Noah Adelstein

Finding & Evaluating 1% GTM Engineers

International Growth @ Rippling & running The GTM Engineer

Davide Grieco

Head of Growth @ Clay

Alex Fine

Co-Founder at Understory

Ilija Stojkovski

CRO @ HeyReach

We'll cover what top hiring managers look for in GTM Engineering candidates and the best questions to ask

The key traits to look for in GTM Engineers

We'll dig into where leaders are looking to find best-in-class GTM Engineers

Where to find strong GTM Engineering candidates

What you can do if you're applying to GTM Engineering roles to stand out with the hiring team

How to stand out as a GTM Engineering candidate

Learn proven approaches for quickly improving AI applications.  Build AI that works better than the competition, regardless of the use-case.

ML Engineer with 20 years of experience

Airbnb

GitHub

DataRobot

AlixPartners

Hamel Husain

ML Engineer with 20 years of experience.

ML Systems & Applied AI Evals Researcher

Google

UC Berkeley

Stanford University

Shreya Shankar

ML Systems Researcher Making AI Evaluation Work in Practice

Cohort 5

Cohort 6

🚨 September 2026 cohort's material is completely refreshed. 🚨All students get:<ul><li>♾️ Unlimited access to future cohorts &amp; office hours: never worry about timing or missing new material.</li><li>🗄️ Lifetime access to all materials!</li><li>🤖 6 months of unlimited access to our new AI Eval Assistant (more info below).</li><li>🧑‍🏫 10+ hours of office hours to maximize the value of live interaction.</li><li>🏫 A Discord community with continuous access to instructors to get unstuck (even after the course!).</li></ul>---Do you catch yourself asking any of the following questions while building AI applications?1. How do I test applications when the outputs require subjective judgements?2. If I change the prompt, how do I know I'm not breaking something else?3. Where should I focus my engineering efforts? Do I need to test everything?4. What if I have no data or customers, where do I start?5. What metrics should I track? What tools should I use?6. Can I automate testing and evaluation? If so, how do I trust it?If so, this course is for you.All sessions are live and recorded.

Stop guessing if your AI works. Build the feedback loops that make it better.

How To Collect Data For Evals

Get immediate clarity and direction with Error Analysis

Implement Effective Evaluations

Master Architecture-Specific Eval Strategies

Run Evals In Production

Ensure That Evals Lead To High ROI

Engineers and PMs who ship prompt changes and hope nothing breaks. (You'll learn to measure impact before and after every change.)

Teams still spot-checking AI outputs by hand instead of measuring systematically. (You'll learn how build automated evals you can trust.)

Leaders who don't know where their AI is failing or where to invest resources. You'll learn how to systematically find &amp; prioritize issues.

Learn the skills + frameworks you need to ace interviews for senior leadership roles (Engineering Manager, Senior Manager, Team Lead). 

Director of Engineering, Career Coach

Amazon

Apple

Microsoft

Alex Kliotzkin

Director of Engineering and Career Coach

EM @ Stripe, Ex-Amazon Bar Raiseer

Stripe

Uzair Khan

Engineering Manager at Stripe and ex-Amazon Bar Raiser

Cohort 8

Cohort 9

As an engineer, you’ve mastered the coding challenges, system design, and behavioral interviews. But when it comes to Engineering Manager roles, the interview process is a different beast. You’ve likely hit a frustrating wall—interviews that feel like you’re doing everything right, but still no offer. You might not even know why you’re not breaking through.The truth? Engineering Manager interviews aren’t about discussing your experience—they’re about showcasing leadership, systems, and strategy in a way that resonates with the interviewer. To land the offer, you don't just need the right answers—you need memorable ones.This course is designed to bridge that gap and help you break through to land that Engineering Manager offer. We’ll focus on how to communicate your leadership capabilities, showcase your seniority, avoid red flags, and tailor your answers to what hiring managers are truly looking for. By the end, you’ll know exactly how to approach the interview process and confidently present yourself as the leader you know yourself to be.

Break Through the Interview Process and Land Your Engineering Manager Offer!

You'll experience mock interviews with real-time coaching feedback

You'll understand the exact hiring criteria for Engineering Manager roles

You'll learn how to convince the hiring manager (Director+)

You'll learn how to nail any behavioral question, even ones you haven't seen

You'll know exactly what the interviewer is looking for

You'll learn how to tailor your answers to go from good to memorable

Managers &amp; team leads that are getting interview opportunities but are unable to break through to land offers.

Senior Tech Leaders who have not interviewed for 7+ years and are looking for new roles (Sr. Manager, Director, VP).

Senior Software Engineers in lead roles looking to promote themselves to engineering manager by landing a new job.

Acquire and develop a critical skill for product managers who are leading and contributing to AI products.

