Vercel AI SDK

A Song of Types and Agents - Roberto Stagi, Ratel

Jul 12, 2026 · 14:16

Roberto Stagi (Ratel) argues that TypeScript is overtaking Python as the dominant language for building AI agents and applications, driven by the rise of coding agents like Lovable, Claude Code, and Cursor that default to TypeScript. He notes that Python still rules training, research, and GPU serving, but the application layer—where AI is shipped inside products—now belongs to TypeScript. Stagi highlights that TypeScript surpassed Python as the most used language on GitHub in August 2025, with GitHub attributing the shift to AI agents. He cites the Vercel AI SDK growing from 1.6M to 15.1M weekly downloads in one year and npm's rich ecosystem of authentication, payments, and UI packages as reasons to build agents in TypeScript. Consistent end-to-end typing via Zod and a unified codebase for agent loops, tools, backends, and UIs further strengthen the case. Stagi concludes by invoking Atwood's Law: any application that can be written in JavaScript will eventually be written in TypeScript, urging developers to build agents in TypeScript to avoid falling behind.

The Future Is Domain-Specific Agents - Justin Schroeder, StandardAgents

Jun 29, 2026 · 30:38

Justin Schroeder of StandardAgents argues that domain-specific agents—small, focused AI agents each limited to a single domain—will outperform general-purpose agents that rely on accumulating tools and context via inheritance, and that composition of such agents is the key to building practical, cost-effective AI systems. He defines an agent as deterministic software harnessing non-deterministic model outputs, then critiques the current approach of piling tools and skills into a single agent (inheritance), proposing instead a coordinator agent that delegates to many specialized sub-agents (composition), each with its own minimal context, system prompt, and tools. He claims these domain-specific agents achieve over 80% token efficiency, enable use of cheaper small models (e.g., DeepSeek V4 Flash is 137x cheaper than a frontier model), improve safety by limiting capabilities, and scale easily. Schroeder predicts rapid adoption through 2026-2027, with multi-agent orchestration becoming mainstream and tokens no longer getting cheaper—up 29% when adjusted for IQ. He describes an ideal agent architecture with hooks, rules, and recursive sub-agents, and invites listeners to try…

Identity for AI Agents - Patrick Riley & Carlos Galan, Auth0

Jan 14, 2026 · 1:22:12

Patrick Riley and Carlos Galan from Auth0 (Okta) present new identity and access management features for AI agents, including Async Auth, Token Vault, and MCP integration. Token Vault securely stores and refreshes upstream resource tokens, enabling agents to access APIs on behalf of users. Async Auth allows agents to request user approval for risky operations, such as placing an order, via out-of-band notifications like push to the Guardian app. They demonstrate a Next.js chatbot that uses Token Vault to read a user's stock portfolio and Async Auth to require explicit consent before executing trades. The MCP server is secured with OAuth 2.0, supporting Dynamic Client Registration (DCR) and fine-grained scopes. The solution bridges user identity, agent identity, and upstream API authorization, ensuring agents can act autonomously but with user-defined boundaries.

[Workshop] AI Pipelines and Agents in Pure TypeScript with Mastra.ai — Nick Nisi, Zack Proser

Jul 12, 2025 · 1:51:14

This hands-on workshop introduces Mastra.ai, a TypeScript framework for building production AI agents and pipelines, and demonstrates how to build an AI meme generator using composable workflows, tools, and agents. Hosts Nick Nisi and Zack Proser walk through creating a multi-step workflow: extract user frustration, find a base meme via ImageFlip, generate captions, and publish the meme at a stable URL. They show how to chain steps with Zod schema validation for deterministic output, then wrap the workflow in an agent that accepts natural language requests. The workshop also covers MCP (Model Context Protocol) and a live demo of MCP.shop for ordering a shirt, emphasizing local iteration with Mastra's playground, built-in memory, and evaluation tools. Real-world patterns include building internal AI assistants for data cleaning, email drafting, and document summarization with minimal code.

