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Keith McAleer

Keith McAleer · San Francisco

I lead marketing — and build the systems behind it.

Fifteen years in brand, growth and product, including eleven as CMO of UC Berkeley's entrepreneurship center. Increasingly, that means designing and shipping AI products and the agentic systems that turn complex technology into something people use.

Hey Neko desktop window: a sleeping cat avatar above a chat where Neko hands a pomodoro app build to Claude Code and later reports that tests and build passed after one repair.01
Relaunched BEGIN homepage: 'Your gateway to the Berkeley innovation ecosystem', with buttons to explore the roadmap or browse all resources and a link to ask BearGPT, beside a photo of the Campanile and the Bay.02
Title slide of The Innovation Collider: white headline on deep navy with colliding particle streaks, subtitled 'Berkeley's innovation ecosystem + marketing in the AI era'.03
Chief Marketing Officer, UC Berkeley SCET
11 years
annual revenue driven through demand systems I built
$1M+
return on paid acquisition across Google, Meta and LinkedIn
5–10×
AI and software products designed and shipped with coding agents
10+

How the work connects

Most marketing problems turn out to be system problems.

The same loop runs through a campaign, a university platform and a desktop agent. What has changed is how much of it I can now build myself.

  1. 01

    Understand the problem

    Who is this for, and what are they actually trying to get done?

    See: Narrow ICPs

  2. 02

    Tell the story

    Positioning and narrative clear enough to survive being retold.

    See: Marketing in the AI era

  3. 03

    Build the system

    The platform, CRM, analytics or agent that gets the story to the people it's for.

    See: BEGIN

  4. 04

    Measure adoption

    Did people use it? Did it pay back? Then do the next loop.

    See: The growth system

AI and product run underneath every stage: as a research tool, as a way to prototype the idea, and more and more as the thing being built.

Selected work

A shipped AI product, an agentic system, a platform, and the commercial engine.

Four projects, each showing a different part of the same job.

Neko chat: a weather answer, then a request to build a Focus Timer app delegated to Claude Code, followed by a completion report with npm test and npm run build checks.
Neko Brain settings: avatar, voice, language, and separate model choices for chat and for coding, plus work hours and custom instructions.

01 · Desktop AI agent

Hey Neko

Shipped · free beta for Windows and macOS

One voice in front of the AI systems you already use.

A voice-first desktop assistant and orchestrator. Neko answers out loud, keeps context for each project and client, runs local apps, and hands coding work to Claude Code or Codex in the background, inside safety boundaries enforced in code.

  • Shipped as a free beta for Windows and macOS (Apple Silicon)
  • 500+ automated tests
  • About 22,000 lines of Python
Ventiin development

Agents

  • EurusStrategy lead
  • AuraBrand
  • ZephyrusEmail campaigns
  • AeolusMarketing loop & leads
  • BoreasContacts
  • NotusPages & forms
  • AellaVideo

Tools by area

  • Campaigns9
  • Brand6
  • Contacts6
  • Forms & pages6
  • Video5
  • Strategy & reports5
  • Leads4
  • Agent hand-offs4
  • Lists & utilities11
Diagram of the system as built so far, from its agent and tool registry. Not a product screenshot.

02 · Agentic marketing workspace

Venti

In development · not yet deployed

Making it easy for a whole community to contribute to its own marketing.

A multi-agent workspace that combines structured contribution forms, reusable brand context and agentic workflows. Faculty, staff and students can hand over stories and campaign inputs with little effort, and a small marketing team can turn them into useful content.

  • In development, not yet deployed
  • 7 agents and 50+ tools implemented so far
  • HubSpot integration that reads contacts and writes back lead scores
Relaunched BEGIN homepage: 'Your gateway to the Berkeley innovation ecosystem', with buttons to explore the roadmap or browse all resources and a link to ask BearGPT, beside a photo of the Campanile and the Bay.

03 · Discovery platform

BEGIN: Berkeley Gateway to Innovation

Live · relaunch in preview

Turning institutional complexity into a navigable product.

A structured discovery layer across 155 Berkeley entrepreneurship and innovation resources, organized by stage, audience and category. A student, researcher or founder can find where to go next without first decoding the university.

