Vercel Eve Beginner to Pro Build & Deploy Agentic AI Agents
Published 6/2026
Created by Tom Phillips, WebDevEducation (Tom Phillips)
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Level: All Levels | Genre: eLearning | Language: English | Duration: 16 Lectures ( 1h 49m ) | Size: 2.5 GB

Use Vercel Eve AI to build and deploy agentic AI agents. With tools, skills, MCP, schedules, human approvals, + more!
What you'll learn
Build AI agents the filesystem-first way with Vercel Eve, where a folder of files is your agent
Connect an agent to a real database using typed tools that create and read records
Give your agent domain knowledge and procedures with on-demand skills
Integrate external services over MCP (Model Context Protocol)
Put risky actions behind human approval gates that appear as buttons your team taps
Schedule autonomous tasks with cron - work that runs every day with nobody present
Requirements
A free Vercel account (we'll set up everything else together)
No prior experience with AI agents or Vercel Eve required - we start from zero
DescriptionAI agents are everywhere, but most tutorials stop at a toy chatbot that can't do anything real. This course is different. You'll learn Vercel Eve, Vercel's open-source framework for building production AI agents, by building one complete, genuinely useful project, from an empty folder all the way to a deployed, multi-channel application.
The project you'll build
Your project is a real-world AI assistant for areal estate sales agency. The kind of software a business would actually pay for. From Slack, real-estate agents talk to your Eve agent in plain language to
add and update property listings (using custom tools)
search inventory against a buyer's exact Requirements
mark properties as sold
book viewings, and receive a daily "your viewings today" digest delivered automatically (using scheduled tasks)
see sales performance as charts generated on the fly
and write polished, accurate propertyarea Descriptions by researching the live web (using Exa MCP)
It's all driven by a single database, andevery feature is chosen to teach a specific Eve building block, so by the end, the patterns are yours to reuse on any agent, in any domain. The real estate app is just the vehicle; the skills transfer everywhere.
Why Vercel Eve, and why now
Eve is new, which means the developers who learn it now are early. It's built on Vercel, so you get serverless deployment, scheduled jobs, sandboxed compute, managed authentication, and model routing out of the box. And its filesystem-first design means adding a capability is as simple as adding a file.
What makes this course different
This isn't a string of disconnected demos. It'sone coherent project that grows module by module, the way you'd actually build software, and it doesn't dodge the hard parts.
The examples are deliberately real and useful, no throwaway projects, but they stay simple enough that you can follow along and build every piece yourself.
By the end you won't just understand Vercel Eve, you'll havebuilt and shipped a real, multi-channel AI agent, and you'll know how to design, secure, schedule, and deploy your own.
Who this course is for
Developers comfortable with JavaScript or TypeScript who want to build real, deployable AI agents
Anyone who's called an LLM API or used ChatGPT and wants to learn how to turn a model into actual software
Engineers who want an early, in-demand skill in the fast-moving AI agent space
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AI agents are everywhere, but most tutorials stop at a toy chatbot that can't do anything real.
This course is different. You'll learn Vercel Eve, Vercel's open-source framework for building production AI agents, by building one complete, genuinely useful project, from an empty folder all the way to a deployed, multi-channel application.
The project you'll build
Your project is a real-world AI assistant for a
real estate sales agency
. The kind of software a business would actually pay for. From Slack, real-estate agents talk to your Eve agent in plain language to:

add and update property listings (using custom tools)

search inventory against a buyer's exact requirements

mark properties as sold

book viewings, and receive a daily "your viewings today" digest delivered automatically (using scheduled tasks)

see sales performance as charts generated on the fly

and write polished, accurate property
area descriptions
by researching the live web (using Exa MCP)
It's all driven by a single database, and
every feature is chosen to teach a specific Eve building block
, so by the end, the patterns are yours to reuse on any agent, in any domain. The real estate app is just the vehicle; the skills transfer everywhere.
Why Vercel Eve, and why now
Eve is new, which means the developers who learn it now are early. It's built on Vercel, so you get serverless deployment, scheduled jobs, sandboxed compute, managed authentication, and model routing out of the box. And its filesystem-first design means adding a capability is as simple as adding a file.
What makes this course different
This isn't a string of disconnected demos. It's
one coherent project that grows module by module
, the way you'd actually build software, and it doesn't dodge the hard parts.
The examples are deliberately real and useful, no throwaway projects, but they stay simple enough that you can follow along and build every piece yourself.
By the end you won't just understand Vercel Eve, you'll have
built and shipped a real, multi-channel AI agent
, and you'll know how to design, secure, schedule, and deploy your own.