Sathyan Nandagopal

AI Product Leader & Advisor. Shipped 6 AI products; built '5D Method' & Aegis

A Content Pipeline That Won't Ship Junk

Learn to score AI output across explicit dimensions so quality becomes a gate you can defend, not a gut call.

Turn "the output feels off" into a number

Watch a draft get accepted or iterated against a threshold — "done" is the score clearing the bar not Agent's opinion

A scored refine loop, live

Walk away with the caps and human-gate pattern that stop a weak draft from ever reaching a user

Guardrails so nothing sub-threshold ships

Eliminate uncertainty in shipping AI features

GenAI Product Builder @ Google, ex-Meta

Marily Nika, Ph.D AI/ML

Senior Data, ML and GenAI Scientist

George Zoto

Senior NLP/AI Scientist

Cohort 5

August-2026

“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.

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

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

Build and ship a real product with Lovable, Supabase, Claude Code, n8n, and Hermes, then evaluate it with TRACE, across 4 hands-on weeks.

Cohort 3 [live]

PhD in ML | Google AI Accelerator Alum

Google

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 2 [ongoing]

Cohort 5 [upcoming]

Stop waiting on engineering. Ship your own AI product in 6 weeks.In six weeks, you build and ship one real AI product, no code required. You do not write code. You learn to direct it, verify it, and ship it, the skill that outlasts every tool.<ul><li>A live full stack app, built from a brief, not a spec nobody reads</li><li>Real data and user login, wired up without writing it by hand</li><li>A feature you direct an AI coder to build for you</li><li>Automation and a working agent, connected to tools you already use</li><li>Evals with TRACE, so you can prove the thing is actually good</li></ul>You will work with Lovable, Supabase, Claude Code, n8n, and Hermes. Most students arrive with the same problem: the idea was there, but shipping it meant waiting on engineering. You leave with a product you actually shipped.A limited number of need-based scholarships are available for applicants facing real financial hardship. <a target="_blank" rel="noopener noreferrer nofollow" class="underline underline underline-offset-2 decoration-1 decoration-current/40 hover:decoration-current focus:decoration-current" href="https://theaiinternship.com/scholarship">See if you qualify.</a>

PRICE GOES UP TO $1,999 IN 24 HOURS. OFFERS CAN'T BE COMBINED.

Ship a working product from a brief, not a spec

Direct AI to build, without writing code

Automate the work, and operate a live agent

Evaluate an AI product like a leader, with TRACE

Carry one product from idea to shipped

Lead an AI build instead of waiting on one

The one thing you really need. If you have a product or a process in mind and the drive to ship it, you are ready to start.

Curiosity and something you want to build

This is a no-code track. You will direct AI tools to build, not write code by hand. Comfort using everyday software is all you need.

No coding background required

We use Lovable, Supabase, Claude Code, n8n, and Hermes. Most have free or low-cost tiers. The pre-check session gets your accounts working so no live time is lost.

The tools, set up before we start

The PM who wants to ship, not just spec. You are done writing requirements and waiting on a backlog. You want to build it yourself.

The founder who needs a product, now. No technical co-founder, no budget for devs yet. You want a live product in front of users in weeks.

The operator automating real work. You see the manual processes everywhere, and you want to automate them.

Every AI idea you drop costs your team more than the idea is worth

Helping tech leaders lead with less

Electronic Arts

Amazon

Salesforce

Lightspeed Commerce

Globant

David Fung

SE leader turned leadership coach | 20+ years in enterprise SaaS

AI Idea Workshop Cohort 1

You see the AI move before everyone else. So you share it, in a standup, in Slack, or in the hallway. Another idea, another direction. You're keeping the team ahead.But from where they sit, the ideas blur. Which of these is real? What do I drop to chase it? Soon your team is managing your flood of ideas instead of shipping, and your best thinking lands as noise.The problem is that every one of your ideas reaches an audience.In this hands-on workshop, you'll build a triage filter that decides which AI ideas reach your team, which wait, and which you hand off. Then the harder part: a filter only holds if you know why you override it. You'll run a short diagnostic on the one idea you can't let sit, and name the belief underneath it. That belief is why most systems fail.You'll walk out with:• A filter you can run on any idea in under a minute • The belief that drives you to hit send, and the tell that exposes it • An if-then plan that makes it stick past this weekYou build this live, on your own real ideas. The method comes from my 23 years in tech and speaking with 100+ leaders on my podcast. Walk in with a habit you can't see. Walk out with a filter that does the subtracting for you.

