Focus: User Incentives, Cross-Platform Feature Expansion & Market Data Refinement

This iteration focused on lowering the entry barrier for new users, expanding feature availability across platforms, and continuing foundational work on frontend adaptability and market data quality.

To support adoption of newly released features, we introduced user incentives that offset trading fees and losses, migrated key trading mechanics to the Telegram Mini App, and progressed on both UI responsiveness and a new K-line algorithm designed to better handle adversarial trading behavior.

At the same time, we began development on a lightweight interactive game—TapTrade—scheduled to launch before the Lunar New Year.

To encourage hands-on exploration of PinkPunk’s new features, we introduced trading credits for new users.

Design Goals

• Reduce psychological and financial friction for first-time users

• Allow users to experience real trading flows with limited downside

• Offset trading fees and realized losses without altering core execution logic

Engineering Considerations

• Credit accounting isolated from real balances

• Clear deduction priority rules between credits and user funds

• Prevent abuse while keeping redemption logic simple and predictable

We migrated both Timed Feature and Lightning Feature from the web platform to the Telegram Mini App.

Why This Matters

• Telegram remains a high-frequency interaction surface for many users

• Feature parity reduces cognitive switching costs between platforms

Implementation Work

• Adapted interaction flows for constrained Mini App layouts

• Unified backend execution paths to avoid platform-specific divergence

• Ensured consistent state handling between Web and Telegram sessions

TapTrade is a lightweight, game-inspired interaction designed to introduce trading concepts through rapid, low-friction actions.

Current Status

• Core mechanics under development

• Designed for short sessions and fast feedback loops

• Targeted for release before the Lunar New Year

Supporting Work

• Event tracking and lightweight state persistence

• Safeguards to prevent excessive resource usage

• Clear separation from core trading logic to avoid risk coupling

• Ongoing adjustments to better support mobile web usage

• Refactoring layout structure for smaller screens

• Improving touch interaction ergonomics without duplicating logic

We are developing a new K-line aggregation algorithm aimed at reducing distortion caused by adversarial trading patterns.

Problems Addressed

• Abnormal long wicks caused by sandwiching and trade stuffing

• Over-amplification of single extreme trades in visual data

Direction

• Smarter aggregation thresholds

• Better time-bucket alignment

• Reduced sensitivity to outlier transactions while preserving trend accuracy

In order to safely ship the above changes, additional work was required:

• Coordinating incentive logic with existing fee and PnL pipelines

• Ensuring cross-platform features share consistent execution semantics

• Hardening API paths under increased experimentation traffic

• Validating Mini App behavior under network and session interruptions

• Preparing monitoring and rollback strategies for pre-holiday releases

While less visible, these efforts were necessary to keep iteration speed high without accumulating instability.

This cycle balanced growth-driven experimentation with continued system refinement.

Some features aim to make PinkPunk more approachable and fun, while others focus on quietly improving correctness and resilience. A few items remain in progress, but the groundwork laid here should make the upcoming releases—especially around the holiday period—less risky and easier to manage.

Focus: User Incentives, Cross-Platform Feature Expansion & Market Data Refinement

This iteration focused on lowering the entry barrier for new users, expanding feature availability across platforms, and continuing foundational work on frontend adaptability and market data quality.

To support adoption of newly released features, we introduced user incentives that offset trading fees and losses, migrated key trading mechanics to the Telegram Mini App, and progressed on both UI responsiveness and a new K-line algorithm designed to better handle adversarial trading behavior.

At the same time, we began development on a lightweight interactive game—TapTrade—scheduled to launch before the Lunar New Year.

To encourage hands-on exploration of PinkPunk’s new features, we introduced trading credits for new users.

Design Goals

• Reduce psychological and financial friction for first-time users

• Allow users to experience real trading flows with limited downside

• Offset trading fees and realized losses without altering core execution logic

Engineering Considerations

• Credit accounting isolated from real balances

• Clear deduction priority rules between credits and user funds

• Prevent abuse while keeping redemption logic simple and predictable

We migrated both Timed Feature and Lightning Feature from the web platform to the Telegram Mini App.

Why This Matters

• Telegram remains a high-frequency interaction surface for many users

• Feature parity reduces cognitive switching costs between platforms

Implementation Work

• Adapted interaction flows for constrained Mini App layouts

• Unified backend execution paths to avoid platform-specific divergence

• Ensured consistent state handling between Web and Telegram sessions

TapTrade is a lightweight, game-inspired interaction designed to introduce trading concepts through rapid, low-friction actions.

Current Status

• Core mechanics under development

• Designed for short sessions and fast feedback loops

• Targeted for release before the Lunar New Year

Supporting Work

• Event tracking and lightweight state persistence

• Safeguards to prevent excessive resource usage

• Clear separation from core trading logic to avoid risk coupling

• Ongoing adjustments to better support mobile web usage

• Refactoring layout structure for smaller screens

• Improving touch interaction ergonomics without duplicating logic

We are developing a new K-line aggregation algorithm aimed at reducing distortion caused by adversarial trading patterns.

Problems Addressed

• Abnormal long wicks caused by sandwiching and trade stuffing

• Over-amplification of single extreme trades in visual data

Direction

• Smarter aggregation thresholds

• Better time-bucket alignment

• Reduced sensitivity to outlier transactions while preserving trend accuracy

In order to safely ship the above changes, additional work was required:

• Coordinating incentive logic with existing fee and PnL pipelines

• Ensuring cross-platform features share consistent execution semantics

• Hardening API paths under increased experimentation traffic

• Validating Mini App behavior under network and session interruptions

• Preparing monitoring and rollback strategies for pre-holiday releases

While less visible, these efforts were necessary to keep iteration speed high without accumulating instability.

This cycle balanced growth-driven experimentation with continued system refinement.

Some features aim to make PinkPunk more approachable and fun, while others focus on quietly improving correctness and resilience. A few items remain in progress, but the groundwork laid here should make the upcoming releases—especially around the holiday period—less risky and easier to manage.