Vercel is the agentic infrastructure company, freeing people and agents to ship what's next. For more than a decade we've helped builders move from idea to production with speed, security, and exceptional developer experience.
Now we're scaling our products for both agents and people to ship and run software, built in the open and trusted by OpenAI, PayPal, Ramp, Supreme, and millions of developers worldwide.
Vercel is building a best-in-class Enterprise Account Executive team to drive growth across our most valuable enterprise customers and high-potential prospects. As a Majors AE, you'll own a portfolio of 30-40 named accounts representing our largest revenue opportunities, working with Fortune 500 companies and leading technology innovators who are transforming how they build and deploy web applications at scale.
This is not a traditional enterprise sales role. You'll operate as a trusted business advisor to C-suite executives, orchestrating complex, multi-quarter deal cycles that span Vercel's full product suite. You'll build long-term strategic relationships with lighthouse customers, quarterback 7-8 figure deals, and collaborate closely with Product on first-of-kind enterprise offerings to grow the world's most sophisticated technical organizations into large accounts.
If you’re based within a pre-determined commuting distance of one of our offices (SF, Austin, or NY) the role includes in-office anchor days on Monday, Tuesday, and Friday.
Your involvement will center around helping companies understand their migration path to Vercel before taking them through the onboarding process and proactively managing the account thereafter.
You will continue Vercel’s dedication to providing an exceptional enterprise experience in the AMER market.
Top performer with history of success
Coachable and collaborative
Positive attitude
Team first attitude and no ego
Experienced with Enterprise SaaS sales cycle closing 6-7 figure deals
5+ years Enterprise SaaS experience
Able to sell to technical buyers / developers, driving process through legal, procurement, security,
Comfortable with outbound sales.
Ability to be self-guided, the team is very supportive, however we are also growing very quickly. Having the ability to accelerate and take ownership is key.
Love to work it out when challenged, happy to help create processes, rather than needing them all pre-defined.
Passionate about your customers and how Vercel solves their problems
Motivated, curious, hungry
Driver who can adapt to constant change and RAPID growth
Have deep technical understanding of web technologies
Experience with web infrastructure / developer tools
Have an established network of technology companies
Have done some web-development
Inclusive Healthcare Package.
Learn and Grow - we provide mentorship and send you to events that help you build your network and skills.
Flexible Time Off.
We will provide you the gear you need to do your role, and a WFH budget for you to outfit your space as needed.
The range for this role is $300,000-$340,000 OTE + equity. Actual salary will be based on job-related skills, experience, and location. The total compensation package may include benefits, equity-based compensation, and eligibility for a company bonus or variable pay program depending on the role. Your recruiter can share more details during the hiring process.
Vercel runs a cloud platform for software teams to build, deploy and operate web applications and AI agents without managing their own servers. Its tools connect code repositories to automated builds and give teams separate environments for testing changes before publishing them. The platform combines application hosting, global content delivery and security controls, while its AI Gateway connects applications to models from several providers. Developers start on a free plan, and professional teams pay subscriptions, metered infrastructure charges or negotiated enterprise contracts. Vercel was founded in 2015 and is headquartered in San Francisco, California, United States.
