---
type: concept
title: "Agent Development Lifecycle"
description: "A repeatable blueprint for taking an agent from planning and a minimal proof-of-concept through database, code, UI, testing, deployment, and evaluation."
tags: [blueprint, planning, mvp, evaluation]
videos: [learn-90-of-building-ai-agents-in-30-minutes, im-hosting-a-huge-ai-hackathon-competition, revealing-my-complete-ai-agent-blueprint]
created: 2026-07-21
updated: 2026-07-21
---

# Agent Development Lifecycle

The agent development lifecycle is the ordered path from an idea to a production agent. Cole frames it as a single walkthrough: "I want to give you an overview a step by step of my entire process for building AI agents starting from the basics and going all the way to having your agent in production." [0:00:31] The lifecycle exists to stop builders from over-complicating the early stages, because "those who are the most successful are the ones who don't over complicate" it. [0:00:00]

It begins with **planning**, the highest-leverage and most-skipped step: "it can save you hours and hours of going down the wrong rabbit holes if you are actually doing some planning up front so ask yourself these questions write out your answers in a document." [0:02:43] From there the build stays deliberately minimal, wiring up the [four core components](./agent-core-components.md) as a proof-of-concept before adding a database, application code, and a UI. Only after the agent works do you layer on the production concerns: "the first seven here you definitely want to do it in that order but now what we have next here is setting up monitoring for your AI agent." [0:11:20] The ordering matters. Simplicity first, infrastructure last.

The discipline is to defer complexity until it earns its place: "you need to keep things simple when you're first creating any agent really any software at all." [0:08:12] Judged as a finished product, a good agent is measured on more than whether it runs. The hackathon rubric captures the full bar: "we've got Innovation how novel is the idea then we've got functionality how well the agent actually works usability the ease of use and implementation and then we've got impact does it actually solve a real world problem," [0:05:37] plus "presentation how well you present your agent through extensive documentation and even a video if you want." [0:05:56]

## Prerequisites

- [What Is an AI Agent?](./what-is-an-ai-agent.md) - know what you are building before you plan it.
- [The Core Components of an Agent](./agent-core-components.md) - the four parts assembled at the proof-of-concept stage.

## Builds on

- [Rapid Prototyping](./rapid-prototyping.md) - the minimal proof-of-concept that opens the lifecycle.
- [Vibe Coding](./vibe-coding.md) - a fast way to stand up the early build.

## Related

- [Model Selection](./model-selection.md) - an early planning decision.
- [Agent Deployment](./agent-deployment.md) - the "into production" end of the path.
- [Agent Evaluation](./agent-evaluation.md) - how you know the agent actually works.
- [Agent Observability](./agent-observability.md) - the monitoring layer added after the first seven steps.
- [Production-Grade Agents](./production-grade-agents.md) - the deferred complexity the lifecycle ends on.
- [Agents That Build Agents](./agents-that-build-agents.md) - A meta-agent whose specialty is generating, iterating on, and eventually running other AI agents on demand, so the agents it produces become reusable sub-agents themselves.
- [Google ADK (Agent Development Kit)](../entities/tools/google-adk.md) - Google's minimalistic agent framework giving full control over prompting and tooling, with sandboxed code execution and one-command deployment to Google Cloud.

## Sources

- [Revealing my COMPLETE AI Agent Blueprint](../sources/revealing-my-complete-ai-agent-blueprint.md) - "[0:00:31] I want to give you an overview a step by step of my entire process for building AI agents starting from the basics and going all the way to having your agent in production"
- [Learn 90% of Building AI Agents in 30 Minutes](../sources/learn-90-of-building-ai-agents-in-30-minutes.md) - "[0:00:54] even more importantly, I want to talk about what you shouldn't focus on at first because otherwise, you're over complicating it"
- [I'm Hosting a HUGE AI Hackathon Competition](../sources/im-hosting-a-huge-ai-hackathon-competition.md) - "[0:05:37] we've got Innovation how novel is the idea then we've got functionality how well the agent actually works usability the ease of use and implementation and then we've got impact does it actually solve a real world problem"
