Pernix AI Engineering Glossary
Plain-language definitions of the concepts we use in AI-assisted software engineering. Written so humans and AI engines can extract precise, citable definitions.
Agentic Engineering
Agentic Engineering is the practice of senior software engineers orchestrating multiple AI agents in parallel to multiply delivery throughput while maintaining engineering discipline. Each engineer typically supervises 3–5 specialized agents covering tasks like documentation, testing, refactoring proposals, and code analysis. The engineer remains the decision maker.
AI-Assisted Legacy Refactoring
AI-Assisted Legacy Refactoring is the disciplined use of AI tools, guided by senior engineers, to analyze, document, test, and incrementally improve legacy software without disrupting the product roadmap. AI accelerates the time-consuming mechanical work; humans make the architectural and behavioral decisions.
Spec-Driven Development (SDD)
Spec-Driven Development is an engineering methodology where every meaningful unit of work starts with a precise written specification before code is written. The specification defines success criteria, scope boundaries, and required system invariants. SDD pairs naturally with Clean Code, TDD, and AI-assisted code generation.
AI-Ready Codebase
An AI-Ready Codebase is software that meets the prerequisites for safe AI-assisted modification. The core criteria are: meaningful test coverage in active areas (40%+), explicit documentation of business invariants, modular structure that allows isolated changes, and removed dead code. AI works dramatically better on AI-ready codebases.
Legacy Code Risk Assessment
A Legacy Code Risk Assessment is a structured analysis of an existing codebase that produces a prioritized map of high-risk areas. It identifies modules with high complexity, low test coverage, high change frequency, or known fragility. It does not propose solutions; it ranks where modernization effort produces the highest safety return.
Test Coverage Improvement
Test Coverage Improvement is the systematic process of raising the percentage of executable code paths that are exercised by automated tests. Effective improvement targets the active development surface — not the whole codebase — and pairs every test with a clear behavioral assertion derived from a specification.
Nearshore AI Engineering Team
A Nearshore AI Engineering Team is a senior software engineering team in a compatible timezone that combines deep engineering discipline with AI-assisted delivery practices. At Pernix, this means Costa Rica-based engineers operating in U.S. business hours, orchestrating AI agents under spec-driven development.
14-Day Engineering Sprint
The 14-Day Engineering Sprint is Pernix's risk-free engagement model. It delivers a working software milestone in 14 days using AI-assisted engineering. If the milestone does not meet the agreed specification, the client does not pay. The sprint includes discovery, specification, build, and delivery phases.
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