Senior Product Designer - Growth
About the job
- A portfolio demonstrating strong product design fundamentals and measurable outcomes, including identifying opportunities, understanding a funnel, choosing measures, testing ideas, and improving a shipped product.
- Experience owning ambiguous, complex work from problem framing through launch and iteration, creating clarity and making progress without a complete brief.
- Ability to form hypotheses, choose success and guardrail measures, and interpret quantitative and qualitative evidence with Data partners.
- Ability to independently build interactive prototypes using modern AI tools, prompt effectively, work near code, and learn tools to validate ideas.
- Ability to design clear, trustworthy experiences across skill levels and abilities, considering interaction details, edge cases, language, accessibility, and recovery.
- Ability to work directly with Product, Engineering, and Data, explain tradeoffs, seek feedback early, and stay involved through implementation; judgment about when to use or evolve a system versus using a one-off approach.
- Own the self-serve experience across onboarding, activation, adoption, monetization, and retention for people and agents.
- Identify high-impact opportunities through customer research, product data, and direct use of Vercel.
- Co-own Growth strategy, priorities, hypotheses, and success measures with Growth Product, Engineering, and Data.
- Build and test working prototypes using tools such as Figma, v0, Cursor, and Claude Code.
- Design and ship experiments, stay involved through implementation, and interpret results while considering trust, accessibility, and the broader funnel.
- Turn successful experiments into durable product improvements, reusable patterns, and better internal tools, and share learnings to improve Design and Growth.
- Experience shipping AI or agent experiences.
- An engineering background or experience contributing production web code.
- Experience designing developer tools, infrastructure, or other technical products, or familiarity with Vercel.
About the company
Vercel provides a platform for building, deploying, and managing modern web applications. It runs a managed, global rendering layer that handles serverless execution so content is delivered quickly anywhere without extra infrastructure. It also offers AI-powered media tools for automatic tagging, smart cropping, context-based transformations, and lifecycle management (auto-tagging, access control, and admin roles). The platform integrates hosting, deployment, routing, and security (automatic HTTPS, encryption, DDoS protection, firewalls) in one service. This makes Vercel different from competitors by offering a unified, globally distributed hosting and rendering stack with built-in AI-enabled media workflows, trusted by millions of developers and thousands of enterprises. The goal is to help developers and businesses ship fast, secure web apps at scale with scalable hosting and AI-assisted media management.
Company Size
1,001-5,000
Company Stage
Series F
Total Funding
$863M
Headquarters
San Francisco, California
Founded
2015
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Simplify's Take
What believers are saying
- September 2025 funding valued Vercel at $9.3 billion, extending runway.
- October 2026 AI Gateway added Microsoft models and Browserbase tools, expanding usage.
- Vercel’s AI Accelerator returned in February 2026 with $6 million credits, strengthening ecosystem lock-in.
What critics are saying
- Cloudflare Pages and Netlify attack Vercel’s pricing with broader framework neutrality.
- Heavy Next.js dependence makes framework share loss an existential risk by 2027.
- AI model launches commoditize Vercel’s differentiators, squeezing margins and platform switching costs.
What makes Vercel unique
- Next.js remains Vercel’s core moat, tightly coupling framework, hosting, and AI tooling.
- AI Gateway centralizes models, tools, and billing into one developer workflow.
- v0 and AI Gateway turn Vercel into an application-creation layer, not just hosting.