  • Live at begin.berkeley.edu, with the relaunch in preview
  • 155 programs and resources organized in one structure
  • UC Berkeley's first AI-guided entrepreneurship resource chatbot
  1. 01

    Paid acquisition

    Google · Meta · LinkedIn

    5–10× ROAS

  2. 02

    Landing experience

    One audience, one decision

  3. 03

    Lead capture

    HubSpot forms & CRM

  4. 04

    Lifecycle

    Nurture for longer decisions

  5. 05

    Enrollment & revenue

    Executive education · Design Lab

    $1M+ / year

GA4 + HubSpot attribution: every stage measured, from first click to revenue

04 · Marketing infrastructure

The growth system behind SCET

In operation

The commercial engine: $1M+ a year, measured end to end.

The demand engine behind SCET's executive education and Design Lab programs. Paid acquisition, landing experiences, lead capture, lifecycle and reporting, all instrumented in HubSpot and GA4 so spend connects to revenue.

  • $1M+ in annual revenue driven through demand-generation systems
  • 5–10× ROAS on paid acquisition across Google, Meta and LinkedIn
  • About $700K annual budget, owned end to end

Things I build

Building is how I think.

Independent products and experiments, mostly built with AI coding agents. Some are tools I use every day. Some exist to find out what's possible.

  • StartupOS

    Live · private workspace

    A workspace where founders grade hypotheses, experiments and decisions on an explicit evidence ladder. The AI assistant proposes structured changes that the founder has to approve.

  • Korean FlashCard Talk & Learn

    Web prototype · iOS app in development

    A Korean practice app where you say the answer aloud. Speech recognition checks it, and missed cards come back until they stick. Decks follow a real curriculum, from daily-life basics to conversation.

  • Rune Rush and small games

    Experiments

    Browser games built as experiments in game feel and in what AI agents can carry end to end. Rune Rush, a first-person wizard arena with boss waves and controller support, was built through Neko.

  • ResumeBuilder

    Personal tool

    A file-based system that AI agents work inside: a canonical record of experience, role profiles, and a written constitution the agents must follow when drafting tailored applications.

  • Expi Labs

    Live

    A small app studio site with the publishing, policy and support pages that apps in the stores require.

Ideas I'm working through

Marketing in the AI era.

Two talks from October 2026. The short version: AI made average content free, so point of view, proof and structure matter more than ever.

All the arguments
Title slide of The Innovation Collider: white headline on deep navy with colliding particle streaks, subtitled 'Berkeley's innovation ecosystem + marketing in the AI era'.

3 October 2026 · BCS AI + Recruiting Summit

The Innovation Collider

Berkeley's innovation ecosystem, then six popular claims about marketing in the AI era, each tested against current research and given a verdict.

  • AI made average free. Average is now worthless.
  • Every AI that recommends you has read your website.
  • You're not behind on agents. You might be behind on positioning.
Read the arguments
Title slide of Startup Marketing in the AI Era: white headline on deep navy with particle streaks, subtitled 'Positioning · Story · Brand · When to invest · Mistakes'.

October 2026 · UDAX Berkeley Accelerator, Cohort 2

Startup Marketing in the AI Era

A practical framework for founders: positioning, story, brand, when to invest in marketing, and the mistakes early-stage teams make most often.

  • Sell the hole, not the drill.
  • Generic is free now. A point of view isn't.
  • A crowd you paid for isn't product-market fit.
Read the arguments

About

Building has become part of how I lead.

I started in communications, and over fifteen years I kept moving underneath the work: websites, then analytics, CRM, UX, automation, software, and now AI agents. Each time, the most useful answer to a marketing problem was a better system, so I learned to build them.

Berkeley's entrepreneurship center gave me founders, engineers and faculty to learn from, a federated organization to make sense of, and permission to experiment. I still write, design, analyze and ship.

Chancellor's Outstanding Staff Award, UC Berkeley, 2022.

More about how I work

I'm interested in consequential work at the intersection of AI, product and growth.

I'm based in San Francisco and talking with teams working on how AI changes products, marketing and knowledge work.