Run a governed AI engineering team in a box

Most teams adopting AI agents in 2026 are making the same mistake: they're plugging agents into human-optimized workflows and wondering why the results are chaotic.

The AI Velocity Pod Starter Kit is the workflow layer we wish existed when we started building with agents 18 months ago, now open-sourced after being battle-tested across 300+ products in 21 countries.

What's inside:

• Agent task definition templates = structured formats for breaking product requirements into agent-sized tasks with unambiguous success criteria and explicit scope boundaries (the #1 thing that separates reliable agent output from chaotic output)

• Governed workflow diagrams = how to structure human oversight checkpoints that don't become bottlenecks: where agents run autonomously, where humans review, where nothing proceeds without approval

• Agentic QA checklist = the 23-point regression and coverage checklist our QA pipeline runs against every AI-generated PR before human review

• Scope definition canvas = the discovery template we use before every fixed-price engagement to define "done" in a way agents can actually execute against

Why free? We built Ailoitte on the belief that engineering teams win when they ship outcomes, not when they bill hours. This kit reflects that. Use it, fork it, improve it.

For teams that want the full AI Velocity Pod structure with a senior engineering team already built around it: ailoitte.com/ai-velocity-pods