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Benefits
Health Insurance
Stock Options
Company Equity
Professional Development Budget
Unlimited Paid Time Off
Remote Work Options
Home Office Stipend
Growth & Insights and Company News
6 month growth
↑ 0%1 year growth
↑ 1%2 year growth
↑ 1%The startup helps developers build AI agents that work over iMessage, SMS/RCS, email, and other messaging platforms. It's a bet that consumers will increasingly
Nudge Security Unveils Adaptive Risk Management to Track How SaaS and AI Risk Changes as Usage Evolves After Approval TMCnet News [September 30, 2026] | / | Nudge Security Unveils Adaptive Risk Management to Track How SaaS and AI Risk Changes as Usage Evolves After Approval New capability continuously reassesses risk as employees connect integrations, expand access, and adopt AI tools, closing a gap left by one-time vendor reviews. AUSTIN, Texas, Sept. 30, 2026 /PRNewswire/ - Nudge Security, a leader in SaaS and AI security governance, today announced Adaptive Risk Management, new functionalities that respond to changes in SaaS and AI vendor risk as well as internal usage, helping security teams to more effectively manage risk across a sprawling SaaS and AI attack surface. Most organizations evaluate a vendor once, during procurement, and treat that assessment as settled. But an application's criticality and risk to a specific business isn't static. After the vendor review and approval is complete, employees often connect it to other business apps and AI agents, share more sensitive data, or invite more internal and external collaborators - often without security's knowledge or review. Traditional third-party risk tools are built to monitor a vendor's external security posture and internal security controls applied once. They are not built to reassess or apply additional security controls as enterprise usage changes. Nudge Security does both, continually monitoring vendors' external risk posture and recalculating an application's risk score as internal usage changes. As risk scores change, Nudge Security applies and recommends appropriate mitigating and compensating controls, natively and through third-party security integrations, creating a truly adaptive risk management program. "Nudge provides a relational view across applications, users, integrations, browser extensions, and authentication that surfaces where security actually needs improvement," said Diego Izquierdo, Senior Cybersecurity Engineer, Third Party Risk Management at Mercado Libre. "For example, an organization can have very strong controls in a tool like Slack, but if users connect less-secure third-party apps into it, that can create a breach path without anyone realizing a new risk was introduced. That integrated perspective on risk is wat makes Nudge unique." Third-party involvement in breaches has risen 60% year over year to account for 48% of all breaches, according to the 2026 Verizon Data Breach Investigations Report. Compressed vulnerability cycles in the post-Mythos era stand to accelerate that trend further, and recent supply chain incidents (including those at Vercel, Salesloft Drift, and LastPass) have already shown how quickly access granted to one application can expose an entire environment. Security teams are increasingly asked not just whether a vendor is secure, but what that vendor's access can actually reach inside their environment right now - a question a point-in-time review can't answer on its own. Compounding this challenge, most organizations actively manage only 30-40% of the SaaS and AI tools actually in use, and typically discover two to three times more tools than they expected with Nudge Security. Adaptive Risk Management is built to close that gap by continuously combining what's known about a vendor's security, supply chain risk, and compliance program with what's actually happening inside a customer's own environment. * Automatic app criticality tiering: Every application is automatically classified by the breadth of use across the organization along with the sensitivity of the data it typically handles, using a proprietary AI model that identifies up to 29 distinct data types, so security teams know which applications matter most without reviewing each one manually. * Continuous risk scoring: Each application gets a dynamic risk score built from more than 30 factors, combining a vendor's external security posture with how that specific application is being used inside a customer's environment: approval status, access granted, data touched, MCP connections, who or what is using it, what security controls in place, and what security findings are failing. Scores update automatically as those factors change, rather than waiting for the next scheduled review. That includes signals like whether a vendor's OAuth grants are stale or unused, whether an AI agent or integration is connected to the app, and whether employees are authenticating through single sign-on or with standalone credentials. * A direct line from risk to action: Nudge Security ranks the specific control gaps driving an app's risk score - such as enabling SSO or closing a stale OAuth grant - by how much closing each one would reduce that risk, and in many cases security teams can act on it directly from the risk panel. The platform also adapts its own monitoring as an app's importance changes: mark an app business-critical, and Nudge automatically begins surfacing additional findings for it - like password reuse or weak authentication - that weren't being tracked before. Risk scores update automatically as those factors change - and Nudge Security customers using strong compensating controls like SSO and MFA can reduce an app's residual risk by as much as 60%. "Too many organizations still treat third-party risk as an annual exercise, while in reality, the conditions that impact risk change every single day," said Jaime Blasco, co-founder and CTO of Nudge Security. "An application approved for a handful of employees becomes entrenched across the business. Someone connects an AI tool to sensitive data or grants an integration broader access. A breach at one of your vendors suddenly turns that access into a potential path into your environment. Your last vendor assessment won't tell you what's at risk now. Fog Computing World built Adaptive Risk Management to connect changes in usage, access, and a vendor's security posture so security teams can continuously reassess their exposure and act as it changes. Nudge Security built its risk model on its own data rather than third-party scoring services, drawing on a self-populating database of more than 250,000 SaaS and AI vendor security profiles. That means Adaptive Risk Management can assess an application from the moment it enters an environment, without requiring vendor cooperation, manual data entry, or even prior knowledge that the application