Google

Amazon Web Services

Suncorp Group

Great Eastern

Jason Tan

Bootstrapped AI Founder | Author & Speaker | AI Product & Business Advisor 

How to Build an AI Agent to Lead Sales Research

Gather and enrich raw contact and company data automatically. Feed the AI agent exact context to process data accurately

Collect and enrich lead data automatically

Build an engine to review headcount and growth metrics. The AI agent evaluates contacts to verify decision makers.

Build an evaluation engine for prospects

Run evaluations continuously to process hundreds of leads daily. A 3-person team can execute like a 40-person one.

Scale your top of funnel capacity

Leave with a working agentic analytics system on your machine, a polished analysis, and the patterns and frameworks to make it all yours.

Principal Data Scientist @ Ontra 

Shane Butler

Principal Data Scientist @ Ontra | Ex-Stripe, Nextdoor, PwC, Appfolio

Data Science Leader |Ex-Microsoft

Sravya Madipalli

Data Science Leader@Superhuman (Prev. Grammarly)| Ex-Microsoft, eBay, Nextdoor

Head of Data @ Ontra AI | Ex-LinkedIn

Hai Guan

Head of Data @ Ontra | Ex-Nextdoor, LinkedIn, Pinterest, Meta

Bootcamp 4

Cohort 5

Anyone can get AI to produce analysis now. The hard part is knowing whether it is right.This is a five week, hands on course where you build an agentic analytics system in Claude Code, and then do the thing almost nobody teaches: prove it works.Weeks 1 and 2 you build. You set up your own environment, write your first skill, design and build a multi agent system, integrate it into a production repo, and connect it to your team's tools through MCP.Weeks 3 and 4 you make it trustworthy. You measure reliability across repeated runs, triangulate a question across independent methods of analysis, build ground truth, align an LLM judge to human labels, trace every answer back to the query that produced it, and engineer the context that makes the system correct on your company's metrics.Week 5 you put it to work. You swap the model underneath it, cross check one model against another, and turn the system into value your company can see.Ten live sessions, two hours each, with three instructors in the room. Every recording is yours to keep. Free course retake. Private AI Builders alumni community. No coding background required, no Python or SQL is ever written by you.

Build AI Analysts that do the work and prove the numbers are reliable. No code.

Build a multi agent AI analyst system from scratch

Integrate your system into a production analytics repo

Build an eval suite that proves your analyst is right

Align an LLM judge for work that has no right answer

Engineer the context that makes the system correct

Swap to open source models and triangulate across them

Product managers who are tired of waiting in the data team's queue. Stop waiting. Analyze it yourself.

Data scientists who want to multiply their output. You know how to do the analysis manually. Now automate it.

Engineers who want to make data-driven decisions without hiring a data team.

Future-proof your finance career by mastering AI tools, predictive modeling, and autonomous agents that handle real finance workflows.

Professor & AI Expert (1M+ Students)

Microsoft

General Motors

Samsung

HSBC

Dr. Ryan Ahmed

Professor, AI expert, & YouTuber who has taught 1M+ learners worldwide.

Director of Engineering @Launchpad.AI

Nike

Levi's

Mr. Cooper

Launchpad

Kukesh Kodess

Director of Engineering with 7+ years building cutting-edge AI/ML systems

Cohort 3

Cohort 4

⭐Over 1 million students taught across 160 countries. Has trained teams inside RBC, HSBC, TD Bank, BNY Mellon, Jefferies &amp; Barclays. Capped at 50 seats. 90+ alumni rated it 4.8/5: Bank of America, American Express, UBS &amp; The LEGO Group. 📩 Questions? Email Ryan: <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="mailto:ryan.ahmed@stemplicityschool.com">ryan.ahmed@stemplicityschool.com</a>You already use AI. It still hasn't taken one recurring task off your plate.93% of finance teams use AI. Only 21% say it changed how they work. The gap isn't better prompts. It's that nobody taught you to build an AI Agent: something that opens your files, runs your process and hands you a finished deliverable while you're in a meeting.Four weeks from now, the work still gets done. You just stop being the one doing it.<ul><li>Finance: close, variance commentary, reconciliations, forecasts, board packs</li><li>Marketing: campaign reporting, competitor monitoring, content ops, attribution</li><li>Sales: prospect research, CRM hygiene, call follow-ups, RFPs, pipeline forecasts</li></ul>Built live on your own files in Cowork, Claude Code, Codex and Copilot. You leave with 8 working agents, a capstone you can demo and a certification. No coding or technical experience needed.

Build AI Agents That Run Your Finance, Marketing & Sales & Get Certified

Build your first AI agent in week 1 with Claude Cowork, with zero coding

Turn messy files into branded PowerPoint, Word and PDF deliverables

Build Excel models and financial analysis with AI agents, not formulas

Forecast revenue, cash flow and risk with AI agents, no stats degree needed

Connect agents to HubSpot and your systems with MCP, then run them nightly

Ship a real end-to-end agent system and earn your certification

If you can use Excel and write an email, you can build Agents. Most alumni are CFOs, controllers, FP&A managers & marketers, not engineers.

No coding or technical experience required

You build your own AI agents starting in week 1. Sample workflow and data are provided if you can't bring your own.

