We mapped six places AI was already reshaping gaming—matchmaking, onboarding, NPC behavior, content generation, anti-cheat, and LiveOps. Five were already crowded with funded competitors. LiveOps—the ongoing work of running a game after launch—was the one area with real player pain and no dedicated AI tooling at all. That gap is where Ghost AI started.

To understand where the gap lived, I examined how Riot, Xbox, Valve, Bungie, and Pearl Abyss described their feedback and bug-triage processes. The same pipeline kept appearing: community intake → classification → investigation → prioritization → engineering → player-facing closure.

I designed a 10-question survey and distributed it through 15+ gaming communities, Discord servers, LinkedIn, and personal networks. To reduce bias, I placed open-ended questions before structured ones, randomized multi-select answers, and required a single choice for the quit-trigger question.

Among 200+ responses, 57% cited core gameplay as the reason they kept playing. Developer trust was the strongest open-ended theme. Personalization had the strongest relationship with feeling rewarded (r = 0.457, n = 191), and 66% of self-reported churn was actionable according to respondents.

I then reviewed 17 Reddit threads to deepen what the survey could not capture, including four FOMO subtypes and the “safety to leave” retention pattern associated with games such as Warframe.

I planned and conducted six interviews across studio sizes and roles. Each guide was customized to the participant and iterated on prior sessions, so later interviews could probe contradictions and gaps rather than repeat a fixed script.

• Indie designer/producer on a 2-person team
• Business/product lead at a 3-person studio
• Systems designer on a major publisher’s MMO
• Tools engineer with sandbox and mobile experience
• Lead producer at a VR studio using AI
• VP of Product for an 8-year-old live-service title

I recorded, transcribed, and coded interviews around feedback collection, business-versus-design tension, trust, tooling gaps, and attitudes toward AI—allowing the team to compare a 2-person studio with a publisher serving 20M+ monthly players.

I combined survey results, Reddit findings, and all six interview transcripts in one affinity map. This made it possible to examine where evidence converged, where it conflicted, and which needs were consequential enough to shape the product thesis.

1. Feedback is abundant, but the pipeline is fragmented.
2. The real bottleneck is manual monitoring, grooming, and interpretation—not collection.
3. Feedback only becomes actionable when paired with context.
4. Prioritization is where feedback becomes political and cross-functional.
5. Player trust is simultaneously the outcome and the risk of the entire feedback process.

This synthesis directly shaped our product thesis and was presented to industry advisors as the evidentiary basis for our design direction.

Before finalizing a design direction, I facilitated a structured co-design session with one of our SME participants, walking them through a storyboard of the envisioned experience and a working in-game report prototype, then giving them unstructured time to sketch their own ideal version of a studio-side dashboard.

The participant cautioned that over-reliance on analytics dashboards could become a “slippery slope” that erodes creative intuition.

With a working prototype, I planned and moderated four usability testing sessions (one individual, one joint dual-participant session) walking participants through both halves of the product: the in-game voice-activated report flow and the studio-side dashboard, including a novel “impersonation mode” letting developers step directly into a player’s reported game state. Sessions used think-aloud protocol throughout, plus targeted scenario tasks (e.g., “200 players reported a similar bug over the weekend—walk me through how you’d make sense of it”).

Findings meaningfully changed the design rather than merely validating it. Multiple participants, independently, identified that a single unified dashboard was trying to serve incompatible roles—one participant noted plainly that “very few companies have the same person fixing bugs and investigating data.” The same participant’s single sharpest, most emotionally charged pain point—bugs routinely assigned to him that he had no ability to fix, with no system to route issues to the correct owner—became a headline feature requirement for the next design iteration.