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Harrison Golden · beyond the résumé

I turn growth priorities into operating systems.

Forecasts, reporting cadences, AI workflows, and 0→1 launch architecture — the connective tissue between strategy and execution for high-growth teams. My résumé shows the roles; this site shows how I operate. Scroll to descend.

Open to — GTM Strategy & Ops · Marketing Ops · BizOps / RevOps · AI Operations · Chief of Staff
What I build

The work, at a glance.

Forecasting & reporting
Multi-line portfolio forecasting, QBRs, and parent-company reporting.
GTM & RevOps systems
Pipeline architecture, launch planning, lifecycle marketing, and operating rhythm.
AI-native workflows
LLM newsletter automation, multi-model review, research synthesis, reporting drafts.
Turnaround & 0→1
Post-acquisition integration partner; a full DTC operating stack, built end to end.
First principles · break the number apart

I don’t trust a number I haven’t taken apart.

In commercial operations the top-line view is usually too blunt to be useful. Demand behaves differently by account, supplier line, reorder cycle, and margin profile — so I treat a forecast as a system to decompose, not one number to defend. Separate the durable from the temporary and the noise, and attention goes where it can actually change the outcome.

Operating rhythm · make strategy recurring

Strategy only matters when it becomes a cadence.

Through a post-acquisition integration, I worked as the strategy-and-operations partner to the President. The work was translation as much as analysis — leadership priorities, sales realities, finance constraints, and parent-company expectations resolving into one rhythm of forecasts, budget tracking, and commercial follow-through. A plan is only useful when other people can run it, repeatedly.

AI-native execution · automate the repeatable

Push the money into the product — automate the rest.

I use AI to remove recurring work that shouldn’t need a person twice — newsletter production, research synthesis, multi-model review, reporting drafts. In my last venture that meant an operating stack where software absorbed the fixed costs, so a lean team could do more before headcount caught up. Not AI as a badge — AI as workflow infrastructure.

Zero to one · the system before the team

I build from ambiguity.

I’m happiest where a business needs structure before it needs headcount. In a pre-launch DTC venture I owned the business function end to end — product strategy, launch planning, financial modeling, and the operating stack behind it: Shopify, Klaviyo, Power BI, and LLM workflows fitted into one spine a small team could run intelligently, before scale justified more complexity.

Judgment · know when to stop

The discipline I trust most is knowing when to pivot.

A good operator doesn’t just build momentum — they know when not to fund it. I spent two years architecting a machine-learning trading system and wound it down when it proved technically sound but not commercially compelling. I made the same call on a venture when changing economics broke the case before launch. I trust intensity; I trust commercial discipline more.

What’s next · open to the right team

Founder-level ownership, operator by craft.

I’m most useful where growth creates operational complexity faster than the organization can absorb it. I grew up inside two family businesses and have been building ever since — now I’m bringing that operating instinct, AI-native by practice, to a high-velocity, scaled team, and committing to it for the long run.

GTM Strategy & Ops · Marketing Ops · BizOps / RevOps · AI Operations · Chief of Staff / Strategic Operations