John Howrey
Available for new work

do.next

A North Star vision for the next decade of DigitalOcean, told as four vignettes about the people who use it

Opening title card on DigitalOcean blue: 'Every company lives between what they dream of and what they can build today,' with 'dream of' and 'build today' highlighted in mint

Every company lives between what they dream of and what they can build today. That space can feel impossible. In the gap between the idea and the first step, complexity and decision-making stop momentum cold.

DigitalOcean closed that gap once. We made the cloud feel simple. We made getting started effortless. Over time, the world got louder, choices multiplied, and what was simple became harder to see.

do.next is a Shared Services initiative I led to bring that clarity back. It turns intelligence into conversation, and conversation into action. It lets the platform understand intent, not just inputs. The artifact you'll see most of in this case is the seven-minute North Star vision video. Its job was to get the whole company on the same page about what DigitalOcean was becoming. It worked. The work underneath the video is the part the company actually uses on Mondays.

I led design strategy, customer research synthesis, art direction, and motion direction. The deliverables are the vision video, a customer-empathy reading packet, a Shared Services leadership offsite playbook, and a phased rollout plan that turns each future-state concept into a near-term shipping bet.

Vision video, available for review on request

The seven-minute video is shared privately with recruiters and clients on request. The stills below cover the major beats.

A mission card on DigitalOcean blue: 'DigitalOcean is an outcome-driven, intelligent platform that helps people build with clarity and confidence,' set in clean sans display type

The foundation

Built from four customers.

Before we wrote a frame of the vision video, we wrote four customers. Each one is a composite drawn from real evidence: customer interviews, the Ideas Portal, post-call recap notes, NPS comments, and patterns in the support ticket queue. The video is a collection of vignettes built from these customers; small, honest snapshots of real needs and real ambition that, together, show the future do.next was made to unlock.

LucentAI, a small AI research collective leaving a hyperscaler for clarity. Their move to DigitalOcean starts as a cost decision and becomes a rediscovery of autonomy.

StudioMosaic, a design-engineering studio in Mumbai running thirty client environments off one parent org. Their growth pain is administrative, not technical. They want the platform to stay invisible.

Kindred Systems, a seven-person AI startup shipping like they're sixty. They want speed they can trust. The line "speed's no good if we don't trust it" is the heartbeat of their story.

Orion Labs, a well-funded enterprise training massive generative models. Their challenge is not capacity. It's transparency. Power isn't the problem; explanation is.

The four stories share a cast of archetypes. An infrastructure lead who wants to see what's happening. An automation engineer who wants the system to behave the same way twice. A designer who wants the data to be legible to people who aren't engineers. A founder, director, or CFO who wants the spend to match the forecast. The same humans recur across every customer scale; the platform we're building has to recognize them.

The starting point

What we had to move past.

The DigitalOcean a developer used to know was a form. Choose an image. Choose a size. Choose a region. Choose options. Add a key. Click create. The form was famously simple, and that simplicity was the company's first growth engine. It is also where the work stopped. The platform asked a developer to know what they wanted before they ever asked for help knowing it.

The original DigitalOcean homepage circa launch: 'Simple Cloud Hosting, Free unlimited bandwidth, Deploy a virtual server in 55 seconds,' with the early Create-a-Droplet form floating above a flat illustration of clouds

The unlock

Type anything. Launch, scale, ask.

The center of the new platform is one input. A monospace prompt that runs across the top of every page and accepts a sentence. Launch a droplet in NYC. Scale my postgres cluster. Search the docs for managed Redis. Investigate the latency on api-gateway-prod. The product no longer asks a developer to remember which tool answers which question. The prompt does the routing.

A wide screenshot of the new DigitalOcean header: monospace prompt across the top reading 'Type anything: launch, scale, search documentation,' with the Dashboard / Projects breadcrumb and an API Inference API page title beneath, status pill reading Healthy

Vignette one · StudioMosaic

A latency spike at the end of the day.

StudioMosaic is a design-engineering studio in Mumbai. Their work keeps their clients' worlds online. Maya manages the accounts. Serena runs operations. It's late in the day when a Slack alert lands; latency is spiking. Easy enough. They tell the platform to run an investigation. The system responds in plain language; no jargon, no guessing.

Most days they'd fix the issue from inside Slack. This one feels different. They want to look a little deeper before they act. In the control panel the investigation is already waiting. First things first: keep the client safe. A quick rollback holds the line while they sort it out. A moment later, confirmation: rollback successful.

Now they can solve the root problem, and it's obvious once they see it. Set the service to autoscale, exactly what DO recommends. Preview the change. Test it. Everything stabilizes. The client never knew how close they came to an outage. Maya and Serena knew. DigitalOcean knew. Together, they handled the whole thing with calm, clarity, and almost no lift.

An AI investigation panel: 'Investigation complete: High latency spike detected on api-gateway-prod,' followed by a written root-cause analysis describing a flood of /stress requests from a specific IP that drove CPU usage from ~171% to ~1517% in 25 minutes, with a mint High confidence pillA chat support transcript: a developer reports intermittent 502 errors on a load balancer; the assistant identifies the LB-NYC3-prod cluster, reports that 2 of 4 backend droplets are failing health checks, ties the failure to a recent deploy, and offers a 'Show specific droplets and logs' quick reply
A production-environment region selector with a stepped progress bar reading 'Select a region' and 'Select a stack,' a glowing mint outline around a 'Production environment: New York City, 12ms latency' card, and a partial San Francisco card to its right

Vignette two · Orion Labs

Anjali wanted a report.