was in use." Availability Adaptive Risk Management is available now to all Nudge Security customers. About Nudge Security Nudge Security delivers SaaS and AI security governance at the Workforce Edge, where employees make thousands of technology decisions daily. Its automated, policy-driven guardrails reach employees when and where they work, enabling rapid technology adoption while minimizing risk and sprawl. Through unrivaled discovery capabilities, AI-driven risk insights, and behavioral science-based engagement, Fog Computing World make security a natural part of how modern work gets done rather than an obstacle to innovation. Nudge Security was founded in 2021 by Russell Spitler and Jaime Blasco and is backed by Cerberus Ventures, Ballistic Ventures, Forgepoint Capital, and Squadra Ventures. Media Contact: Danielle Ostrovsky Hi-Touch PR [email protected] View original content to download multimedia:https://www.prnewswire.com/news-releases/nudge-security-unveils-adaptive-risk-management-to-track-how-saas-and-ai-risk-changes-as-usage-evolves-after-approval-302893378.html SOURCE Nudge Security [ Back To TMCnet.com's Homepage] |
Blazity to address frontend architecture challenges in Generative AI Companies at Next.js Conf: London Watch Party. September 29, 2026 Originally posted on October 23, 2023 @ 06:00 Last Updated on: 29th September 2026, 05:54 am Blazity, a software consulting company specialising in Next.js development, will be participating in an expert panel discussion on the frontend architecture challenges encountered by Generative AI Companies at the Next.js Conf: London Watch Party. Organized by Vercel, the Next.js Conf stands as the foremost event for the entire Next.js community, uniting developers and business leaders committed to advancing the ecosystem. Blazity's co-founder, Jakub Czapski, will take part in the expert panel, which aims to emphasise the significance of frontend technologies, particularly Next.js, in shaping the user experience for generative AI companies. In collaboration with experts from WPP, Jakub will delve into the distinctive challenges faced by AI companies, highlighting the pivotal role that Next.js and headless architecture play in resolving these issues. With the swift adoption of AI-driven solutions, AI companies often grapple with rapidly expanding user bases and escalating data demands. Blazity ardently advocates for headless software architecture, which disentangles the frontend presentation layer from the backend logic and data layer. This decoupling facilitates horizontal scalability, empowering startups to efficiently manage surges in traffic and data volume. Headless architecture empowers AI startups to experiment, iterate, and make alterations to the frontend independently of the underlying AI algorithms or backend infrastructure. It enables them to update the frontend interface autonomously, resulting in accelerated time-to-market and the ability to swiftly adapt to evolving business requisites. Jakub Czapski, Blazity's co-founder, asserts, "Integrating backend AI models with the frontend and performance optimisation are just some of the challenges highlighted by our clients. We believe that with its server-side rendering, speed, scalability, and flexibility, Next.js is truly the best frontend framework for Generative-AI companies." He further emphasises, "As the AI landscape is growing and changing rapidly - time to market is key. Headless architecture enables horizontal scalability, allowing companies to handle high traffic and data volumes more efficiently. They can scale the frontend independently from the backend, ensuring optimal performance and responsiveness even during peak usage periods." During the panel discussion, participants will also explore other challenges encountered within the broader AI ecosystem, such as bridging the skills gap and locating talent well-versed in the unique intricacies of frontend development for AI applications. This panel promises to be an invaluable resource for developers and organisations seeking to harness the full potential of Next.js and headless architecture. Blazity's involvement in this discourse reaffirms the company's unwavering commitment to remaining at the forefront of technological advancements in web development. Shareable URL
Daily AI roundup: updates from Anthropic, openai, and Qualcomm. AI-generated illustration Today's AI roundup highlights significant updates across cloud development sessions, workplace software integrations, and efficient on-device computing hardware. Tech companies continue expanding how developer tools and artificial intelligence agents function across daily workflows in the apps sector. Major AI roundup developments. Anthropic announced that Claude Code cloud sessions have exited research preview to become officially available. This update enables tasks to persist even after users close their laptops, and Anthropic is providing a $100 credit for Pro subscribers alongside $250 for Max users, as reported by @ClaudeDevs. In addition, Anthropic launched Claude Marketplace as a single directory hosting integrations, consulting partners, and agent purchases. The directory includes connectors for Slack and Notion, software from Cursor and CrowdStrike, and consulting services from Accenture and Deloitte, according to @claudeai. OpenAI updated ChatGPT Voice inside ChatGPT Work on web and mobile devices to access plugins for Slack, email, and calendars. Furthermore, the voice feature can now run on Astra, Sol, or Luna models to support professional users in the modern economy, according to @OpenAI. Developments in AI agents. Cursor reduced agent token costs by 7% without reducing output quality by refining prompt structures, compressing file reads, improving caching, and selectively loading tools, according to @cursor_ai. Meanwhile, Cognition integrated its Devin coding agent into Microsoft Teams and Microsoft 365. This integration links Devin directly to email, chats, files, and calendars within corporate environments, as stated by @cognition. Vercel introduced persistent Drives in public beta for Vercel Sandbox across all account tiers. Sandboxes support up to four Drives of 16 TiB each to retain agent workspaces, code dependencies, models, and files between active executions, according to @vercel_dev. On-Device hardware and chips. PrismML demonstrated its one-bit Bonsai vision-language model executing locally on smart devices powered by Snapdragon AR1 Gen 1. The setup showed fourfold lower memory consumption after optimization for the Qualcomm Hexagon NPU, as reported by @PrismML. Finally, Liquid AI partnered with Qualcomm to run its Liquid Context system directly on the Hexagon NPU found in Snapdragon chips. This engineering step provides local personal context for autonomous agents on mobile hardware, completing today's AI roundup overview as noted by @liquidai.
