nWave

Make AI output consistent, reviewable, and safe to scale.

nWave is a free open-source workflow for AI-augmented engineering. It brings specs, quality gates, and PR-ready output into the AI loop so Tech Leads and Engineering Managers can reduce variance, protect standards, and show defensible results, without stalling delivery.

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THE PROBLEM

AI coding tools can help, but the wins aren't consistent.

  • Outcomes vary, so review load goes up.
  • Prompting becomes tribal knowledge; teams can't repeat results.
  • Variance increases rework and slows delivery.
  • Leadership wants impact, but you need a workflow you can explain and defend.
WHAT NWAVE IS

A workflow that brings AI into the SDLC with the same discipline you already expect from elite engineering.

  • Acceptance Tests as living documentation before code (shared templates).
  • Quality gates: tests/guardrails are part of the loop.
  • PR-ready output: changes are reviewable and auditable.
  • Designed to reduce variance, not just write more code.
WHAT YOU GET

A focused framework you can try in one repo

Assets that make results measurable and shareable internally.

  • A minimal wedge workflow your team can run in normal delivery.
  • Automated workflows that reduce prompting fragmentation.
  • A prerequisites + setup checklist (so time-to-first-value is predictable).
  • A definition of success + what we'll measure (so results aren't opinions).

What happens in the first guided session

(so you know it won't drag on)

  • We set up the workflow in your environment.
  • We implement 1–2 core agents (only what you need to start).
  • You leave with a concrete artifact your team can reuse (e.g., spec → tests → PR checklist) plus a simple measurement plan.
SERVICES

Bounded, outcome-led workshops to expedite performance

Audit

Readiness + Evaluation Plan

A scoped, low-friction evaluation you can run without derailing delivery.

Includes:
  • Current-state snapshot
  • Wedge selection
  • Prerequisites
  • Success metrics
  • Evaluation economics guidance
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Enablement

Implementation Sprint

A working setup in your environment plus the artifacts to repeat it.

Includes:
  • Hands-on implementation
  • Team session
  • First evidence pack draft (templates in use + before/after snapshot)
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FAQ

Constraints + evaluation questions

Now: Claude Code-first. Soon: ChatGPT/Codex.

First visible win in the first guided session, then expand only if it's worth it.

The workflow produces reviewable artifacts (specs, tests, PR-ready changes) and a clear measurement plan so outcomes are defensible.

One repo, one motivated engineer, and a Tech Lead who can sponsor the workflow for eligible work during the evaluation window.