[Evals Workshop] Mastering AI Evaluation: From Playground to Production

Jul 1, 2025 · 1:25:08

In this workshop, Braintrust Solutions Engineers Carlos Esteban and Doug guide participants through the complete AI evaluation lifecycle, from offline testing in the playground to production monitoring. They explain the three core ingredients of an eval—task, data set, and score—and demonstrate how to run evals both via the Braintrust UI and the SDK. The session covers LLM-as-judge vs. deterministic code scores, the importance of starting small with synthetic data, and how to use online scoring and logging to capture real user feedback. Human-in-the-loop review is highlighted as a way to establish ground truth and close the feedback loop. The presenters also address audience questions on bootstrapping data sets, non-determinism in LLM judges, and integrating evals into existing projects.

Evals 101 — Doug Guthrie, Braintrust

Jun 27, 2025 · 48:31

Braintrust solutions engineer Doug Guthrie presents the full AI evaluation lifecycle, covering offline and online strategies for building robust AI products. He explains that evals require three ingredients—tasks (prompts or agentic workflows), datasets (real-world examples), and scores (LLM-as-a-judge or code-based)—and demonstrates how to run them in Braintrust's playground and via SDK. The talk emphasizes creating a feedback loop: production logs feed into datasets, enabling human review and user feedback to iteratively improve offline evals. Guthrie showcases a changelog app, the new AI-driven "loop" feature for prompt optimization, and answers audience questions on A/B testing models, handling multiple human scorers, pre-launch validation, and exporting data for custom dashboards.

How to build world-class AI products — Sarah Sachs (AI lead @ Notion) & Carlos Esteban (Braintrust)

Jun 27, 2025 · 1:43:46

Sarah Sachs (AI lead at Notion) and Carlos Esteban (Braintrust) explain that building great AI products requires 10% prompting and 90% evals and observability, with Notion AI using Braintrust to iterate on prompts and models. Sachs details their cycle: curate small datasets, tie them to scoring functions (LLM-as-a-judge with per-sample prompts and heuristic checks), run evals before shipping, and use production logs to catch regressions. She notes Notion AI supports 100M+ users, switches models in under a day, and 60% of enterprise users are non-English—requiring multilingual eval rigor. Carlos and Doug then walk through Braintrust's framework: tasks (prompts, tools, agents), datasets, and scores (0-1). They demonstrate offline evals via playground and SDK, online scoring in production, user feedback capture, human review setup, and remote evals to bridge complex code with the playground. The workshop covers moving from pre-prod evals to production monitoring, closing the feedback loop by adding underperforming spans to datasets.

[Full Workshop] How to add secure code interpreting in your AI app: Vasek Mlejnsky

Feb 6, 2025 · 1:48:16

Vasek Mlejnsky, CEO of E2B, demonstrates how to add secure AI code execution to any app using E2B’s Code Interpreter SDK alongside Anthropic's Sonnet 3.5 and Vercel’s AI SDK. The workshop builds an open-source version of Claude’s artifacts UI, running Python code in isolated Firecracker VMs that start in ~900ms and support custom environments via Dockerfiles. Vasek explains how E2B’s Jupyter-server-based sandbox returns stdout, stderr, runtime errors, and rich outputs like PNG charts, which are streamed to the front end using Vercel’s stream data. He covers security architecture—full root access in a VM that self-destructs on escape—and plans for AWS/GCP self-hosting and snapshot-based agent branching. The episode also addresses customizing sandboxes with private packages, mounting cloud storage (S3, GCS), and interpreting table previews as HTML or images.

The Weekend AI Engineer: Hassan El Mghari

Nov 22, 2023 · 21:49

Hassan El Mghari shares how he built viral AI apps like RoomGPT and AI Commit, arguing that simple off-the-shelf APIs and focused weekend sprints can attract millions. He describes building 11 side projects in a year, which grew from 20,000 visitors to over 8.5 million unique visitors and 2.8 million sign-ups. Key projects include RoomGPT, which used ControlNet for room redesign and reached 6 million visitors, and AI Commit, an open-source CLI tool adopted by 30,000 developers. He emphasizes using tools like the Vercel AI SDK and v0.dev to accelerate development, making apps free and open source to drive growth, spending 80% of time on UI, and launching quickly with minimal fine-tuning.