LEARN TO Leverage
Artificial intelligence THROUGH AI academy

a 6-month program designed to help public equity analysts harness the power of AI to augment workflows and enhance processes.

Price: $1850 6-month program

Cut through the noise and discover how to augment your INVESTMENT process with AI

don’t replace your process; enhance it with ai

AI has reached an inflection point, achieving real enterprise adoption in multiple industries. Deploying AI in investment research offers the promise of significant productivity gains and deeper investment insights.

However, a balanced, evidence-based approach is necessary. Poor data quality, hallucinations, and the challenges of cultural and workflow transformation have led to a slower relative adoption of AI in investment research. Will AI tools sacrifice quality for speed? And can AI tools ultimately drive better investment outcomes, helping managers better protect & grow investor capital?

AI for Investment Research is a no-code, user-focused program designed to help fundamental analysts discover how AI augmentation can increase both speed and depth of analysis without sacrificing research quality, situation comprehension, and the judgment & intuition that defines successful investing.

Our approach blends structured curriculum, a “master class” guest speaker panel, interactive AI case studies, community learning, vendor discovery, and a capstone AI showcase where students will present their most compelling AI use cases. Students will leave with immediate, actionable process improvements and a framework for continuous adaptation as AI capabilities rapidly evolve.

free webinar Replays

Get a chance to learn directly from our instructors before joining the program. These recorded live sessions give you a taste of how we teach and how AI is actually being used in investment workflows.

Webinar 1:
With Brett & Kris – Explore 6 real workflows and how AI fits in

Webinar 2:
With Brett & David – Learn practical prompts that analysts actually use

In public equity markets,
comprehension & precision matter

what‘s included in the program?

Month 1 live instruction

  • Four virtual classroom sessions. You can join live or watch the recording at any point after the session

  • Slide presentations and additional materials are available for download

Months 2-6 Office Hours & “AI Labs”

  • Expert-hosted office hours and monthly “AI Lab” supported by extended vendor trials

Guest Speaker Sessions

  • On-demand guest speaker panel of 15+ managers, vendors & consultants in investing-AI

Community Table & AI Showcase

  • Peer collaboration structure to identify & operationalize AI-augmentation best practices

THE CURRICULUM

  • Investment Research 2030

    • A brief history of investing tools

    • Our assessment of the current state of AI

    • Process, outcome & AI-augmentation

    • Three key barriers to AI adoption in investing

    • AI bull case: rapid & disruptive breakthroughs

    • AI base case: steady, helpful progress

    • AI bear case: edge cases & “auto complete”

    • Alpha: adaptive tools, adaptive markets

  • AI & Investing: first principles

    • The five pillars of AI-augmentation

    • Why a first principles intuition matters

    • LLMs 101: Architecture & mechanics

    • LLMs 101: Training data & its implications

    • LLMs 101: Retrieval & completion

    • LLMs 101: Hallucinations & transparency

    • The superpowers & blind spots of LLMs

    • Deploying LLMs in investment research

  • investment research prompting

    • Will prompting continue to matter? The bull/bear

    • Why prompting matters today: first principles

    • Prompting & hallucination mitigation

    • Anatomy of effective investing prompts

    • Advanced prompt techniques

    • Quick mastery: recursive prompting

    • Building your library of effective prompts

    • Real-world prompt examples

  • Where to start: system design

    • Six considerations for your AI journey

    • Buy vs. Build, and a hybrid approach

    • Generalist vs. domain-specific tools

    • Now, Next: Quick wins vs. transformational bets

    • Key data architecture foundations

    • The velocity vs. comprehension frontier

    • The excel problem: a key logjam

    • A/B testing & pilot project identification

  • Deconstructing your process

    • AI & investing: the heterogeneity of process

    • The art of comprehension & distillation

    • Process, judgment & alpha generation

    • Identifying your “three golden processes”

    • Decomposing what makes you special

    • An approach to documenting your process

    • The characteristics of a discrete workflow

    • Creating your own workflow document

  • Crafting your AI workflows

    • Reading stack, data dashboard & field research

    • Aligning workflows with model capabilities

    • Workflow document -> prompt library

    • Gaining confidence: parallel A/B testing

    • A framework for process blending: more with less

    • Crafting rubrics & checklists

    • Cultural considerations on precision vs. velocity

    • Aligning your culture around new frontiers

  • AI & Alpha Signal Generation

    • The opportunity in unstructured data

    • Digging deep: AI as a research super-power

    • Sector specialization & data identification

    • Creative AI approaches to field research

    • Learnings from a decade+ in “quantamental”

    • A prior: the alternative data alpha window

    • Building an AI-powered data dashboard

    • Expectations & set-up work with AI

  • Implementing your AI-system

    • One size decidedly does not fit all

    • Balancing velocity, precision & comprehension

    • Navigating obsolescence risk in your stack

    • Compliance & data privacy considerations

    • Building your vendor evaluation rubric

    • Frameworks for training & team alignment

    • Experimentation, iteration & evolution

    • The key question: will AI drive alpha?

