DS architecture & tokens
Token systems, multi-brand and multi-product theming, mode strategy, foundation vs semantic vs component-level tokens, Figma variables vs Token Studio trade-offs.
I'm Vids, a design systems specialist. I work with design and engineering teams to build systems that product teams reach for by default - and that hold up past the launch party (the easy bit).
Most engagements start in one of these zones. Some stay there, some pull in all three.
Token systems, multi-brand and multi-product theming, mode strategy, foundation vs semantic vs component-level tokens, Figma variables vs Token Studio trade-offs.
LLM-ready design systems, Claude + Code Connect for Figma-to-code pipelines, DS as instruction sets, prompt-aware components, internal DS chatbots and doc tooling.
Coverage measurement, design-to-development handoff, branching workflows, snowflake component management, office hours and showcase rhythms, rollout sequencing.
Each card flips for the approach. Most engagements are framed as a problem and a sequence of decisions — not a sales pitch.
The design team wanted to figure out where Claude actually helps the DSM workflow — not 'should we use AI' but 'given AI is here, where does it earn its keep?'
Walked through Code Connect for Figma-to-code, internal DS chatbots, and concrete prompts the team could use. Filtered AI use cases against the maintenance overhead each would create.
Two designers managing three products with shared DNA, building a platform that's itself LLM-driven. They wanted a DS approach legible to LLMs.
Discussed LLM-ready DS principles: legible naming, predictable structure, machine-parseable docs. Mapped a coverage approach scaled to a 2-person team.
Enterprise logistics org standing up a more formal DS function. Multiple product lines, uneven coverage. What does the right DS posture look like?
Strategy-level discussion on DS scope, sequencing, and team structure for an enterprise platform. Talked through coverage sequencing, governance models, and how to plan workshops for cross-team alignment.
Tens of thousands of color values, no semantic layer governing how they mapped to UI surfaces. New designers couldn't tell which color was for what.
Started with 'how do we reduce this?' and moved into broader architecture. Mapped reduction strategy to semantic naming, walked through a reference color system at scale, and discussed migration patterns.
Two consumer apps sharing near-identical components, but each with hard-coded values. The team came asking for a 'central design system'. The framing was the first thing we revisited.
Reframed the ask from 'central DS' to 'shared token layer + product-specific surfaces'. Worked through Token Studio multi-mode setup, semantic vs foundation token split, and a rollout sequence that didn't require freezing product work.
Internal team experimenting with AI for screen generation, running into the gap between 'AI generates UI' and 'AI generates UI that fits our system'.
Connected DS strategy with AI prompting. Discussed how to shape components so they're prompt-friendly, and how to close the gap between generated screens and system fidelity.
Agency team wanting a repeatable DS approach across client projects. Less theory, more 'show us how this works'.
Hands-on session through foundation tokens, component patterns, and a repeatable kickoff kit they could adapt per engagement.
All prices are starter rates. Most engagements begin with a short scoping call so we can pick the right format.
₹5K – 10K
30–60 min, 1:1
₹20K – 50K
1–3 hrs, up to 7 people
₹50K – 1L
Half or full day, up to 15 people
₹1L – 2L / mo
2–4 sessions per month
By day, I lead Design System 3.0 at Keka HR — a four-lane initiative spanning core system, adoption, accessibility (WCAG 2.2 AA), and AI tooling.
This consulting practice is what I do off-work, advising other teams on the patterns and trade-offs I'm working through in real time.
The Bigbasket work is what most informs the consulting — building a token system that supported multi-brand theming, mode strategy across 15+ products, and an in-house Token Studio to Flutter converter pipeline.
I run Decode Design Systems, a designer community in Bangalore. 160+ mentees on ADPList. Speaking at AI BuildCon 2026 and VizChitra 2026.
Teams often ask for a specific solution when the actual problem is upstream. The first 30 minutes are usually about reframing the problem.
Token systems, governance models, adoption sequences should start with one or two components, not the full library. Run a POC, prove the workflow, then scale.
A DS that lives only in Figma is just a style guide. The interesting work is in the bridge — converters, naming, code-design parity, dev mode workflows.
Send a short note about what you're working on. Most engagements start with a 30-min call to figure out scope and decide if we're a fit. I usually reply within 24 hours.