# Give the investment thesis a working memory.

An agentic layer that breaks an investment thesis into linked claims, risks and initiatives, and reasons across every deal a fund holds.

Company: VectorShift

Contribution: Agentic layer design

Company tenure: VectorShift · Jul 2025–present. This is not a claim about individual project dates.

Context: Claims → risks → initiatives

## TL;DR

Problem: An investment thesis sat in a static memo, so nobody could see which of its claims still held as deals changed.

My call: Break the thesis into linked claims, risks and initiatives, and design an agent that reasons across every deal the fund holds.

Outcome: Thousands of initiatives proposed and amended through it.

- Initiatives proposed and amended: Thousands
- In the agent’s reasoning scope: Every deal
- Linked types: claims, risks, initiatives: 3

## Context

- Company: VectorShift (YC S23)
- My role: Built the product and designed its agentic layer
- Users: Private equity deal teams and portfolio operations
- Scope: Every deal the fund holds

Conceptual relationship map. Claims, risks and initiatives connect to an investment thesis, with reasoning across deals.

## The problem

A fund writes an investment thesis when it decides to back a company. After that, the thesis usually lives in a memo.

The claims inside it change status quietly. This market grows. This margin expands. This team can execute. The risks that challenge those claims show up in board updates and diligence notes, not in the memo.

So when a partner asks whether to push an initiative or pull back, the reasoning gets rebuilt from memory and scattered documents, one deal at a time.

Evidence: Theses were read at underwriting and at exit, rarely in between. The same kind of risk appeared across several deals without anyone connecting them.

## Constraints & non-goals

The agent has to reason across every deal the fund holds, not one document at a time.

Investment decisions stay with people. The agent makes the argument. It does not take the action.

Every argument has to point back to the claims, risks and sources it depends on.

Out of scope: Automated investment decisions. Market forecasting. The agent reasons over the fund’s own information. Replacing the investment committee memo.

## Options I weighed

Rejected: Chat over the memo folder Fluent answers with no structure underneath. Retrieval finds passages. It does not know that a claim in one deal is undermined by a risk in another.

Rejected: A manual thesis tracker with no agent Structure without leverage. At fund scale, nobody keeps the links up to date by hand.

Chosen: Linked thesis objects plus an agentic layer The structure gives the agent something real to reason over. The agent keeps the structure useful by proposing and amending initiatives.

## The spec

Users: Partners and principals who own a thesis. Portfolio operations teams who run value-creation initiatives.

Requirements: A thesis breaks down into claims, risks and initiatives that link to each other. The agent argues for or against a move using information from every deal in the fund. People can propose and amend initiatives. Every argument cites the claims, risks and sources it relies on.

Acceptance criteria: When a new risk is added to one deal, the agent surfaces other deals with linked claims. Every argument shows the evidence for and against. A person accepts, edits or rejects every proposed change.

Guardrails: The agent never changes a thesis or initiative without a person accepting it. Arguments without cited evidence are not shown.

## What shipped

1. Decompose. The thesis is broken into claims, risks and initiatives.

2. Link. Objects connect within a deal and across deals.

3. Reason. The agent builds the case for and against a move across the whole fund.

4. Decide. People propose and amend initiatives.

## What changed

Thousands of initiatives have been proposed and amended through Deal Intelligence.

The thesis became something teams use between underwriting and exit, not a memo read once.

It is the clearest example of how I design agent systems: structure first, then reasoning, then a human decision.

This measures workflow adoption. I don’t claim an effect on investment returns.

## Reflection

The design question that mattered most was not what the agent could say. It was what the agent was allowed to change.

If I did it again, I would put the linked structure in front of users before the agent, so the objects the agent reasons over are already familiar when its arguments show up.

The takeaway: Structure the thesis first, then let an agent reason over it.

Last updated: 2026-09-13