A real workflow that you want to automate

<blockquote>CFOs, Controllers &amp; FP&amp;A Teams who want to automate the close, variance commentary, reconciliations, forecasts and board-ready reporting.</blockquote>

Financial Analysts &amp; Accounting Teams who want to automate reconciliations, transaction reviews, tie-outs and recurring monthly reporting.

<blockquote>Marketing &amp; Sales Leaders who want to automate campaign reporting, competitor monitoring, prospect research, CRM hygiene and RFP responses.</blockquote>

Build AI Agent Skills that Actually Work - 3 Hours Hands-on Workshop

Product Leader and Super IC at Google

Disney+ Hotstar

Zynga

Anshumani Ruddra

Product Super IC at Google with 22+ years crafting experiences and blockbuster products

Cohort 07

Cohort 08

Most product builders use AI agents the same way they used search - typing queries and hoping for the best. That's leaving most of the value on the table.The teams pulling ahead aren't using better prompts. They're teaching their agents. Agent Skills are reusable, testable instruction sets that tell AI agents exactly how to handle specific workflows: your deployment process, your code review standards, your team's edge cases. Write one skill well, and every agent on your team benefits from it, every time, automatically.The problem: nobody is teaching product builders how to create them. Most documentation is written for a narrow technical audience, and the tooling is fragmented across Claude Code, Codex, and Gemini.In this hands-on workshop, you'll go from zero to a working skill installed in your own agent: one that reflects your real workflows, not generic templates. You'll also learn how to evaluate and improve skills systematically, so they get better over time instead of drifting.If you build or are hoping to build products with AI agents: this is the highest-leverage skill you can develop right now.

🤖 Learn to build procedural Agent Skills, transforming your professional mindset from solo prompter to manager of elite AI agents

Shift to an AI Management Mindset

Build Custom, Reusable Agent Skills

Leverage the Open-Source Ecosystem

Evaluate and Iterate for 10x Output

Product Managers: who use Claude Code or Codex daily but rely on ad-hoc prompts - and want repeatable, team-shareable AI workflows.

Entrepreneurs &amp; Founders: building AI-native products who need their agents to encode business logic, not just generate code on demand.

Tech Executives &amp; Product Leaders: who want their teams to stop reinventing prompts and start shipping a shared skills library.

Watch a campaign agent built live using Claude or ChatGPT, in 90 minutes.

Founder & CEO, Perry Co | AI Advisor

Stanford University

Section

Northstar Travel Group

Tahnee Perry

I help marketing teams and agencies work smarter with AI

Founder & CEO, Design Method 

LoveShackFancy

Kosas

Joseph Joseph

Kmart

Toyah Perry

I help brands, agencies and creative teams use AI to create creative faster.

Cohort 1

Cohort 2

Competitive research takes half a day. A content brief needs three rounds of editing. Design assets take weeks to produce.These tasks are consuming the time your team should spend on strategy.In 90 minutes, you watch us build the AI agent that takes you from research to brief and the system that designs your assets in minutes instead of weeks.👉 The agent scans your competitive set, surfaces what your audience is searching for and produces the insight clusters your strategy needs.👉 The agent then turns the research into a strategy document with objective, audience segment, core message and channel plan.👉 And then converts that into a campaign brief you can use to produce your final assets.This is a watch-and-learn session.You leave with:<ul><li>The Claude &amp; ChatGPT setup guide</li><li>Step-by-step instructions to build the campaign agent in your own account</li><li>The seven skill files the agent uses to run research, strategy and brief end to end</li></ul>

See a Claude agent run a full campaign from research to design brief, and leave with the templates to rebuild your own.

A competitive research workflow the agent runs in under ten minutes

A strategy document the agent builds from your research

A campaign brief the agent hands off to your design platform

Confidence in what a production-ready AI content system looks like end to end

You own the campaign development and you're tired of the gap between what AI produces and what's publishable.

You run an agency, and you're tired of re-prompting Claude endlessly to generate client outputs.

You've used Claude for parts of the campaign cycle and seen what's possible, but don't have the full system.

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

The Problem with Manual Lead Research and High SDR Turnover

Speaker Introduction: Jason Ten

AI Chatbots vs. AI Agents: Understanding the Difference

Overview of the AI Agent Lead Processing Workflow

Finding and Extracting Target Customers with High Intent

Using Get Prospect to Extract Leads from LinkedIn Events

Autonomous vs. Deterministic AI Agents for Workflows

Introduction to n8n for Building Visual AI Workflows

Step 1: Data Ingestion and Cleaning via API

Step 2: Evaluating Leads with AI Based on ICP Criteria

Step 3: Categorizing Leads into Qualified and Unqualified Buckets

Step 4: Crafting Hyper-Personalized Outreach Messages

Step 5: Updating the Lead Database Status

Automated Outreach Strategies and Tools

The Results: Scaling from 100 to 400 Leads per Day

Next Steps, Resources, and Q&A

Sales professionals who drive revenue through client engagement and pipeline management.

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.

Driving user acquisition, activation, retention, and monetization through product-led growth strategies.

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

How to Build an AI Agent to Lead Sales Research

What you'll learn

Why this topic matters

You'll learn from

Jason Tan