Company Size
501-1,000
Company Stage
Series F
Total Funding
$863M
Headquarters
San Francisco, California
Founded
2015
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AI daily|october 18, 2026. 12stories5sections10sourcesAbout 4 min DeepSeek has launched version V4.1-Flash-1017, delivering substantial performance gains in agentic and coding benchmarks alongside faster execution and lower token usage. This brief is compiled automatically by AI and may contain errors. Check the linked sources. * Bottom line:DeepSeek has launched version V4.1-Flash-1017, delivering substantial performance gains in agentic and coding benchmarks alongside faster execution and lower token usage. * Benchmark Performance:Achieved significant improvements on complex agent evaluations, raising Terminal-Bench 4.0 scores from 31.2 to 42.3. * Pareto Efficiency:Delivers faster task completion with shorter outputs, reducing token consumption and task costs without raising API pricing. * Open-Weights Availability:Released under an MIT license with checkpoints available on Hugging Face and ModelScope for self-hosting. * Source: 在 X 上查看 @OpenRouter 的貼文 * Bottom line:JetBrains has open-sourced Mellum 2.1, a 12 billion parameter model optimized specifically for low-latency coding agent workflows. * Parameter Size:Features 12B parameters tailored for developer tooling and autonomous programming tasks. * Open-Source Release:Made openly available by JetBrains to support community-driven coding agent ecosystems. * Source:JetBrains AI Blog * Bottom line:Kyutai and academic partners have released REKI, a 2.4B VLA model designed to provide efficient memory and control for robotic manipulation. * Architecture:Built with a compact 2.4 billion parameter Vision-Language-Action architecture. * Pre-training Data:Pre-trained exclusively on public data and released on Hugging Face under an open license. * Source:MarkTechPost Coverage * Bottom line:Vercel has introduced session affinity in AI Gateway logs to automatically route sequential chat turns to the same provider for maximum prompt caching benefits. * Routing Logic:Directs consecutive turns to the provider that served the previous request, retaining cached prompt states. * Session Analytics:Aggregates requests into session views displaying total costs, models, provider pathways, and cache hit rates. * Source:Vercel Changelog * Bottom line:DeepSeek has opened its proprietary enterprise search and web fetching APIs to developers, enabling real-time grounding for agent harnesses. * Core Capabilities:Combines multi-language web search and URL text extraction to supply verified context to LLM workflows. * Pricing Structure:Priced per successful request starting November 1, with unsuccessful or timed-out queries incurring no charge. * Source:DeepSeek API Documentation * Bottom line:OpenCode disclosed a security breach affecting 1.4% of its Console users linked to a large-scale distillation attack, prompting urgent API key revocations. * Impact Scope:Impacted 1.4% of OpenCode Console users who had third-party provider keys (OpenAI, Anthropic, Google) stored in the platform. * Security Remediation:Affected users were notified via email and advised to immediately revoke compromised keys and update dependent systems. * Source: 在 X 上查看 @opencode 的貼文 * Bottom line:Meta updated its commercial terms to remove phrasing that legal experts previously interpreted as allowing publisher domain scraping for AI model training. * Policy Adjustment:Removed specific language suggesting commercial account data could be used to train Meta products and AI models. * Official Stance:Meta clarified that its web crawler practices remain unchanged and scraping terms apply strictly to ads and commercial products. * Source:The Verge Report * Bottom line:An internal Anthropic report showed that junior technical hiring dropped significantly as internal agent work hours reached six times human operating levels. * Hiring Changes:Junior technical employee representation fell from 21% to 14%, and junior hiring share decreased from 27% to 9%. * Agent Workload:Telemetry data indicated that interactive AI agent work hours scaled to six times human operator levels by August 2026. * Source:TechCrunch Coverage * Bottom line:Researchers demonstrated an 8B reasoning model trained to propose diverse and novel research ideas in a single generation by weighting conceptual distance. * Methodology:Trains a small reasoning model to generate sets of research ideas while penalizing similarity to previously generated concepts. * Evaluation:Outperformed larger frontier models like Claude Opus 4.8 and GPT-6 Astra on creative utility and diversity metrics. * Source:ArXiv Paper * Bottom line:Tencent researchers proposed a recursive self-improvement framework using verifier-guided fine-tuning and PPO to dramatically elevate terminal coding agents. * Performance Gains:Elevated the four-suite Terminal-Bench average from 20.68% to 50.58%, scoring 86.52% on Terminal-Bench 2.1. * Training Architecture:Alternated between fine-tuning on verified successful trajectories and running PPO with an inherited critic across five stages. * Source:ArXiv Paper * Bottom line:Anthropic's Claude successfully reverse-engineered and cracked a 25-year-old NIST elliptic curve cryptography seed originating from the NSA in under 30 minutes. * Background:Addressed the NIST standardized ECDSA curve seed from 2000 whose unspecified NSA origins long prompted backdoor speculation. * Resolution Speed:Solved the complex cryptographic mystery in less than 30 minutes using advanced chain-of-thought reasoning. * Source:The Decoder Coverage * Bottom line:The Claude Code team published an engineering breakdown detailing how they overhauled code reviews as AI agents generate roughly 90% of their codebase. * Efficiency Metrics:Despite merged pull requests doubling between June and September, code revert and incident rates dropped by over 40%. * Multi-Layered Checks:Employs a Swiss-cheese verification model featuring self-checks, independent reviewer agent pipelines, and automated CI tests. * Source:Claude Engineering Blog Thanks for reading to the end. Stay curious. See you tomorrow. Ad · Scribis Experience Scribis: ultimate AI audio & video workflow. Scribis is an all-in-one AI audio tool designed for creators, researchers, and professionals. It combines local privacy computation with cloud API integration, providing millisecond-level speech-to-text, speech synthesis, and dynamic timeline editing.
