Dean Bushmiller

Co-creating cyber security experts since 1999

AiFDSE - Ai Field Deployed Security Engineer

Asses your current standing in 4 core skills

Current skills

Consulting components

Depth of detail and possible learning programs

Ai components

Security components

Programming components

Build the technical judgment and customer-facing skills to take an AI agent from ambiguous requirements to production.

AI Educator to 145k Linkedin 

Meri Nova

Technical founder, 145k LInkedin community

Senior AI Engineer, Investor & Advisor

Hai Nghiem

Investor | Builder

V3 (Cohort 4)

AI Forward Deployed Engineer

Forward Deployed AI Engineers work directly with customers and stakeholders - to uncover the real problem, - turn ambiguous requirements into a build plan, - make pragmatic technical decisions, - and ship a solution into production. In this 4-week hands-on bootcamp, you will practice the full lifecycle of Forward Deployed AI Engineering. You will learn the foundations behind the modern AI agentic projects, build with a practical full-stack agent stack, gather and prioritize requirements, work through realistic customer scenarios, and take a final project from proof of concept to production. This is not a collection of disconnected AI tutorials, but a guided simulation of the work an FDE is expected to do. Taught by leading AI Forward Engineering firm in Canada, <a target="_blank" rel="noopener noreferrer nofollow" href="https://www.agiventures.ca/">AGI Ventures.</a>

Go from building AI demos to delivering AI systems people can actually use.

Understand modern AI agents and their harnesses

Be job-ready for AI FDE roles

Navigate difficult conversations with multiple stakeholders

Compre and make trade-offs in making architectural decisions

Move from proof of concept to production

Software, product, AI, and ML engineers who can build applications and want to move into applied AI or forward deployment.

Solutions architects, technical consultants, and technical PMs who want stronger requirements, stakeholder, and production-delivery skills.

Career switchers, founders, and professionals with development experience who need a credible path from customer problem to production.

The skills you need to succeed as an AI Forward Deployed Engineer in production environments.

Owner/CEO, AI Makerspace

AI Makerspace

AI Fund

FourthBrain

University of Dayton

Dr. Greg Loughnane, Ph.D.

Building industry-leading AI training for engineers and teams since 2021

Author, LLMs in Production

Matthew Sharp

Matt Sharp is a seasoned leader and professor in AI, MLOps and Engineering. 

Information Systems Engineer at Adobe

Tyler Laughlin

A background in BI, data science, machine learning, and cloud-native apps.

Cohort 1

Cohort 2

This is a live class with real experts and a hard limit of 30 people. Please see "Who this course is for" before applying.AI Forward Deployed Engineering today refers to the industry-relevant skills needed to scope customer problems, to build and test AI prototypes with users, to deploy prototypes to existing production environments, and to secure, operate, and improve production applications at scale that generate real ROI.Our <a target="_blank" rel="noopener noreferrer nofollow" href="https://aimakerspace.io/the-aie-bootcamp-changelog/">curriculum changelog</a> shows the evolution of our flagship course (previously <a target="_blank" rel="noopener noreferrer nofollow" href="https://maven.com/aimakerspace/ai-eng-bootcamp">The AI Engineering Bootcamp</a> - <a target="_blank" rel="noopener noreferrer nofollow" href="https://aimakerspace.io/the-ai-engineering-bootcamp-book/">textbook</a> coming soon) from 2024 to today. We enrolled over 538 students in the first 10 cohorts, certifying 272 of them as <a target="_blank" rel="noopener noreferrer nofollow" href="https://aimakerspace.io/graduates">Certified AI Engineers</a>.Our v1.1 (Cohort 11) course has expanded the curriculum and has a higher, more specific bar for admission than ever before. It will help you build 🏗️, ship 🚢, and share 🚀 your way through the vast AI product-engineering landscape by focusing on a single problem that matters to your company.AI Makerspace is the only certified enterprise training partner of <a target="_blank" rel="noopener noreferrer nofollow" href="https://www.linkedin.com/posts/a-meaningful-milestone-today-for-ai-makerspace-ugcPost-7460037108691476481-0wES?utm_source=share&amp;utm_medium=member_desktop&amp;rcm=ACoAAAOfOE4BdOGPD97rGOwB0qdCpNDB_wvyxsI">Andrew Ng &amp; Kirsty Tan's AI Aspire</a> on Maven. Learn more about custom offerings <a target="_blank" rel="noopener noreferrer nofollow" href="https://aimakerspace.io/agentic/">here</a>.

The industry-standard certification for production AI FDEs.

Scope problems & their solutions better than Anthropic & OpenAI FDEs 

Apply best-practices from MVP to production

Understand why open weights matter and how to use them

Embrace evals as the language that connects business to engineering

Understand why security and adversarial techniques are first-class issues

Understand scaling and what it takes from product and engineering perspectives

VSCode with GitHub Copilot (or equivalent) should be your daily driver already.

Git & Python mastery, Coding Agent (e.g., Claude Code or Codex) proficiency

If you have never held a job where you contribute code to a production software environment, this class is not for you.

Experience writing code that is deployed to production software environments

This means an understanding of training, testing, and inference for various model architectures, including LLMs

Machine Learning & Deep Learning fundamentals

Engineers working full-time inside a company that are prepared to bring a real use case from work and iterate on the AI solution weekly.

If you are a startup founder, consultant, big tech employee, or currently unemployed, this course is likely NOT for you.

If you are unable to get sponsorship from your company to take this course, this course is likely NOT for you.

The #1 FDE Skill Isn't AI or Coding. It's Storytelling!