Stop dropping every AI idea on your team. Build a filter that decides which reach them, and uncover why you override it.

Build a three-route filter (wait, trade, designate) you run in 60 seconds

Diagnose the one idea you can't let sit, and name the belief beneath it

Write an if-then plan so the filter holds past the workshop

<blockquote>Engineering leaders (VP, Director, CTO) whose offhand AI ideas land as mandates and quietly reshuffle the team's priorities.</blockquote>

<blockquote>Staff+ engineers and tech leads who flood Slack with AI ideas faster than the team can absorb or act on them.</blockquote>

<blockquote>Sales engineers, solutions architects, and technical PMs who relay every new AI move inward, blurring what's actually a priority.</blockquote>

You leave with deployable systems and documented architecture — not slide decks.

AI & DeepTech Leader & Entrepreneur

Hike

Yatra

Apparel Group

Oracle

Bytelearn

Dr Ankur Narang

Three decades building HPC and AI systems processing billions of transactions

Enterprise AI Agent Architect

Adda247

Mobileum

Kush Khurana

AI product and deep-tech builder, Visiting Professor at Ashoka University

AI Systems Architect & Leader

Stryker

Samsung

Dr Aveek Brahmachari

Stryker Senior Staff Engineer; IIT-ISM, USF PhD; ex-DRDO, Samsung

Founding Cohort

A 4-week intensive for engineers mastering autonomous cognitive workflows — from cost compression and self-correcting loops to revenue-scaling agents that turn AI from a cost center into a profit driver.<a target="_blank" rel="noopener noreferrer nofollow" href="https://deepcorexlabs.com/courses/production-ai-agents">Course Webpage</a>Build The Economic Engine of Agents: This goes beyond the technical deep-dive. We focus exclusively on production-grade impact—engineering the measurable business outcomes that deliver exponential ROI.20x ROI via Cost CompressionAchieve 20x return on investment by reducing operational overhead — replacing manual human-in-the-loop processes with self-correcting agentic loops.100x ROI via Revenue ScalingUnlock up to 100x return on investment by deploying agents that solve high-intent, real-time use cases — turning AI from a cost center into a primary profit driver.Achieve 5–10x lower AI infrastructure costsToken routing, caching, and cost modeling that saves six figures at scale.Systematic evaluation capabilityInternal eval infrastructure — catch regressions before users do.De-risked architecture decisionsBuild-vs-buy calls backed by production data, not vendor pitch decks.Reusable patterns across teamsOne cohort creates blueprints your entire engineering org can adopt.

Deploy Agentic systems that deliver 20x–100x return on investment.

Ship a functioning agent with structured tool use and state management.

Ship a retrieval pipeline that's grounded, verified, and citation-backed.

Ship cost controls and failure recovery into your agent.

Ship your capstone with full eval harness and deployment pipeline.

<h3>Engineering &amp; Product Leaders</h3>Responsible for shipping AI features. Need production patterns beyond prompt engineering and API wrappers.

<h3>Technical Founders &amp; CTOs</h3>Built the prototype yourself. Need it reliable enough for paying customers and investor due diligence.

<h3>Lead Developers</h3>You're the person who makes the AI system actually work — and keeps it working when inputs get messy.

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.

Operations professionals who optimize processes and manage day-to-day business functions.

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

Building autonomous AI agent systems that take actions, use tools, and orchestrate multi-step workflows.

Measuring and evaluating AI model performance, quality, and reliability for production use cases.

Automating professional workflows with AI tools — productivity, operations, and task automation.