How free low-latency embedding engines can unlock real-time document AI at scale. *Today's briefing looks at Vercel's free Beam model, a new DeepSeek update, a massive Indic pre-training effort, and improved observability for AI Gateway - all of which reshape the data platforms that power embeddings and document-level intelligence.* Lead story - Vercel ships Beam on AI Gateway for free. Vercel has added Beam, a low-latency, open-weight model from Reflection AI, to its AI Gateway and made it free to use during the launch window [Vercel AI](https://vercel.com/changelog/reflection-ai-beam-now-available-on-ai-gateway). Beam is hosted in the US, offers sub-second response times, and is positioned as an "open-w" model for embedding generation and lightweight reasoning. Why it matters: Most document-AI pipelines - RAG, classification, summarisation - rely on an embedding service that can keep up with high-throughput ingestion. Traditional hosted embeddings (e.g., OpenAI's text-embedding-ada-002) charge per-token and can become a bottleneck when scaling to millions of pages. Beam's free tier eliminates per-token fees and, thanks to its low latency, allows near-real-time indexing of newly created or updated documents. For a retail catalog that adds hundreds of product descriptions hourly, or a clinic that continuously receives scanned records, the ability to embed on the fly without queuing dramatically shortens the "data-to-insight" lag. Practical implication for businesses: 1. Plug-and-play integration - AI Gateway provides a standard HTTP endpoint, so existing ingestion services can swap in Beam with a single URL change. No SDK overhaul is required. 2. Cost-first experimentation - Since Beam is free for the launch period, product teams can prototype RAG-style support bots, compliance checkers, or personalised recommendation engines without worrying about embedding-related OPEX. 3. Latency-driven architecture - Sub-second embeddings make it feasible to run "on-the-edge" workflows (e.g., a browser-based document uploader that instantly surfaces relevant policies) while still centralising the model in a secure Vercel data centre. The caveat is that Beam's free window is limited; businesses should treat it as a pilot and plan migration paths (e.g., to a self-hosted open-weight model or a paid Vercel tier) before the promotion ends. Nevertheless, the announcement signals a shift toward free, low-latency embedding services that can be the backbone of real-time document AI stacks. DeepSeek V4.1 Flash 1017 raises the bar for multimodal embeddings. Vercel also rolled out DeepSeek V4.1 Flash 1017 on AI Gateway, a minor yet impactful upgrade that improves reasoning, coding, agentic tasks, and image understanding [Vercel AI](https://vercel.com/changelog/deepseek-v4-1-flash-1017-now-available-on-ai-gateway). The model's enhanced image-to-text capabilities mean it can generate visual embeddings alongside text, opening the door to richer document AI that handles scanned forms, receipts, or medical imaging alongside OCR text. *Implication:* Retailers can embed product photos together with descriptions, improving visual search relevance. Clinics can index radiology images with accompanying notes, enabling multimodal retrieval for diagnostic support. The upgrade is available through the same Gateway interface, so teams using Beam for pure text can add DeepSeek for mixed-media pipelines without additional infrastructure. Hugging Face reveals a 2.8-trillion-token Indic pre-training pipeline. A joint blog from Hugging Face and NVIDIA details an open data generation pipeline that pre-trained large language models on 2.8 trillion Indic tokens [Hugging Face](https://huggingface.co/blog/nvidia/scaling-indic-pretraining). The effort showcases how to build a scalable, reproducible data platform that harvests raw text, cleans it, and feeds it into distributed training jobs. *Why it matters for embeddings:* The pipeline's emphasis on open, version-controlled data assets and automated tokenisation provides a template for organisations that need domain-specific multilingual embeddings (e.g., a pan-Indian retail chain handling Hindi, Tamil, and Bengali product catalogs). By re-using the same pipeline, businesses can generate high-quality embeddings that respect local linguistic nuances, improving downstream retrieval accuracy. AI Gateway logs now expose session affinity - better observability for embedding pipelines. Vercel's latest logging feature groups requests into