About Morgan Kotter

I'm a product manager and indie founder based in Utah. For seven years I've been forward-deployed inside enterprise SaaS — first at Lucid, now at Marq — embedding AI directly into the workflows of large customers and owning the outcomes that result. On the side, I run a small studio of AI-native products that I design, build, deploy, and iterate on myself.

I do the same job both places: take an ambiguous customer problem, ship a working AI system against it, and stay close enough to the user to actually move the metric.

How I work

The pattern is the same whether I'm shipping inside a 200-person enterprise CRM or against my own paying users on the weekend:

Own the agent end-to-end. Prompt design, tool calls, evals, guardrails, deployment, telemetry. No throwing it over a wall — every layer is part of the product, and the metric on top is mine.
Stay close to the user. I sit with the people who actually use the system. Workshops with customer stakeholders, calls with paying users, my own dogfooding. The shortest possible loop from "saw the problem" to "shipped the fix."
Ambiguity is the work, not the obstacle. Almost everything I ship starts as a vague request and a deadline. I prefer it that way.
Outcomes over outputs. I track the agent's effect on the user's real-world outcome — completion rate, reply rate, time-to-value, revenue — not the number of features shipped.

What I'm currently working on

Marq · Growth Product Manager (2021 – present)

I lead AI inside Marq's CRM-native content platform. Most of my work is in the same shape as a forward-deployed PM role at an applied AI company:

Design, build, and deploy AI agents that turn live CRM signal (Salesforce, HubSpot) into personalized sales collateral, sequences, and decisions
Run discovery and design sessions with senior customer stakeholders to scope what "good" looks like, then own the rollout and the metric afterward
Prototype in code alongside engineering — LLM orchestration, evals, tool use, prompt versioning — so the loop from idea to deployed agent is hours, not weeks
Set guardrails, monitor live behavior, and iterate on prompts, retrieval, and tools as real usage exposes the failure modes
Translate what works back into platform capabilities for every other customer

Stack: TypeScript, Next.js, Python, Postgres, OpenAI / Anthropic / Google APIs, n8n, CRM SDKs.

Modlific · Founder

Modlific is the studio I run on the side. Same playbook as my day job — the customer is just whoever signs up.

ToonyStory

An AI-native consumer app where a multi-stage agent (story generation → character consistency → illustration → layout → print fulfillment) produces physical, printed books. I own the entire agent loop — prompts, evals, retries, print-quality constraints, and the conversion metrics that follow.

Specway

Developer-facing AI tooling for API documentation. Built for teams that want docs to ship at the speed of code, not the speed of a docs team.

ChoreSplit

A household task app with thousands of weekly active users. Where I learn what consumer retention actually looks like when the user opens the app every morning.

SwipeThread

AI-generated social carousels. A focused agent that turns long-form input into platform-native output — a useful test bed for multi-modal generation and format constraints.

Pathalize

B2B task accountability — the ChoreSplit pattern adapted for workplace teams.

Modlific

The parent studio. Same operating model across every product: ship the smallest useful version, deploy to real users, measure, iterate.

Previous experience

Sep 2021 – Present

Marq

Growth Product Manager

Forward-deployed product manager for AI features inside Marq's CRM-native content platform. I scope agents with enterprise customers, build them in code with engineering, deploy them, and own the metrics they move.

Design and ship AI agents that turn live CRM signal into personalized sales content, sequences, and decisions across Salesforce and HubSpot.
Run customer workshops to align on use cases, success criteria, and guardrails — then own the rollout and the post-launch optimization loop.
Stack: TypeScript, Next.js, Python, Postgres, OpenAI / Anthropic / Google APIs, n8n, CRM SDKs.

May 2021 – Sep 2021

Lucid Software

Customer Marketing Automation Manager

Built and automated the post-sale customer lifecycle for enterprise accounts — onboarding sequences, training cadences, in-product education — at scale across a portfolio of 380 customers.

Sr. Customer Success Manager (Apr 2018 – May 2021): managed enterprise account portfolios end-to-end, implementing SCIM/SSO, DAM, MLS, and printer integrations directly with customer engineering teams.
Built CS automation in Marketo + Zendesk that maintained 99.8% NRR across 380 accounts and saved CSMs 700+ hours/year.
Customer-facing implementation work with senior stakeholders at large customers — the foundational reps for the forward-deployed role I do today.

Feb 2018 – Apr 2018

Property Management Business Solutions

Online Results Manager

Performance insight reporting for 250+ franchisees. Early reps in turning operational data into a tool that frontline operators actually used.

Apr 2016 – Jun 2017

AvantGuard Monitoring Centers

QA Manager

Led operations for night and grave shifts at a 24/7 alarm monitoring contact center. Managed teams of 15–26 agents and raised QA from 60% to 90%.

Customer Operations Specialist (Sep 2015 – Jun 2017): maintained a 100% QA rating for two years on the floor before moving into management.
Direct contact-center operations experience: real-time agent handling, quality measurement, and the patterns I now think about applying AI to.

What I'm best at

Owning an AI agent end-to-end: prompt design, evals, retrieval, tool use, deployment, monitoring, iteration
Forward-deployed customer work: workshops, scoping, technical implementation, post-launch optimization with senior stakeholders
Shipping fast inside ambiguity — turning a vague problem into a deployed system in days, not quarters
Operating across product, engineering, and customer success without needing a hand-off between them

Outside of work

I climb, mountain bike, and travel when I can. At home it's my Mini Australian Shepherd and whatever I'm building this week.