Hollywood hires through referrals. The only software in the market charged studios $30,000 a production and nobody liked it. I led design end-to-end on a platform that made existing relationships visible and faster to act on — without breaking the trust that drives hiring. Three phases: build the network, turn it into a hiring system, keep people on-set after they're hired.

Before Impact was a hiring platform, it was a Y Combinator accelerator for writers. The writers' strike froze that business overnight, and with Series A runway burning, we zoomed out.
What we found: the crew side of the industry had almost no online presence. Hiring was referrals over email and text — no visibility into who was available or free. The deeper problem wasn't the missing online presence; it was the relationship layer underneath it. The pivot moved fast because the bones already existed — database search, lists, profile structures all transferred from writers to crew. The audience changed; the concept didn't.

Coordinators worked off personal Excel sheets and their own phones, asking friends for referrals. The process lived entirely inside personal contact lists. Roles weren't filled this week — they were filled yesterday, and only the people already top of mind got called.
Hiring outside the circle always hit the same hesitation:
"I'm scared to hire someone new because I don't know how it would reflect on me — and I don't know if they're verified because they weren't part of a guild or organization already."
The decision wasn't just about filling a role. It was a personal reputation bet made under extreme time pressure.
People trying to break in joined paid Facebook groups, hired coaches, took hundreds of coffees — and got almost nothing. Not because they lacked talent, but because the system was structurally closed. Without a network, there was no legitimate path in.
Scenechronize had a near-monopoly on a UI that felt like Windows 2000. Coordinators hated it and used it anyway, because at $30K a production it was the only option. A necessary tool, a captive user base, and a product nobody liked using.
Being unknown was a bigger barrier than being unqualified. Roles filled in hours, so coordinators called friends first. Getting work required experience and experience required work, so early-career crew had no way in. And the one existing tool covered only a narrow slice of the workflow.
How might we open access to opportunity in an industry where who you know determines who gets hired — without disrupting the relationships that make it work?
The instinct was to build a better database. But experienced coordinators weren't struggling to find people — they already had a network that worked. The people left out were everyone outside it.
So the challenge was two-sided: make coordinators' existing relationships visible and faster to act on without disrupting how they hired, and give crew a legitimate path to surface reliability without an established reputation. A tool that only reinforced existing relationships would just digitize the gatekeeping; one that ignored them would never get adopted. The answer was a reputation network that honored trust signals while creating new ones.
Phase 01
Network + Credibility
Solve cold start. Build a network with real signal — people you've worked with, not just people who exist on a database.
Phase 02
Hiring System
Structure the hiring workflow without replacing it. Evolve existing behavior into something faster and trackable.
Phase 1: Building the Network (2022)
Coordinators couldn't hire outside their circle not because they didn't want to, but because the system gave them no way to — no visibility into availability, no trust signals for strangers, no time to vet anyone.
Phase 1 addressed each barrier directly. Profiles and search gave visibility beyond the personal contact list. Availability status answered the speed problem without phone calls. And for trust, we built a clear hierarchy: mutual connections first, shared credits second, profile and experience third.

Claim Your Profile Page (Onboarding as Activation)
Our first approach: use a Variety Insights dataset to pre-populate profiles. Claim your profile, verify your info, jump into the network. Frictionless on paper.
Only 16% of users made it through.
Two problems. People didn't know what Impact was, so a cold email to an unfamiliar profile felt like spam. And some pre-filled credits were wrong, so even curious users hit a wall and bounced. We'd asked people to trust Impact's data before they had any reason to trust Impact at all.
The trust anchor itself was wrong. We shifted from "claim your profile" to "see your network" — leading with relationship signals instead of credits: who from your past productions is already here, who you have in common. Same product, different first impression. That shift drove a 32% sign-up lift. The insight came from LinkedIn: it doesn't open with "here's your profile," it opens with "here's who you know."