sessions and shows how "session affinity" routes each one [Vercel AI](https://vercel.com/changelog/ai-gateway-logs-now-show-session-affinity). For teams that stitch together multiple calls - file upload | OCR | embedding | RAG - this visibility is crucial. It lets engineers spot latency spikes, identify which model (e.g., Beam vs. DeepSeek) is handling a given session, and attribute costs accurately. *Practical tip:* Enable session logging on your embedding endpoint and correlate the session IDs with downstream RAG request logs. This end-to-end trace helps you fine-tune batch sizes, cache strategies, and fallback models, ensuring that real-time document AI remains both fast and cost-predictable. Enterprise workflow platforms are catching up. A survey of 12 enterprise workflow automation platforms notes that many now include native connectors for AI services, including Vercel's AI Gateway [n8n](https://blog.n8n.io/enterprise-workflow-automation/). While the article is a broader market overview, the key takeaway is that modern orchestration tools are ready to call out to low-latency embedding APIs as part of automated data-ingestion flows. This convergence reduces the need for custom glue code and accelerates time-to-value for AI-driven processes. IOTA's take. For clinics, retailers, and SaaS teams, the emerging ecosystem of free, low-latency embedding models (Beam, DeepSeek) combined with robust data-pipeline tooling (Hugging Face's Indic pipeline) and observable routing (AI Gateway session logs) means you can now build truly real-time document-AI services without ballooning budgets. Start by routing new documents through Vercel's Gateway, prototype with Beam, and layer in multimodal embeddings from DeepSeek as your use cases mature. The payoff is faster knowledge retrieval, higher user satisfaction, and a clearer line of sight on AI spend.
Introducing Domain Connect. JMJoseph Maregn October 16, 2026 Connect a custom domain to AgentMail through Vercel or Cloudflare in a few clicks, with no DNS records to copy by hand. Built on Domain Connect and available through the API. custom-domains domain-connect Your agents deserve their own email address. Setting one up shouldn't be the hard part. Today, AgentMail, Inc. is introducing Automatic Domain Setup, powered by Domain Connect and launched in partnership with Vercel and Cloudflare. Add a custom domain to AgentMail, click Set up with Vercel or Set up with Cloudflare, approve the DNS changes with your provider, and come back to AgentMail for verification. There are no DNS records to copy by hand. The same flow is available through the API, so an agent can start the setup itself and a person only has to approve it. * What it is: AgentMail now connects custom domains through Domain Connect, an open DNS standard. Domains on Vercel and Cloudflare can be set up in a few clicks instead of by copying records. * Why AgentMail, Inc. built it: 42.1% of new customers who added a custom domain in the past month hit at least one verification failure, almost always from a small mistake made while copying records. * How it works: AgentMail generates the records and sends them to your DNS provider through a signed link. The provider shows you the changes, and nothing is applied until you approve them. * For agents: GET /v0/domains/{domain_id}/setup-link returns the signed link, so an agent can create a domain and start the setup without a developer assembling records. One of the things AgentMail, Inc. has always believed at AgentMail is that AI agents should be first-class citizens on the internet. That means having their own identities, their own inboxes, and the ability to communicate with the outside world. Increasingly, developers want those identities to live on their own domains. Until now, getting an agent set up with a custom email domain has been more complicated than it needed to be. Why is setting up a custom email domain so frustrating? Setting up a custom domain meant moving back and forth between AgentMail and your DNS provider, copying records by hand, and waiting for verification. That's five DNS records, verification checks that back off exponentially and stretch out the wait, and many points of failure. In fact, 42.1% of new customers who added a custom domain in the past month encountered at least one verification failure. Sometimes it was a missing character. Other times it was a duplicated domain suffix, or a record entered in the wrong place. These failures come from copying and