Superhuman
Superhuman Innovation & Technology Culture
Frequently Asked Questions
Superhuman’s technology culture centers on building practical, human-centered AI at scale, with teams focused on infrastructure reliability, responsible AI, product quality and data-informed development.
- AI infrastructure at scale: Superhuman’s engineering teams work on systems that support more than 40 million daily users across Grammarly, Coda, Mail and Go. One director of engineering described the work as spanning “scaling AI-driven systems,” building platforms that simplify developers’ lives and creating large language model-based product experiences for a global user base.
- Responsible AI as a technical discipline: Superhuman’s responsible AI work is treated as a core product and engineering concern. An AI engineering leader said the team sets standards for AI development, conducts deep research, shares knowledge across the company and builds automated tools for assessing AI safety and safeguarding against known risks. That approach reflects a technical culture that prizes human judgment.
- Data-informed product development: Superhuman’s data science and engineering teams help evaluate product health, user engagement, AI quality and where teams should innovate next. A product data science and engineering leader said the team’s job is to build a “deep and nuanced understanding” of every product and feature, while using data to understand whether products are serving users and improving over time.
- Product integration and technical complexity: Superhuman’s technology culture reflects the complexity of integrating Grammarly and Coda. Engineering and data teams are reconciling different product systems, improving Coda Docs performance through shard-based architecture and developing approaches that help large documents run more smoothly on lower-memory devices.
- External signals:
- Strong Tech Talent: Employees on external review sites describe Superhuman as a strong place for technologists, with reviews pointing to interesting technical problems and user-focused engineering. (Glassdoor; Blind)
- Engineering Environment: Reviews highlight strong documentation, capable coworkers and useful internal tools, highlighting a technology environment built around knowledge sharing and execution quality. (Glassdoor)
- AI Innovation: Employees describe the company’s AI work as cutting-edge and motivating, with one machine learning employee noting that each new AI development creates an opportunity to push boundaries. (Blind)
- Strategic Direction and Product Confidence: Employees express excitement about working on a product they use themselves, with reviews highlighting pride in Superhuman’s customer impact and its position at the forefront of AI-enabled productivity tools. (Glassdoor; Blind)
Bottom line: Superhuman’s technology culture is strongest for employees who want to build AI products at scale while working in an environment that values responsible development, data-backed decisions, infrastructure quality and practical user impact.
Superhuman's Candidate Tradeoffs
If you’re weighing whether Superhuman is the right fit, these are the core tradeoffs to consider.
- Superhuman emphasizes bold, forward-looking innovation that creates breakthrough opportunities and meaningful impact, though that requires comfort with uncertainty.
Superhuman Employee Perspectives
What practices does your team employ to foster innovation, and how have these practices led to more creative, out-of-the-box thinking?
We focus on creating intentional space for innovation — both structured and organic. Each quarter, we run two-day hackathons where small, cross-functional teams tackle ideas of all shapes and sizes. It’s fast-paced and high-energy, and it often sparks some of our most creative solutions — many of which become real product features or internal tools.
We also dedicate time each quarter to “quality weeks,” giving everyone protected space to focus on ideas that matter to them — often ones sidelined by deadlines. This includes tackling tech debt, building prototypes and improving the developer experience. It’s a creative outlet that often surfaces unexpected and very impactful ideas.
Weekly demos keep the team connected and inspired by each other’s work, while ride-alongs with sales and on-call support rotations help engineers build deeper user empathy. Seeing how our work is pitched — or where it causes friction — sharpens intuition and improves decision-making. Together, these practices foster innovation, a strong sense of team bonding and a shared vision for how to deliver real value to our customers. The result is not just better ideas but better products.
How has a focus on innovation increased the quality of your team’s work?
Our focus on innovation has had a direct and measurable impact on the quality of our work — from product design to code reliability to internal tooling. One example came from our support rotation: After seeing how cumbersome it was for support team members to access customer data, an engineer built a secure, time-limited access flow. It boosted both security and support efficiency — born from hands-on experience.
Some of our best product ideas have gone through multiple hackathon iterations. Revisiting ideas with fresh perspectives — across disciplines or teams — often leads to a better user experience and more robust implementation. One such feature shipped after several prototypes, and customer feedback was overwhelmingly positive from day one.
Hackathons have also improved our internal developer experience. Tools like linters, Storybook, and Zod-based validation were first prototyped in these sessions. Once adopted, they boosted productivity, improved code quality and reduced bugs before they hit production. By making space to explore, experiment and reflect, we’re not just generating ideas — we’re delivering better outcomes for our users and teams.

When generative AI initially emerged, the demands on Grammarly’s [now Superhuman’s] infrastructure grew significantly — but Andriy Derevyanko knew what to do.
The director of engineering is no stranger to rapid change, having joined the company seven years ago during its high-growth startup years. So when the need to evolve the company’s infrastructure arose, Derevyanko was ready to tackle what was in store.
“Scaling our cloud platform to keep pace with this transformation has been both a challenge and a privilege,” he said.

Superhuman Employee Reviews


What People Are Saying About Superhuman
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User Experience & Design: Feedback suggests a speed-first, keyboard-centric interface with sub-100 ms interactions and a universal Command palette meaningfully reduces friction versus traditional clients. Split Inbox and focused queues further shift work from one stream to prioritized flows.
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Product Innovation: Feedback suggests Split Inbox/Auto Labels, in-context collaboration (shared drafts/comments), and follow-up reminders reimagine email triage and coordination in-flow. Built-in AI for thread summaries and drafting extends the fast UI philosophy into content generation and cleanup.
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Emerging Technology Adoption: Feedback suggests Superhuman layers AI across mail for summarizing, drafting, and auto-labeling while positioning assistance to work across apps. This indicates embedded, in-flow AI and expansion beyond email into broader AI-assisted work.
