GenAI Product Builder @ Google, ex-Meta

Marily Nika, Ph.D AI/ML

Product Manager AI&ML @ Google

Diego Granados

Senior Data, ML and GenAI Scientist

George Zoto

Senior NLP/AI Scientist

Cohort 4

“Does it work?”... “Is it good enough?”... “Can we ship it?”...How do you answer these questions for AI products? You’re responsible for “running evals” but what does that mean?How do you choose the right metrics, interpret fuzzy results, and make a confident decision?This course gives you a framework to do just that.<ul><li>Map user value to evaluation (eval) objectives so your metrics aren’t abstract. Define success then translate it into measurable criteria.</li><li>Choose metrics you can actually maintain: capability, safety, UX friction, latency, cost and “does this reduce support tickets or increase activation.”</li><li>Set ship/no-ship thresholds you can defend to leadership.</li><li>Build lightweight workflows that work in real teams: human review where it matters, automation where it lasts, documentation that drives decisions.</li><li>Consider domain constraints (e.g., healthcare safety) and know what to avoid: silent failures, misleading proxy metrics and tests that don’t reflect production.</li><li>Tie everything to ROI: impact vs unit cost, eval coverage vs reliability, and the minimum viable monitoring you need post-launch.</li></ul>Experience AI evals through a case-based approach with a real AI product that we evaluate together.

Eliminate uncertainty in shipping AI features

Make confident ship or hold decisions for AI features

Translate user value into clear evaluation goals

Choose the right metrics for capability, safety, UX, and cost

Set defensible thresholds leadership will trust

Build lightweight evaluation workflows teams can maintain

Navigate domain constraints and avoid common failures

PMs leading AI features, growth, or platform initiatives

PMs who partner with ML teams and want to set evaluation standards

PMs who need to make clear “ship or hold” calls without doing the engineering

Master the systems to stop micromanaging and transition from a referee to an orchestrator of a self-running team.

Founder at The Strength Hack

Daimler AG

Airbus

Audi

Toll Collect GmbH

Murk Creusen

Founder & Leadership Coach at Strength Hack

Founding Cohort

You cannot fix burnout by working harder. You have a matching problem.AI is making your team's hard technical skills obsolete faster than they can learn them. You cannot fix this "AI anxiety" or burnout by asking them to work harder. You don't have an effort problem; you have a matching problem.Most Engineering Managers spend 70% of their week trapped in the "Mediocrity Loop" - refereeing personality clashes, fixing broken handoffs, and watching their team's shared knowledge collapse as junior roles vanish. You're bleeding runway and morale.This 30-day accelerator gives you the system to break out. Using the Big Five (or CliftonStrengths) assessment, a proven framework, and the Strength Hack AI, you'll map your team's cognitive architecture and engineer the conditions for psychological safety - not just hope for it.In 4 weeks, you will:<ul><li>Stop Generalist Exhaustion: Identify energy leaks and delegate based on Cognitive Fit, not calendar space. </li><li>Engineer Swift Trust: Use the 6-dimension Matching Compass to translate friction into synergy.</li><li>Drive ROI: Transition from a reactive referee to a strategic orchestrator</li></ul>

Engineer Psychological Safety. Stop Refereeing Your Team.

Shortcut the "Storming" Phase to Engineer Swift Trust

Reclaim 70% of Your Week (Plug the Energy Leak)

Turn Personality Clashes into Solvable Data

Restore the "Who Knows What" Architecture Your Team Lost

Walk Away with a "Plug-and-Play" Facilitation Kit

To get ROI from this course, a real-world team (direct reports or agile squads) is recommended to apply the Matching Compass frameworks.

Team Leadership or Management Role

You must take the free Big Five test (or CliftonStrengths) before to map your personal psychological operating system.

Completion of a Baseline Assessment

The Overwhelmed Engineering Manager / Tech LeadYou lead a hybrid or remote team. You want a data-driven system, not another workshop.

The Ambitious Senior / Staff Engineer<blockquote>You're moving to people manager. You want proven frameworks to lead a team without micromanaging.</blockquote>

The People-Conscious CTO / CPO<blockquote>You own culture and delivery for 10–200 people. Your board wants AI readiness. You need L&amp;D that's credible.</blockquote>

GTM Engineering

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

Introduction and Panelist Backgrounds

Defining the GTM Engineer Role

The Single Most Important Skill

Interviewing for Ownership and Business Acumen

Key Traits: Obsession Over Pedigree

The GTM Engineer as a Creative Artist

Sourcing Talent: LinkedIn, WhatsApp, and Internal Hires

Onboarding Strategy: Immediate Ownership

How to Land a GTM Engineering Job

For Companies: When and How to Hire a GTM Engineer

Final Advice and Conclusion

Executives and senior leaders who set strategy, lead teams, and drive organizational outcomes.

Marketers who drive brand awareness, customer acquisition, and growth across channels.

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

Finding & Evaluating 1% GTM Engineers

What you'll learn

Why this topic matters

You'll learn from

Noah Adelstein

Davide Grieco

Alex Fine

Ilija Stojkovski