Orion Labs trains huge generative models. Their work turns data into imagination. Their CFO, Anjali, is the one who has to make the math add up. Every experiment racks up GPU minutes. She needs a clear view of spend from the last month. Her team built her a dashboard for it. She's not convinced; tools like this usually break the moment you need them. Still, she clicks.

It's there. Clean. Straightforward. Tailored for her. One thing catches her eye: a suggestion from DO about how to save money. Seriously? They're telling me how to spend less? She tries the simulation. It shows the change, the impact, the new bill. Eighteen percent savings. That's not nothing. She sends it to her team, approves the update, and notifies the rest of the org.

She thought she wanted a report. Turns out she wanted a decision. The safety net helps too: she can roll the change back for the next 48 hours if anything feels off. With one adjustment, she has something she hasn't had before: a real sense of control. Not just watching the spend, but shaping it.

A cost optimization simulation panel: GPU instance usage at 65% with a recommendation to use lower-cost spot instances for non-critical workloads, scheduling optimization on, and a current monthly bill of $174,000 vs a projected monthly bill of $173,638 in mint greenAn AI-generated migration plan: a 2-node HA cluster card with 'Why this choice? People like you typically choose this,' a region card showing FRA, and two large buttons reading Run a test simulation and Create this managed database, with a summary listing engine, vCPU, and memory

Vignette three · StudioMosaic again

Ninety seconds. That's all it took.

StudioMosaic is growing. New client, new request, another chance to move fast. Serena opens the Copilot bar. Add monitoring for Client A. The Marketplace slides in right where she's working. The defaults look right. The price looks right. She installs it. A moment later: monitoring added to all Client A projects. Ninety seconds. That's all it took. Serena walks away feeling like she can take on the whole week.

An agent setup screen: 'Recommended options' panel for adding a knowledge base, a checkbox to 'Connect agent to VPC network' with the helper text 'Make sure traffic doesn't leave the private network,' and an 'Add Tags' section below

Vignette four · One conversation

Continuity, at last, between the human and the system.

Serena opens a support thread in the Control Panel Copilot. Hours later she switches to the CLI. The same conversation is right there waiting. Continue troubleshooting? She does. The dialogue flows through Console, CLI, and Support, uninterrupted, aware of everything that came before. When a DO engineer joins, they see the full trail: logs, commands, outcomes. The issue gets resolved without anyone repeating themselves.

A CLI session continuing the previous chat: the assistant recognizes the developer has switched terminals, restates the prior context (LB-NYC3-prod, 2 droplets failing health checks), prints a list of api-server droplets with health-check status, and recommends investigating the /health endpoint on the failing serversA permissions query result: prompt reads 'Who can access Spaces data,' answer reads 'Good question! On this team, currently 4 team members have access to Spaces.' Four cards show team members and their permission counts; one card outlined in red flags a contract dev with 9 Spaces permissions versus the others' 6

The platform that knows you

Welcome back, by name.

The dashboard greets the developer the way a colleague would. It already read the activity feed; it already knows the migration finished; it already saw the spend trend. The opening line is a paragraph in plain English with the next two actions ready to click.

The new DigitalOcean dashboard top: 'Hey, Anjali. Hope your week has been going well!' followed by a written summary that starts 'Welcome to your new dashboard! Check below for some [ways to] optimize costs. Your team's migration from Azure went [well]. Things are up and running.' Below it, a Your Projects header with API Inference API and New Project tiles
The proactive dashboard layout: a left rail listing Droplets (AI Inference API), Database (lucentai-metrics), Quick Create New Resource; a Recommended Actions card group with 'Enable automated backups based on your history' and 'Publish your deployment template'; an activity feed showing 'Storage Monitor: Your spaces were reconfigured to free up some storage' and 'Migration Assistant: Your migration from AWS completed with 0 errors'; a Security Alerts card reading 'Phew. New issues reported'; and a Billing column with Total Team Spend, Subscription Spend, Usage-Based Spend, and Org Spend tiles each at 41% with month-over-month deltas

From vision to rollout

A video, then the work.

A vision is only useful when other people can navigate by it. The video is the headline; the work is the rollout. We paired the do.next North Star with a phased plan that converts each concept into a shipping bet.

The shell and navigation, rolled out in phases through the Control Panel: collapse the legacy left rail, introduce the universal prompt, layer in outcome-based menus, then add a contextual workspace mode and dark theme. Phase one shipped first; the rest follow on a calendar. I keep a public-facing rebuild of that shell on this site as Seashell UX; same vocabulary, same phased thinking, generic so anyone can poke at it.

The customer-empathy reading packet, used as the pre-read for a Shared Services leadership offsite. Four customer composites, a spread-coverage framework, lifecycle tables, and an evidence ledger so any product team can trace a vision concept back to a real customer ask.

The cross-org product story, used in roadmap reviews to keep teams aligned on the same future. The shared archetypes, in particular, gave product, engineering, design, and go-to-market a vocabulary that didn't fragment when translated across functions.

A component library and tooling plan, scoped under Shared Services Design and UI Engineering, so the surfaces in the vision video can converge on the same shell rather than rebuilding the same patterns locally.

Not more tools. Better outcomes. A cloud that listens, learns, and works alongside its users.

Outcome

Across LucentAI, Kindred, StudioMosaic, and Orion Labs, the work looked different but the pattern was the same. Each team found something essential: clarity, momentum, resilience, foresight. They all began in the same place we opened with; that tension between what they imagine and what they can actually do today. do.next closes that gap again. By turning intelligence into conversation, and conversation into action, we help people move with confidence.

Takeaways