confidence_level: "beginner | intermediate | proficient"

Learning Velocity Targets

Metric	Target
Hello World running	< 30 min
Basic patterns mapped	< 90 min
Ecosystem set up, tests passing	< 3 hr
First real feature implemented	< 4 hr
Pattern recognition accuracy	> 85%
Anti-pattern avoidance (first 10 implementations)	> 80%

When NOT to Learn Everything

Decision Criteria

Learn what the task requires. Skip the rest until needed.

Task	Learn	Skip (for now)
REST API in Go	HTTP server, routing, JSON, errors, testing	Generics, reflection, cgo
CLI tool in Rust	Clap, file I/O, error handling	Unsafe, macros, async
Data pipeline in Elixir	GenServer, streams, Ecto	NIFs, distributed Erlang

Progressive Depth

Layer	Timeframe	Scope
1	Day 1	Core syntax, basic patterns
2	Week 1	Ecosystem, idioms, testing
3	Month 1	Advanced features, performance
4	Month 3+	Internals, contributing

Most tasks require Layer 1-2 only.

Reference Files

• references/language-comparison-matrices.md - Comparison tables across 10+ languages
• references/learning-templates.md - Setup scripts, quick reference templates
• references/phase-guides.md - Detailed guides for each learning phase
• scripts/new-language.sh - Interactive learning protocol script