AI-Supported Production Workflows

Studios know that AI matters. Ad hoc experiments produce functional demos, but not always repeatable production value: outputs that look impressive but don’t scale. Drifting output, sycophantic responses, and context loss make chat-based AI risky to rely on unchecked. Meanwhile security and IP concerns rightly keep a lot of functionality locked down, so an all-the-AI-all-the-time approach can’t work in practice. The result is real interest, real constraints, and a less clear path towards iterative adoption.

That gap is what I work in. 25+ years leading production across AAA, live service, co-development, and UGC — LucasArts, Crystal Dynamics, Cloud Chamber / 2K, Meta, and most recently building AI-assisted production tooling and reporting infrastructure for a distributed studio. I’m not an AI consultant who learned games — I’m a video games production leader who has spent the last two years working in AI-first environments, solving real workflow problems with AI, inside real studio constraints.

The Engagement — A 4-Day Production AI Pilot

Day 1

Discovery (1:1s)

1:1 stakeholder interviews with leads and main consumers. Map your current tools, approved AI access, security constraints, and where past attempts stalled — ideally the week before training, to clear access hurdles and build a training plan around the tools you actually have.

Day 2

Fundamentals

Introduction to AI tooling structures that work at scale. Context windows, memory, and sycophancy can steer conversations with conviction — we’ll cover tools and habits to maintain project integrity, and how to interrogate a response instead of accepting it.

Day 3

Applied Coaching

Use the tooling built on day two to run real production processes — design breakdowns, Jira scrubs, project planning artifacts, executive reporting — and refine both process and tools as you go.

Day 4

Implementation

Lock in 2–3 working tools or workflows and wire them into your actual pipeline, documented so they outlast the engagement.

Follow-up

A 60–90 minute session two to three weeks later to check adoption and troubleshoot drift or loss of context.

What You Get

A written discovery summary of your constraints, risks, and opportunities
A verification framework your team keeps and reuses
2–3 production tools/workflows built for your pipeline, not a generic template
A leadership readout: what’s working, what’s still risky, recommended next steps, and any recommended additional tools or connections

What This Isn’t

Not a push to bypass your security policy or procure new tools — I work within whatever’s approved (though may recommend functionality outside of this for future engagements)
Not a replacement for any internal or corporate AI strategy — I make that strategy usable at the production level
Not a promise to cut headcount or “10x” output — this is about the quality and reliability of AI-assisted work your team already does
Not a company-wide transformation program — this is a bounded pilot for one team

Scope

Every engagement is scoped to your team, your tools, and your constraints. Structured as a bounded pilot for one production/operations team, with direct implementation support available after.

Talk Scope & Pricing

AI-Supported Production Workflows

The Engagement — A 4-Day Production AI Pilot

What You Get

What This Isn’t

Scope

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