CORE INSTRUCTORS

  • Brett CAUGHRAN

    HEAD TRAINER

    Brett brings 13yrs of hedge fund experience at Maverick, D.E. Shaw, Citadel, Two Sigma & Schonfeld.

    Brett founded Fundamental Edge in 2022 to help improve training on the buy-side. Brett has led over 750 buy-side analysts through Analyst Academy and has designed and delivered numerous custom analyst training programs.

  • David PLON

    INSTRUCTOR

    David is the Co-Founder and CEO

    of Portrait Analytics, an AI powered investment research platform. He draws from his experience as a buy-side analyst at The Baupost Group and Slate Path Capital to build AI tools tailored for fundamental investors.

  • Kris BENNATTI

    INSTRUCTOR

    Kris is the Co-Founder and CEO of Hudson Labs, where she leads the development of AI tools that transform financial disclosures and public data into actionable insights.

    As a licensed CPA and former data scientist, Kris taps into her deep knowledge of financial statements to develop buy-side ready tools.

AI Guest Speakers:

Complementary perspectives to explore ai from all angles

  • Daniel Swiecki

    Head of Current - AI Solutions at Walleye Capital and bring former buyside experience at Maplelane, Balyasny and Andor Capital

  • Jim Falbe

    Former Managing Principal at Saguaro Capital which was a long-only, AI-powered investment firm, and a former Portfolio Manager at Vulcan Value Partners

  • Suhas Pai

    CTO and Co-founder of Hudson Labs, NLP lead at Aggregate Intellect, Chair of TMLS, and former IBM engineer with a decade of experience advancing applied AI

  • Tarun Amasa

    Cofounder and CEO of Endex.ai, Thiel Fellow, and former engineer at Apple and Tesla, building frontier AI systems at the edge of innovation

  • Jared Kubin

    Founder and CIO of Issachar Technologies, former tech investor at Adage Capital, with a decade of experience in public markets and a passion for faith-driven impact

  • Thomas Li

    Co-Founder and CEO of Daloopa, former TMT investor at Angelo Gordon and Point72, building AI tools for financial decision-makers

  • Michael Watson

    Co-Founder of Hedgineer, former Head of Equities Engineering at Citadel, with deep expertise in transforming investment firms through AI

  • Khe Hy

    Founder of RadReads and executive coach to top investors and founders, with a decade of hedge fund experience at BlackRock and Treedale Partners

  • Raj Shah

    Co-Founder of Stoic Point Capital, former Partner at Light Street and Stillwater, with a decade of investing experience across hedge funds and private markets

  • Ying Hua

    Founder of Implied, former Portfolio Manager at Balyasny and Analyst at Citadel, with deep expertise in insurance and AI-driven investing

  • Brooker Belcourt

    Building an Internal AI System Bio: GM of Finance at Perplexity, former Head of Product at Tilt and Founder of Covey, with deep expertise in building products for financial services and investor communities

  • Nan Lu

    Director at BlackRock AI Labs, former Director at Credit Suisse, building AI-driven systems at the frontier of quantitative finance

  • Nico Christie

    Co-Founder of Fundamental Research Labs, founding team at PredictionStrike, and former pro athlete turned strategist

  • Connie Lee

    Founder & CIO of Felis Advantage, former Partner at Tiger Global, with past roles at Berkshire Partners, BCG, and a fintech startup

  • Artem Fokin

    Artem Fokin

    Founder of Caro-Kann Capital, former Principal at Outrider Management, with a background in international tax law at Greenberg Traurig

  • Andrew Freedman

    Partner at Hedgeye, former Communications Sector Head and Healthcare Analyst, with prior experience at Clearbrook Global Advisors

FAQs

  • We will meet four consecutive Monday evenings 5-8pm ET via Zoom starting September 15th for roughly 3 hours. After this, we will proctor 5 month-long case studies with office hours. With self-paced guest speakers, total cohort time will exceed 40 hours. All sessions are recorded & available for replay for up to 12 months.

  • We will primarily focus on slower evolving principles such as workflow decomposition & process augmentation. Inescapably, we will discuss many fast-evolving areas, but will put forth suggestions to keep up with these evolutions

  • A subscription to Claude, Gemini & ChatGPT. A stack of extended finance domain vendor trials will be offered

  • No. We will not discuss engineering principles of building an LLM. This course will focus on the user’s perspective in investment research

  • We will send a pre-req reading & YouTube list, but there are no technical skills required