ZACHARY MACTAVISH.

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Client

Giga Intelligence

Role

Lead Designer to UX Consultant: Brand & Web App

Timeline

1.5 years (ongoing)

Platform

Brand / Web App

Designing at the frontier of AI product design: where the agent is the product

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Giga landing page on a MacBook, Why join Giga?

Overview

Giga began as a privacy-first social and content platform built around user ownership of information. Its AI-native version lets people create agents, research topics, and publish short-form and long-form content with AI support.

Founder Richard Devlin brought me in as lead designer at the product's earliest stage. Over a year and a half, I designed the brand and web app across both versions before shifting into a UX consulting role.

My Role

Across the Giga engagement I was responsible for:

Brand strategy and identity design: icon, wordmark, and full visual system

UX architecture and interaction design for the full web app

Visual design across all core product surfaces

Designing onboarding, social feed, content creation, AI chat, and bot creation flows

Ongoing UX consulting as the product evolves into its AI-native version

Two iMacs displaying the Giga social and content platform

Design Goals

The goals shifted meaningfully between V1 and V2, but the brand foundation needed to hold across both.

For V1, the priorities were to establish a trustworthy, clean visual identity that communicated privacy and user ownership; to design a social and content creation experience familiar enough to onboard users quickly but distinct enough to signal something new; and to build a design system flexible enough to grow with the product.

For V2, the priorities expanded: evolve the UX to support AI-native interactions including chat, bot creation, and agent-assisted writing, without losing the social and content creation core; maintain visual continuity with V1 so the brand felt like it had grown, not pivoted; and design interfaces that made AI feel useful and accessible rather than complex or intimidating.

The Brand Identity

The Giga identity combines an icon and wordmark built to work across browser tabs, app icons, marketing materials, and product UI. The elements work together or independently, giving the brand range without losing recognition.

Clean white, light blue, and editorial typography distinguish Giga from darker AI products and high-intensity social platforms. The system makes the interface feel open, focused, and credible for people creating and sharing knowledge.

The identity was designed to extend from Giga's privacy-first V1 into its AI-native V2. The icon, palette, and typography carried forward intact, preserving recognition as the product evolved.

Brand Identity in Practice

The identity comes together in the live marketing site: the dual-tone logo mark, an editorial serif paired with Poppins across the UI, and a palette built on clean whites and Giga's signature blues. That combination set Giga apart from the dark, dense aesthetic of most AI products, reading as professional and approachable rather than intimidating. Because the system was codified early, it carried from V1 straight into the AI-native V2 without a rebuild.

V1: Privacy-First Social Platform

Giga V1 was a privacy-first social and content platform built around user control of data and channels. It offered a deliberate alternative to mainstream platforms that monetize user information.

The design paired familiar social patterns with a quieter, more intentional experience. Clear hierarchy and restrained UI kept attention on the content rather than the interface.

I designed the end-to-end product system for onboarding, discovery, profiles, channels, and content creation. The work covered short-form and long-form publishing across the platform.

Isometric grid of Giga V1 social platform screens

The V1 system: a privacy-first social and content platform built around user-owned data and private channels.

iPad displaying the Giga content marketplace interface

The same content-first system, translated cleanly to tablet.

Light & Dark, Across Devices

V2: AI-Native Platform

The evolution to an AI-native product introduced a new layer of design challenges and a more expansive product vision. Giga V2 is built around an agent model: a user identifies a topic they want to explore, the AI helps them research it deeply, and the platform supports publishing what they've learned in both short and long-form content. The social layer remains, but the intelligence layer is now the primary differentiator.

Designing the AI-Native Flows

AI Chat Interface lets users work with Giga's AI and custom bots in a conversational research space. Hierarchy, response formatting, and long-form output make it feel like a capable partner rather than a generic chatbot.

Bot Creation gives non-technical users a clear path to build their own AI bots. The flow exposes useful control without feeling like system configuration.

Agent-Assisted Content Creation connects research, writing, and publishing in one continuous workflow. Users can move from an AI conversation to the editor without losing momentum.

Feed and Publishing brings AI-assisted work into Giga's social layer alongside user-created posts. The redesign preserves discovery and engagement while supporting the new content model.

Giga marketing slide, Your journey, your expertise, your AI

Personalized intelligence: each user shapes an agent around their own expertise and goals, so the AI works the way they think.

Bot creation: a flow built so non-technical users can stand up their own AI agent in minutes, while still surfacing control for power users.

Giga build-your-agent step, choosing a learning goal

Bot creation, continued: a guided flow that gets non-technical users to a working, purpose-built agent in a few simple choices.

Collaboration

I worked closely with Richard Devlin, whose product vision and technical depth shaped key design decisions. Xing Yi and Joel Fernando handled front-end development, and the work stayed grounded in engineering constraints throughout the engagement.

Challenges

The central challenge was keeping Giga coherent as its value proposition shifted from privacy-first social networking to AI-native research and publishing. The brand and interface system needed to evolve without losing continuity between V1 and V2.

AI chat, agent creation, and assisted workflows still lack settled interaction conventions. The work balanced emerging patterns with Giga's users and product goals instead of copying larger AI platforms.

Giga marketing slide, Jon taught his AI his favorite recipes

Outcome

Both versions of Giga are live and active. The platform continues to grow and evolve, and my engagement has matured from hands-on designer to UX consultant, contributing strategic and experiential guidance as new features are conceived and built. The brand identity has held across both versions of the product, proving the durability of the original design decisions.

Giga companion confirmation, Louie is your new AI companion

The payoff: a personal AI companion that lives across the platform, ready whenever the user calls on it.

Reflection

Giga pushed me to design AI as core product architecture rather than an added feature. Building a platform where the agent is the product required new interaction models beyond conventional product patterns.

The strongest lesson was to make intelligence useful rather than impressive. Every flow had to help users think, write, or learn more effectively, or it did not belong.

That standard, useful over impressive, is one I carry into every product I work on now.