Midnite’s edge is product quality. That’s a real challenge in a heavily regulated industry, where compliance, risk and trust shape every design decision as much as usability and visual polish do. As the company doubled to ~200 people and raised their Series C, that quality was at risk of either becoming the bottleneck or being diluted. Meanwhile, AI raised serious questions around how many new designers were even needed vs how far augmenting the existing team could get.
I came in two days a week to work through both. The brief was to build and level up the design team, and to take weight off the Head of Product as the product org grew. In practice, that meant working closely with the designers on everything that shipped, and alongside product and exec leadership on company-wide scaling decisions.
Pressure-tested Series C headcount planning and org design
Nobody wanted to hire a bunch of designers and find that AI had made half the roles unnecessary. Nor to under-hire and watch quality slip. I worked it through with the exec team with one foot in what larger organisations genuinely need, and the other in what AI now makes possible, separating the work AI could absorb from the capability they needed to hire for. That led to confident decisions on headcount shape, seniority and sequencing, including where to invest in horizontal capabilities like design systems, design ops and AI.
Doubled the product design team from 3 → 6
Each new hire needed to complement the existing team, while deepening a core capability such as product strategy, AI fluency or design engineering. That gave the team more to learn from one another, and made design a genuine partner to product and engineering. I built the recruiting funnel from scratch: job descriptions, interview guides and scorecards. I engaged a specialist recruiter alongside it to accelerate sourcing, and then trained the panel so hiring decisions ran on evidence rather than vibes. Everything was shared in a single Notion space, which spread interviewing skill well beyond design. Alongside that I wrote the product design career framework from scratch, fed into the PM ladder, benchmarked salary bands, and ran the Head of Design search to a strong final shortlist.
Established quality, alignment and consistency as a team habit
The existing team had talented individuals, but needed the right rhythms to get visibility and feedback on each other’s work to keep the end-to-end experience consistent and high-quality. I established a few key weekly rituals that helped galvanise the team and improved decision-making quality: a weekly design sync (across product, motion and brand design in a single room), design critiques, design jams and 1:1 coaching sessions. While these started out with strong steer from me to set standards, they quickly grew into self-sustaining rituals where the team resolved trade-offs together. The signal it was working was subtle. People started making, on instinct, the calls I’d been giving feedback on for weeks. For instance, when to reach for bespoke, inventive UI, and when a faster, more boring pattern was the right answer.
Enabled faster cross-functional product teams with clearer remits
When I arrived, product, design and engineering all operated quite independently. That helped early on, but it was starting to slow momentum, with decisions drawn out and often trapped in DMs. I introduced and led Product Reviews, bringing the three functions into the same room to make calls together on a regular cadence.
Three new product teams were stood up in this period, focused on areas such as onboarding, internal tooling and new customer experiences. I worked with the incoming PMs and exec leadership to shape each team’s direction, goals and remits, and pulled brand, product and marketing design closer so the work held together across the whole experience.
Shaped AI strategy for the whole company
The headcount question needed a company-wide answer, so this took my input well beyond design. Together with another AI consultant, I interviewed the entire exec team and surveyed every function to uncover areas where AI would genuinely help. We then ran company-wide AI upskilling workshops, an AI champions programme, and recommended the tool stack to weave an AI-forward mindset into every corner of the company. Design culture shifted alongside it, from sharing static Figma mocks to interactive prototypes, which pulled the whole toolkit toward motion, real data and testable artefacts. The last piece was shaping Midnite’s 2026 AI strategy, to establish clear guidance and focus areas for their incoming permanent Head of AI.
After eight months I left a design team twice the size, and enough lightweight structure for its impact to keep compounding without me: the hiring engine, the weekly rituals, the career framework, and an AI strategy that reached well past design.
Plus, it was genuinely FUN. This is the work I find most energising: helping a startup scale quickly without losing the spark that made it worth scaling in the first place.