Pixel Canary is free on Vercel's AI Gateway, and it's built for interfaces. A new model just landed on Vercel's AI Gateway that scores near the top of frontend coding benchmarks and costs nothing right now. Here's what that means if you're a designer building your own app. By VibeLab · September 26, 2026 Vercel just quietly dropped a new AI model called Pixel Canary on its AI Gateway, available free while it's in stealth. It is specifically tuned for frontend and mobile app development, which makes it worth a closer look if you are a designer who is learning to build. What makes this different from just another model drop. Most new model announcements are aimed at engineers. Pixel Canary is interesting to designers because its stated strengths are literally the things designers care about most: responsive layouts, app screens, navigation patterns, and interactive components. Vercel is not just pointing a general-purpose model at frontend code and calling it a day. This one was evaluated specifically on Next.js tasks (Next.js is the web framework Vercel is built around), and the results are genuinely competitive. On Vercel's own Next.js benchmarks, Pixel Canary passes 28 of 31 tasks at a 90.3% baseline success rate, which ties it with GPT-6 Astra at high settings. Feed it the Next.js documentation file (called AGENTS.md) alongside your prompt, and it jumps to 30 of 31 tasks passed, 96.8%, matching the leaderboard's top score in that setting. Those are the kinds of numbers that suggest the model has real, practical knowledge of how modern web interfaces get built, not just a surface-level understanding. The tasks it was tested on are worth naming because they translate directly to things designers run into: App Router migrations, data fetching, image and font optimization, caching, and view transitions. These are the unsexy implementation details that trip up non-engineers when they try to ship something real. How a designer can actually use this right now. The fastest way to try Pixel Canary is through Vercel's model playground at vercel.com/ai-gateway/models/pixel-canary. No setup required. You can paste in a prompt describing a screen or component and see what comes back. If you want to wire it into a project you are building, the model is accessible through AI Gateway using the identifier stealth/pixel-canary. The Vercel CLI (a command-line tool you install once) has a setup command that handles the connection for you: npm i -g vercel@latest vercel ai-gateway setup Run that, and it detects any coding agents you have installed, sets up an API key (a private password that lets your app talk to the model), and configures everything. Then you just select stealth/pixel-canary in your agent's model settings. No manual configuration of credentials or routing rules. If you are using a vibe-coding tool like Cursor or a similar AI coding agent, the setup command is designed to detect those and configure them automatically. That is a genuinely low-friction path for a designer who does not want to spend an afternoon reading documentation. Once it is running, AI Gateway gives you built-in usage tracking and cost monitoring, plus the ability to set spending limits on API keys. For a designer building a side project or a small product, that kind of guardrail is useful. You can see exactly what you are spending and cap it before it surprises you. What to keep in mind before you lean in. A few honest caveats worth knowing. Pixel Canary is in stealth, meaning it is an early, unfinished release. The free pricing is explicitly described as limited time, so treat it as a window to experiment rather than a permanent budget line. There is also a data privacy point that matters: Vercel notes that Zero Data Retention (ZDR, a setting that prevents your prompts from being stored or used) is not available for this model. Prompts and responses sent through Pixel Canary may be used for training and model improvement. If you are working on anything commercially sensitive or involving real user data, that is worth factoring in before you route it through this model. The benchmark scores are also measured using a method called pass@4, meaning a task counts as passed if the model succeeds on any of up to four attempts. That is a reasonable evaluation approach, but it means real-world first-try reliability may be a bit lower than the headline numbers suggest. The grounded takeaway. Pixel Canary is a genuinely interesting tool for designers building interfaces, not because of the hype around a new model launch, but because Vercel has published specific evidence of what it can and cannot do, and the results hold up on exactly the kinds of tasks you will actually face. The free stealth window is a low-risk moment to try it on a real project screen or component. Just go in knowing it is early, your prompts are not private, and the pricing will change. Use that to your advantage now, and stay curious about what it looks like when it officially ships. ai tools vercel vibe-coding frontend model releases