---
title: "Agentic Engineering: A Practitioner's Playbook"
url: https://daily.dev/posts/agentic-engineering-a-practitioner-s-playbook-9nmcufzid
source_url: https://domino.ai/blog/agentic-engineering-practitioners-playbook
type: article
source: "Domino Data Lab"
published: 2026-06-03T16:30:01.268Z
updated: 2026-06-03T16:31:03.227Z
tags: ["ai-coding", "mlops", "tdd"]
reading_time: 25
upvotes: 0
comments: 0
language: en
---

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# Agentic Engineering: A Practitioner's Playbook

**[Domino Data Lab](https://daily.dev/sources/ddl)** · 25 min read · 0 upvotes · 0 comments

## Summary

Agentic engineering is a structured methodology for building AI-assisted software that actually reaches production, contrasted with vibe coding which produces demos that stall. The core framework has four pillars: spec-first design (writing a detailed specification before any prompt), the Ralph loop (an 8-step structured prompt cycle covering audit, planning, self-critique, test-first development, implementation, diagnosis, production readiness review, and iteration), layered testing (unit, integration, and end-to-end), and cross-model validation. Code generation is explicitly step 5 of 8, emphasizing that human thinking and verification are the highest-leverage activities. The approach is especially relevant for data scientists in regulated industries like life sciences and financial services where prototypes must meet audit and compliance requirements.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://domino.ai/blog/agentic-engineering-practitioners-playbook>

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- [Agentic Engineering](https://daily.dev/posts/agentic-engineering-vu5lypi1u) · Addy Osmani · 380 upvotes · 11 comments

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Tags: [#ai-coding](https://daily.dev/tags/ai-coding), [#mlops](https://daily.dev/tags/mlops), [#tdd](https://daily.dev/tags/tdd)

[View this post on daily.dev](https://daily.dev/posts/agentic-engineering-a-practitioner-s-playbook-9nmcufzid)
