A small selection of recent design and development work by Eder Rengifo for Automattic and personal projects.

02 — Approach

The latest product revamp improved the outdated UI, but the core experience remained the same: a simple, easy-to-understand analytics product focused on simplicity. However, the market had changed. Products like Plausible had started positioning themselves as simpler alternatives to Google Analytics, which reduced the uniqueness of simplicity as the main value proposition.

02 — Approach

If Stats needed to become more profitable, it had to become more versatile. Its value could not rely only on simplicity. It also needed to support more customization, so it could serve small sites as well as larger businesses with more advanced needs. The proposed solution was a system based on boards and responsive widgets.

02 — Approach

Widgets became flexible elements with different levels of abstraction. With this system, users could build their own analytics experiences, while the product could also support more advanced data views as Stats connected with other plugins. Prototyping within the codebase was key to better understand the interactions and the UX opportunities.

03 — Outcome

This is still an ongoing effort and has not been fully tested yet. However, as one of the company’s primary internal goals, the approach is already setting the foundation for a flexible components system that can be reused across other products and experiences powered by Stats.

02 — Approach

At the time, AI in WordPress was still new territory, with few established patterns to reference. One of the main questions was whether the experience should feel fully integrated into the editor or work more like a conversational assistant. We chose an integrated approach to reduce the learning curve and make the tool feel like part of the editor experience. The first version helped us validate some of those assumptions.

02 — Approach

Through several iterations, we continued polishing the experience and its accessibility. It was important that AI features felt deeply connected to the editor, rather than like external extensions added on top of it.

03 — Outcome

The tool evolved over time and gained complementary features. By 2025, 59.2% of generated content was accepted by users, with an average of 1.8k daily requests. From a revenue perspective, within the first six months after introducing paid access to additional requests, this feature accounted for 15% of total Jetpack sales. At the time, it became the highest-performing paid feature in the Jetpack plugin.

02 — Approach

The work started with a competitive analysis to understand where the biggest gaps were and how we could improve the experience efficiently with a small team. The main opportunities were related to individual network customization, previewing, and scheduling.

02 — Approach

The key challenge was creating a scalable experience within an editor that had several component limitations, which required some design compromises. Despite this, the end-to-end experience became fluid enough for simpler needs while remaining comprehensive enough for more advanced ones.

03 — Outcome

The tool still needs more iteration, especially around media customization, but it has already shown strong results. Since the end of 2025, around 400k users have generated approximately 5.6M shares per month. This represents a 73% relative increase in shares per user compared to the period before 2025.

02 — Approach

The plugin was designed around a simple flow: select a layer, scan for layers using a % prefix, and generate data for them. Users could generate random data by customizing a few parameters. Once set, those parameters could be reused across the design.

02 — Approach

Users could also connect the plugin with Google Sheets to bring in existing data or test case scenarios. This connection followed the same simple principle: map data to the same layers and update them quickly.

03 — Outcome

This was an experiment that helped me learn more about the Figma ecosystem and how to approach a complex problem with a simple solution. The plugin has around 40 installations, even though I did not actively promote it.

02 — Approach

I first created a website that could automatically generate more interesting gradient variations. The tool used an algorithm to create random radial color positions and generate ready-to-use HTML code for both static and animated gradients.

02 — Approach

When trying to use these gradients in Figma, I realized that Figma handles gradients differently. To solve this, I created a Figma plugin that used the same algorithm and translated the HTML output into Figma-compatible color configurations.

03 — Outcome

The Figma plugin has around 215 users, and the website has been used around 1.8k times since launch. This small project helped me better understand deployment, launch processes, and what it takes to build and release a product independently.

02 — Approach

My main focus was transforming the keyboard into a tool that would let me play chords within a scale and quickly switch between variations. Very accessible and takes full advantage of hand positioning.

02 — Approach

The interface was designed to feel like hardware and was heavily inspired by modern devices. I also added small visual elements to support live performance and make the learning experience easier.

03 — Outcome

This is still an ongoing experiment that I have continued testing and improving. I am currently working on turning it into an iOS app and a VST plugin, so it can be used inside DAWs.