Why Good UX Has to Cheat — and Plan Like a Villain

Users don’t experience your product. They experience their impression of your product — and those two things are almost never the same.

This is not a philosophical detour. It’s an engineering problem. And most product and UX teams in Southeast Asia are still solving the wrong version of it.

The Tetris Problem: Reality Is Not the Point

Here’s a fact that should quietly disturb every product designer: the original Tetris used a genuinely random piece generator, and players hated it. Not because it was unfair — it was fair — but because true randomness produces streaks. Four S-pieces in a row. No straight pieces for two minutes. Statistically normal. Experientially infuriating.

As UX Collective contributor Takuma Kakehi explains, Tetris had to cheat to feel random. Modern versions use a “bag” system that shuffles all seven pieces before dealing them out — guaranteeing distribution, eliminating streaks, and creating the sensation of fairness that pure probability never could.

This is a principle that should live in every design system: perceived fairness beats actual fairness every time. Users cannot see a probability distribution. They see a sequence, and human intuition is catastrophically bad at reading sequences correctly. Design that ignores this will be judged broken — even when it’s technically correct.

For Southeast Asian platforms operating at scale — Shopee’s product recommendation engine, Grab’s surge pricing display, any loyalty points system — this matters enormously. When users perceive streaks or clustering in what should feel neutral, trust erodes. The fix is rarely in the algorithm. It’s in how the output is sequenced and surfaced.

Perceived Randomness Has a UI Layer

So what does “cheating for fairness” actually look like in practice? It means designing the presentation of system outputs as deliberately as the outputs themselves — and this is where most data-driven product teams drop the ball.

A recommendation carousel that surfaces two near-identical products back-to-back will feel broken to a user, even if the model scored them correctly. A notification system that fires three alerts in forty minutes will feel spammy, even if all three were individually triggered by legitimate user actions. The underlying logic is fine. The sequencing is the problem.

Implementation moves worth considering: introduce minimum spacing rules between similar content types at the UI layer, independent of backend logic. Build “perceptual shuffle” buffers that smooth clustering before it reaches the interface. On mobile — which accounts for the overwhelming majority of e-commerce sessions across Indonesia, Thailand, and Vietnam — these clustering effects are amplified because users see one or two items at a time, not a grid. A streak is far more visible on a 6-inch screen.

The cost of not doing this is measurable: Shopee and Lazada both invest heavily in recommendation diversity precisely because homogeneous feeds depress session length and repeat visit rates. Perception is a product metric.

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Stop Reacting. Start Scheming.

The second insight worth sitting with comes from UX Collective’s Wira Indra Kusuma, who draws a surprisingly sharp distinction between how villains and heroes operate in narrative structure — and maps it directly onto product team behaviour.

The observation: villains plan. They have a theory of the future, they build toward it deliberately, and they anticipate resistance. Heroes react. They respond to what’s in front of them, course-correct under pressure, and win through improvisation and moral clarity.

Product teams, almost universally, behave like heroes. Roadmaps get built sprint by sprint. Design decisions get made in response to user complaints, competitor moves, or whoever shouted loudest in the last stakeholder meeting. There’s a certain agility to this — but it produces interfaces that are reactive by nature, full of bolted-on features and inconsistent interaction patterns that accumulate like technical debt.

The alternative is to design with villain-level intentionality: a clear picture of the experience you’re building toward, the obstacles users will encounter, and the deliberate choices that will get them through. This isn’t waterfall planning. It’s having a design thesis — and making individual decisions in service of it.

What Villain-Level Planning Looks Like in a Design System

In practical terms, this means your design system needs to encode intent, not just consistency. Most design systems in the region are built to solve the immediate problem of visual coherence across channels — which is valuable, but insufficient. A mature design system should also carry decisions about why components behave the way they do, so that new contributors aren’t improvising from scratch every time.

For teams working across multilingual interfaces — which is essentially every serious consumer brand in Southeast Asia — this matters even more. A button label that works in English may be 40% longer in Thai or Vietnamese, breaking your layout entirely. A villain-planner designs for this in advance: variable-length text containers, flexible grid systems, and component-level documentation that explicitly addresses language switching.

Stakeholder buy-in for this kind of upfront investment is always the hard part. The framing that tends to work: reactive design accumulates invisible costs — in engineering rework, in inconsistent user experiences, in the time designers spend re-litigating decisions that were already made. A design system with encoded intent is cheaper to maintain and faster to extend. That’s a CFO argument, not just a craft argument.

The brands getting this right in Southeast Asia — Sea Group’s product teams, Gojek’s design org — share one characteristic: they treat their design systems as living strategic documents, not style guides.

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Key Takeaways

• Design the perception of your system’s outputs — sequencing and clustering at the UI layer are product decisions, not afterthoughts.
• Build design systems that encode strategic intent, not just visual consistency — especially across multilingual, mobile-first interfaces.
• Shift from reactive roadmapping to thesis-driven design: know the experience you’re building toward and make deliberate decisions in service of it.

The uncomfortable question this raises: how many of your current design decisions were made deliberately, and how many were made in response to something? If you can’t answer that with confidence, your interface is probably a hero — and heroes, as any decent villain will tell you, are easy to outmanoeuvre.

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At grzzly, we work with digital teams across Southeast Asia to build the kind of design intelligence that connects UX decisions to measurable business outcomes — from design system architecture to how your data pipeline surfaces insights that actually inform product direction. If your team is spending more time reacting than planning, that’s a conversation worth having. Let’s talk