EST. 2026

9:51:03 UTC

SPARKAI

/

2026

One input. Every model.

Nothing in between.

A ground-up rebuild of an enterprise AI workspace — taking a dark, card-

cluttered chat product and turning it into one input-first canvas where choosing a

model, speaking a prompt and reading the receipts all happen in the same place.

WHO WAS ON THIS?

Me (Product Designer)

ROLE

Product Designer

SCOPE

IA · UI · Interaction

PLATFORM

Web Application

YEAR

2026

MY ROLE AND SUMMARY

I took an enterprise AI chat tool that had grown in every direction at once and

rebuilt it around the one thing every session actually begins with — the input.

Model switching, attachments, voice and dispatch all collapsed into a single

container anchored to the middle of the canvas. Chat history got a spine. Answers

got somewhere to keep their receipts. Everything that wasn’t the exchange

between prompt and response got cut.

The measure for every decision was the same: does this shorten the distance

between what the User means and what the system gives back?

CHALLENGE, PURPOSE AND DEFINITION

What’s actually wrong with most AI workspaces?

Enterprise AI tools tend to accumulate. A model gets added, so a card goes on the

home screen. A feature ships, so a button joins the tray. Nothing is ever obviously

wrong, and then one day the prompt field — the only element every single session

touches — is the smallest thing on the page, pinned to the bottom edge, below four

cards explaining models the User already knows.

PROBLEM

The one thing every session begins with was

the hardest thing on the screen to reach.

I PULLED THE LEGACY BUILD APART, AND HERE’S WHAT I FOUND

01

An isolated input zone, detached from the controls that govern it — the model

picker lived in the top bar, attachments in a tray, the field itself at the bottom.

02

Static model cards holding the centre of the canvas, describing Auto Pilot,

Gemini 1.5 Pro, Llama 3.1 70B and Runway to people who switch models

twelve times a day.

03

Chat history with no semantic grouping — nine consecutive threads all

reading “1- Greetings & Salutations…”, which is a list that technically works

and practically doesn’t.

SO I DEFINED WHAT THE REDESIGN HAD TO DO

People running six models a day need one place to

type, one place to look, and no decisions in between.

Before and after, drag to compare

After
Before

Before: four model cards, a payment banner and three tool tabs crowd the canvas and push the input to the bottom edge.

Before: four model cards, a payment banner and three tool tabs crowd the canvas and push the input to the bottom edge.

After: one centred input carries model, attachments and voice, and history is grouped by date with pinned chats on top.

After: one centred input carries model, attachments and voice, and history is grouped by date with pinned chats on top.

THE DESIGN APPROACH

Consolidation first

The model cards came off the canvas entirely. In their place, a single input container sits at the optical centre of the screen and absorbs everything that used to be scattered around it the attachment control, the model selector, the microphone, the dispatch button. One footprint, four jobs.

Chat history moved into a structured sidebar and picked up chronological grouping July 2026, June 2026, April 2026, December 2025 so locating a prior session became a matter of remembering roughly when, not scanning a flat column of near-identical titles. Vector Vault and My Data sit above the fold, where the work actually starts.

MODEL AND VOICE

Both live inside the same footprint

An in-line switcher with search surfaces the whole catalogue — Auto Pilot, Amazon

Nova Micro, Azure ChatGPT 3.5 and 4o, ChatGPT 4 Turbo, 4.1 and 4.1 Mini —

without the User ever leaving the input context. The default is labelled as the

default, so the common path needs no decision at all.

Voice renders as a live waveform inside the field rather than over it. Recording

state, elapsed duration and dispatch occupy exactly the footprint the text cursor

just vacated. No modal, no overlay, no state to dismiss before you can type again.

Modal selection

dictate

NAVIGATION

It collapses when you don’t need it

Navigation is multi-tier and independently collapsible. The primary rail compresses

to icons; the history panel folds away on its own. At full collapse the canvas is

almost entirely input and answer, which is the point.

Per-conversation actions — Pin Chat, Edit, Delete — moved into contextual hover

menus instead of permanent affordances. And a Prompts panel on the right edge

lists every prompt in the session in sequence, so a long thread stops being

something you scroll and becomes something you navigate.

Collapsible sidebar

Per conversation actions

Prompts Panel

OBSERVABILITY

When an answer needs receipts

A complex AI response is three different things at once, so it segments into three

views. Answer carries the structured content, comparative tables included.

Sources exposes the reference links, clickable, for anyone who needs to verify

before they forward. Details surfaces the execution metadata — runtime, model

attribution — so “Executed: 17.40s” is available to the people who care and

invisible to the people who don’t.

In an enterprise context this is the difference between an answer and a usable one.

Full observability, no visual overload.

Answer, Sources, details

Per conversation actions

In AI tooling, restraint is a feature. Every element

I removed from the canvas gave attention back

to the exchange between prompt and response.

SAIF KHAN — PRODUCT DESIGNER

SAIF KHAN — PRODUCT DESIGNER

IMPACT AND LEARNING

Impact

Fewer decisions per prompt. Consolidating model, attachment, voice and

dispatch into one container removed the cross-screen hunt that used to precede

every message.

History you can actually re-enter. Chronological clustering replaced linear

scanning, so returning to a session from three months ago is a date recall, not a

reading exercise.

Answers that survive scrutiny. Sources and execution details are one tab away,

which is what makes an AI output forwardable inside an enterprise.

What did I learn from this?

Subtraction is a design move. The cards weren’t badly designed — they were

well-designed things in the wrong place. Removing them was the largest single

improvement in the project.

Consolidation beats arrangement. I could have spent the whole redesign

moving controls closer together. Putting them in the same container was the

version that actually worked.

Enterprise users want the metadata, just not constantly. Runtime and model

attribution matter enormously — right up until they’re on screen all the time.

Lahore, Pakistan

20

°C

Lahore, Pakistan

20

°C