Top 1% AI Expert, Ex-@Google, Microsoft

Google

Microsoft

The Wharton School

Intel

Priyanka Vergadia

AI & Cloud leader @Microsoft @Google | Visual Storyteller | TED Speaker

I've built and hired FDE teams, DevRel and Solutions Engineers for 10+ Years. This workshop teaches what hiring managers look for beyond coding!As a Software Engineer or AI Engineer, you can build agentic workflows and ship AI apps in days. That's not what makes a good FDE.What kills FDE careers early: a CTO wants faster deployments, you jump to CI/CD tooling. The engineering team is uncomfortable you're there, you don't notice. Someone hands you a pre-scoped project, you build without asking if it's the right problem.FDE roles are everywhere: Google, OpenAI, Anthropic are all building this function. But engineers getting those offers aren't winning on technical chops. They ask questions, keep going past the first answer, figure out who does the work, who feels threatened, what's politically doable. Not just tech. People. Org charts. They leave with scoped projects the customer actually wants built.In this workshop you will:<ul><li>Run real discovery conversations with enterprise customers</li><li>Navigate stakeholders who don't all agree and some who don't want you there</li><li>Turn a business goal into a scoped project you can deliver</li></ul>AI and code got you this far. This gets you to FDE.

Go from engineer to FDE with the SCOPE Method: uncover problems, manage politics, define outcomes, influence without authority.

STUDY & CONNECT: Run executive discovery that uncovers the real business problem

OBSERVE: Double-click past surface-level asks to find the real problem

PEOPLE: Navigate stakeholder politics and influence without authority

EXECUTE: Scope projects tied to outcomes and present with confidence

Software Engineers: You ship production systems but have never run customer discovery or scoped a project from a vague exec ask.

Solutions Architects Consultants: You have stakeholder skills but need the framework to own outcomes and shape projects, not just sell them.

Technical Product Managers: You define what gets built but have never embedded with a customer's engineering team to ship it yourself.

Practice the three skills that make senior people listen: a sharp narrative, command of the room, and composure under pressure.

PhD in ML | Google AI Accelerator Alum

Amazon Web Services

OpenAI

NVIDIA

Dr. Aki Wijesundara

AI Founder | Educator | Google AI Accelerator Alum

Exited AI Founder | Founder, TAI Labs

Boston Consulting Group (BCG)

McKinsey & Company

Manu Jayawardana

AI Advisor | Founder, TAI Labs

Cohort 3

September Cohort

You’ve done the courses. You’ve built the RAG chatbot. But when a hiring manager opens your GitHub, nothing proves you can take a messy real problem to something reliable, measured and explainable. That is what AI Engineer, Forward Deployed Engineer and AI PM interviews screen for, and demos don’t show it. In 3 weeks you’ll fix that. You’ll pick a realistic business problem, build an agentic system around it with Claude Code, prove it works with a proper eval report, and package it into a portfolio piece written for the role you want. <ul><li>Week 1: scope a real problem and ship a working v1 </li><li>Week 2: build a golden set, a failure taxonomy and before/after numbers </li><li>Week 3: public repo, demo video, case study, demo day with a hiring panel </li></ul>One core build, three role tracks. AI Engineers leave with an eval harness and architecture record. FDEs leave with a discovery doc and deployment plan. AI PMs leave with a PRD and metrics plan. TAI courses are built and taught by practitioners who ship agentic systems for real clients every week. 10,000+ professionals trained. Alumni from OpenAI, Google, Meta, McKinsey and BCG. The app is the evidence. The proof is the product.

Ship three production-grade AI projects with evals and a story in 3 weeks.

Scope a portfolio project hiring managers actually want to see

Build a working AI system

Prove it works with a real eval report

Package it into a portfolio piece that gets interviews

Ship the role-specific artefact interviewers ask for

Present to a hiring panel on demo day

You should have built at least one LLMpowered project before. This course is about proof, not first steps

One AI course or bootcamp completed

Engineers write code. PMs spec and drive a Claude Code build. Either path works, but you must be able to run a project locally.

Comfortable with Python or TypeScript, or driving Claude Code

You'll need both before Session 1. Setup takes about 15 minutes, and course-wide API costs run a few dollars.

A GitHub account and an Anthropic API key

The Engineer moving into AI. Has done a bootcamp or two. Needs proof of production judgment, not another demo.

The aspiring Forward Deployed Engineer. Can build, but has no customer-facing deployment story to tell in interviews

The PM targeting AI roles. Expected to spec and evaluate AI features. Needs a shipped example with real metrics

Agentic AI

Coding with AI

AI Workflows

Claude Code

OpenClaw

Vibe Coding

AI Evals

AI Transformation

RAG & Search

AI for PMs

AI for Engineers

AI for Designers

AI for Marketers

AI for Founders

Product Sense

Product Discovery

User Research

Prototyping

Growth

Analytics

Tech Foundations

Strategy

Influence

Leadership

Career Growth

Machine Learning

LLM Ops

Context Eng

Security

System Design

Figma

Design Systems

Visual Design

Design Strategy

Automation

Content Marketing

Demand Gen

Go-to-Market

Product Marketing

Positioning

Social Media

Brand

B2B Marketing

SEO & AEO

AI for Leaders

AI Governance

Communication

Management

People Operations

Exec Presence

Storytelling

Goal-setting

Personal Brand

Fundraising

Everyone

Operators

Data Scientists

Business Analysts

User Researchers

Customer Success

Project Managers

HR Professionals

Sales People

Lawyers

Finance

Investors

Real Estate

Educators

Creators

Engineers and engineering leaders who build, deploy, and scale software systems.

Applying AI tools and techniques to professional workflows — assign alongside more specific AI topics.

Getting promoted, navigating job transitions, and advancing to the next level in your career.

Securing software systems — application security, threat modeling, authentication, and infrastructure protection.

AiFDSE - Ai Field Deployed Security Engineer

What you'll learn

Why this topic matters

You'll learn from

Dean Bushmiller