pasting records manually, and every DNS provider has its own interface for entering them. A small mistake could turn what should have been a quick setup into a frustrating debugging session. AgentMail, Inc. wanted to change that. How does one-click domain setup work? AgentMail, Inc. has partnered with Vercel and Cloudflare to make connecting your custom domain to AgentMail much simpler. Instead of copying DNS records, you connect your domain directly through your DNS provider: * Add your custom domain to AgentMail. * Click Set up with Vercel or Set up with Cloudflare. * Review and approve the DNS changes with your provider. * Return to AgentMail for verification. That's the whole flow. There's no back and forth between tabs and no records to copy and paste. Can an agent set up a custom domain through the API? Yes. AgentMail, Inc. didn't want this to stop at the console, so Automatic Domain Setup is available through the API as well. Your agent can create a domain, request a configuration link, and start the setup process without a developer assembling DNS records: # 1. Create the domain curl -s -X POST "https://api.agentmail.to/v0/domains" \ -H "Authorization: Bearer $AGENTMAIL_API_KEY" \ -H "Content-Type: application/json" \ -d '{"domain": "example.com"}' # 2. Request a setup link for it, using the domain_id from step 1 curl -s "https://api.agentmail.to/v0/domains/$DOMAIN_ID/setup-link" \ -H "Authorization: Bearer $AGENTMAIL_API_KEY" { "supported": true, "provider_name": "Cloudflare", "url": "https://...", "state": "..."} Open url for the domain owner to approve, and store state first so you can check it when the provider redirects back. If the provider isn't supported, supported comes back false and the records can be added manually. The setup link reference covers every field, including the popup size and the warning returned when the domain already has another email provider's MX records. The domain owner still reviews and authorizes the changes with their DNS provider, but the rest of the workflow can be orchestrated programmatically. How does Domain Connect work under the hood? Automatic Domain Setup is powered by Domain Connect, an open standard for simplifying DNS configuration. AgentMail generates the records required for email delivery and authentication, then passes them to your DNS provider through a signed configuration link. The provider presents the proposed changes for approval before applying them. Because the link is signed, the provider knows the records came from AgentMail and weren't edited along the way. What does it not cover yet? Automatic Domain Setup works today for domains whose DNS is hosted on Vercel or Cloudflare. Domains on other providers still use the manual flow in the custom domains guide, and AgentMail, Inc. is adding more providers. It also doesn't remove the approval step. Someone with access to the DNS account has to approve the changes, which keeps a person in control of what gets written to the domain. Custom domains are available on paid plans, as listed on the pricing page. What does this mean for agents? AgentMail, Inc. is working toward a future where developers can give agents everything they need to operate independently: identities, inboxes, authentication, and the ability to communicate with people and services. That future requires making infrastructure that was designed for humans easier for agents to use. Custom domain configuration is one small but important piece of that. If you're running many agents across many domains, how to manage custom domains for thousands of agent inboxes covers which agents should share a domain and which should get their own. With Automatic Domain Setup, developers can spend less time configuring email infrastructure and more time building what their agents can do. It's available today for domains using Vercel and Cloudflare, with more providers coming soon. Try it in the AgentMail console. AgentMail is the first email provider built for AI agents. Create an inbox in one API call, send and receive email, no OAuth and no domain verification. Free tier, no credit card required. Faq. AgentMail connects custom domains through Domain Connect, so on Vercel or Cloudflare you click a setup button, approve the DNS changes with your provider, and AgentMail verifies the domain with no records copied by hand. The same flow is available through the API, so an agent can create the domain and request the setup link itself, and the domain owner only has to approve it.