Profile Cards — From Static Credits to Filter-Responsive Signals
Original results were credit-heavy — not what a coordinator needs to decide whether to reach out. We shifted emphasis to relationship signals (mutuals, shared collaborators, unions and guilds, network proximity), which took a full backend refactor.
Then we pushed further. Most search UIs treat results as static; we made the filter and the card one connected system. Filter by department, rate, or availability and the card reorganizes to surface those signals first. The filter isn't just narrowing the list — it's telling results what you care about.

Why messaging shipped alongside connecting
Messaging had to launch with the connect feature, not after it. Connection without communication is a dead end — there's no pull. Bundling messaging gave connecting a reason to exist and gave the network a reason to grow.

Phase 2: From Connecting to Hiring (2022–2023)
The network worked, but hiring was still fully manual: search, email, wait, follow up, repeat — across many candidates at once. At production speed that breaks down. The move was to make saved lists actionable.
Avail Check
Avail Check let coordinators send availability requests to their entire saved list in one action and track every response in one place. Crew got an email with full context — studio, dates, role — and one click to respond, with the conversation starting after confirmation, not before. It didn't make people respond faster; it eliminated the time lost before anyone was contacted. We sent requests through email on purpose — not everyone was on the platform, so every request was an invitation in.

What broke first
The first statuses — "Available" / "Not Available" — didn't reflect how hiring works, so coordinators kept tracking nuance outside the system. Working with coordinators from Netflix and HBO, I mapped real states from actual workflows: Outreach sent → Response received → Follow-up needed → Offer made → Confirmed.
Response times dropped from roughly a week to under 48 hours.

Avail Check Pro — validating the idea before fully building it
Before building full self-serve, we ran a paid concierge tier: our CX team did the search and tracking manually through the tracker UI. A Wizard of Oz test — paid demand confirmed real intent, the manual process showed exactly where friction lived, and clients learned the product while we did the work. By the time we handed it back as self-serve, they already knew how to use it.

Phase 3: On-Set Tools
Once hiring worked, retention told a different story. Users got hired through Impact and then disappeared from it — production was happening off-platform in texts, calls, and separate apps. On-set communication was the gap.
Establishing & Scaling The Design System
As the product scaled across three phases and two platforms, I built the design system in Figma on atomic principles — tokens to components to flexible patterns — a shared language between design and engineering that cut implementation back-and-forth and let the team move without losing consistency.
Color tokens, typography scale, spacing system — the layer that never changes across surfaces.
Buttons, inputs, cards, modals — consistent across every screen.
Layout assemblies that flex based on platform and context.












Scenechronize charged $30,000+ per engagement. Impact delivered comparable capabilities at roughly 30% of that cost — and once studios were already using Impact through their coordinators, the enterprise conversation sold itself.
Sign-up lift — driven by shifting onboarding from profile-first to network-first. The trust anchor moved from the company to the user's own relationships.
Hiring response time — down from roughly a week. The time wasn't lost to slow replies. It was lost before the first message was ever sent.
Of competitor's pricing — Scenechronize charged studios $30K+ per engagement. Impact's studio deals landed at a fraction of that, with better UX.
Lifecycle retention — on-set tools closed the retention loop. Users hired through Impact stayed in the platform and were more likely to be rehired through it.
Next Steps & Reflections
Every tool we added — Avail Check, status tracking, the side panel — we asked whether it fit how coordinators already worked. The ones that fit got adopted. The ones that didn't got abandoned.
You can't build a credible hiring tool without a real network. You can't build on-set tools until hiring is actually happening. The sequencing wasn't a roadmap — it was a dependency chain.
The shift from "claim your profile" to "see your network" was a design reframe, not a product change. Same features, different first impression. What you lead with determines whether someone has a reason to stay.
Designing for a 14-hour shoot day forced ruthless prioritization. Every piece of UI that didn't earn its place got cut — and the constraint produced a better product than a relaxed brief would have.