AI infrastructure heats up as models get more efficient. AI efficiency is exploding while security demands intensify, giving developers both more powerful tools and greater responsibility. From Microsoft's new models to critical vulnerabilities in popular libraries, the infrastructure Revolter AB depend on is being reshaped in real time. Today's tech news paints a picture of two counteracting forces in the developer world. On one hand, the AI industry is accelerating, with more efficient models and more accessible tools appearing constantly. On the other hand, security threats grow exponentially as more people and systems depend on these same tools. AI is getting faster and more efficient. Microsoft unveiled MAI-Base-2, a mixture-of-experts model that is 4 to 12 times more efficient than DeepSeek-V4-Pro in training. That sounds technical, but the meaning is concrete: for developers, this means you can train larger models for less money and in less time. Greater efficiency in AI infrastructure trickles down to everyone building AI features. Nvidia is pushing the same trend with Nemotron-Bolt, a 74-billion-parameter model that now fits on a standard 24GB laptop. This completely changes what's possible to build locally without relying on API calls. On-device inference stops being a futuristic vision and becomes a practical reality for developers who want low latency and better privacy. Meta also released an open-weight AI model optimized for Apple Silicon, meaning modern AI models can now run efficiently on consumer hardware. The shared trend here is unmistakable: AI is becoming less dependent on cloud infrastructure and more distributed to the edges. Platforms are democratizing development. Bluesky expanded Attie, its AI-powered tool for building websites and games without knowing code. It's a sign that artificial intelligence is starting to make it possible for non-developers to ship things that previously required specialized knowledge. For those of Revolter AB building at a professional level, this means competition from no-code solutions is only growing. Vercel introduced always-on workers, letting you run persistent backend compute without traditional serverless scaling. It's subtle but important, because it removes one of the biggest friction points in serverless architectures: everything constantly spinning up and down. This lets developers focus on real problems instead of infrastructure orchestration. RapidCanvas raised 29 million dollars for its platform that lets non-ML-experts build custom AI tools. This is a symptom that AI tooling is rapidly normalizing and abstracting away from pure machine learning toward becoming a business problem that gets solved quickly. Security holes are growing at the same pace as success. But this isn't just a success story. GitHub was targeted in a coordinated attack where hackers compromised around 1900 accounts and targeted 30000 repositories. It's a reminder that developer infrastructure is something attackers prioritize heavily, because a compromised GitHub account is a gateway into thousands of projects. Even worse was the LiteLLM CVE-2026-35029, a critical vulnerability that exposed API keys at scale. LiteLLM sits between your applications and multiple LLM providers, so a vulnerability here can potentially compromise your entire integration chain. This is classic supply-chain risk that developers need to take seriously. OpenAI also announced deprecation of the GPT-4o API with only three months notice instead of the promised six months. This says something about the dynamics in the AI market: vendors move fast and can change terms on short notice. For developers, it means you should build abstractions around your AI API calls so you don't get locked into a single vendor. Responsibility and transparency on the rise. Anthropic gave METR researchers employee-level access to evaluate Claude, signaling a willingness toward transparent security assessment. This is the opposite pole from the security holes Revolter AB saw earlier. This type of open scrutiny could become industry standard as AI systems become more critical. What ties today together is a simple truth: the more powerful AI infrastructure becomes, the more important security, transparency, and long-term architecture become. Speed shouldn't mean building houses on sand. This is part of Revolter's daily developer brief series.
Vercel adds free Nemotron 3.5 Lightning, with a prompt-retention warning. Vercel's free Nemotron 3.5 Lightning route is served by NVIDIA, which may retain prompts for model improvement. Check what you send. BuilderWithin Editorial Team BuilderWithin Vercel has added a free route to NVIDIA's Nemotron 3.5 Lightning through AI Gateway, its service for connecting apps and coding agents to models. NVIDIA serves the requests, and Vercel warns that the provider may retain prompts for model improvement. The model can work with tools and return structured data that an app can process. Vercel lists support for coding agents including Claude Code, Codex, and Cursor. The route's model name is nvidia/nemotron-3.5-lightning-free. An agent's prompt can include the code or other context it needs for the task. As with open-model access through Netlify, using a gateway still requires checking how the serving provider handles your data. Review what your agent sends and the provider's data terms before using this route with private code or customer information. A public example or invented data lets you try it without sending that private material. End of article BuilderWithin Weekly · Free If you found this useful, subscribe free. Get BuilderWithin Weekly in your inbox. Daily briefings publish on the site, and the weekly roundup pulls together what mattered. Unsubscribe any time. BuilderWithin Weekly · Free · No spam Get BuilderWithin Weekly in your inbox. One weekly roundup in your inbox. Daily briefings publish on the site for people who ship products. Unsubscribe any time · Weekly email, always free