v0

Form factors for your new AI coworkers — Craig Wattrus, Flatfile

Aug 22, 2025 · 15:35

Craig Wattrus, AI design engineer at Flatfile, argues that designing AI interactions requires treating AI as a new coworker with distinct form factors — invisible, ambient, inline, and conversational — rather than traditional UI. He demonstrates how feeling the material by building tools like a 'chat tuner' to tune AI character shifts from helicopter-parenting to character coaching. Finding the grain involves designing tool UX where AI communicates visually, checks alignment, and hands back control. Courting emergence yields unexpected results: an agent combined two files without being asked and suggested the user contact HR for missing employee IDs. Looking forward, Wattrus explores auto-complete for data transformations, using LLMs to suggest fixes alongside human oversight.

Evals Are Not Unit Tests — Ido Pesok, Vercel v0

Aug 6, 2025 · 15:22

Ido Pesok, an engineer at Vercel working on v0, argues that evals—not unit tests—are the key to making LLM applications reliable, using the basketball court analogy of understanding your domain (the court), collecting user queries (data points), and scoring passes/fails. He illustrates with the Fruit Letter Counter app, which failed in production despite passing manual tests, because LLMs are inherently non-deterministic. Pesok advises collecting data from thumbs-up/down, logs, and forums, and structuring evals with constants in data and variables in task (e.g., system prompt). He emphasizes deterministic pass/fail scoring, adding extra prompt tags for easy parsing, and integrating evals into CI/CD to detect regressions when changing models or prompts. The episode stresses that improvement without measurement is limited, and evals enable systematic reliability gains.

The Bitter Layout or: How I Learned to Love the Model Picker — Maximillian Piras, Yutori

Jul 21, 2025 · 14:24

In this talk, Maximillian Piras argues that conversational interfaces remain dominant in AI apps not because they are natural, but because they are 'conformable' — able to absorb the next model's capabilities without redesign. He calls this pattern 'The Bitter Layout': an input field, turn-by-turn flow, and a model picker, which prioritizes flexibility over usability. Applying Clayton Christensen's theory of commoditization, Piras claims that as long as scaling laws keep models from commoditizing, the interface itself is the commodity, and designers must conform to the next model. He traces the debate over chat UX from Linus Lee (2022) to Julian Lear (2024), and criticizes the model picker as a 'mode selector' that creates usability issues. Looking ahead, Piras suggests designers shift from procedural thinking to setting goals and constraints, and speculates that future AI UX will be 'grown' like a garden rather than built.

Don’t get one-shotted: Use AI to test, review, merge, and deploy code — Tomas Reimers, Graphite

Jun 27, 2025 · 5:45

Tomas Reimers, CPO and co-founder of Graphite, argues that AI-generated code accelerates the inner loop (development) but bottlenecks the outer loop (review, test, merge, deploy), necessitating AI-native tooling across the entire workflow. He presents Graphite's AI code reviewer, Diamond, which achieves a 52% acceptance rate on its comments—exceeding the 45–50% rate for human comments—while only 4% of its comments are dismissed. Reimers emphasizes that AI tools must deeply understand the codebase, integrate with CI/testing pipelines, and provide high-signal, low-noise feedback to handle the increasing volume of AI-assisted code. He cites that 46% of GitHub code is now written by Copilot, and predicts the outer loop will break without AI-driven prioritization, review automation, and optimized deployment. The talk advocates for self-driving code review that lets developers focus on product features rather than manual processes.

Why the Best AI Agents Are Built Without Frameworks (Primitives over Frameworks) — Ahmad Awais, CHAI

Jun 3, 2025 · 27:06

Ahmad Awais, founder of LangBase/CHAI, argues that production AI agents like Perplexity, Cursor, v0, Lovable, Bolt, and CHAI itself should be built using AI primitives rather than frameworks. He demonstrates live coding a 'Chat with PDF' agent using LangBase primitives (memory, parser, chunker, threads). Awais presents eight agent architectures—augmented LLM, prompt chaining, agent router, parallel agents, orchestrator-worker, evaluator-optimizer, tool-calling, and memory-based—all built with plain code and no framework. He claims frameworks are bloated and slow, while primitives offer flexibility and automatic scaling (e.g., memory storing terabytes). Awais shows how to compose multiple LLMs (Gemini, DeepSeek Llama, Claude) in a router agent, and notes that his team has built agents for OCR, image analysis, and deep research using primitives and external tools like Mistral OCR.

The era of unbounded products: Designing for Multimodal IO: Ben Hylak

Sep 25, 2024 · 20:32

Ben Hylak, founder of Dawn and former Apple Vision Pro designer, argues that the key to building intuitive AI products in the era of unbounded interfaces is adding structure—highlighting what matters, establishing hierarchy, and leveraging familiarity—lessons from designing VisionOS. He shows how successful AI apps like Dot, Perplexity, and Claude use structure (e.g., Claude pulling code into artifacts) while the Vercel chatbot's inline dynamic UI is an anti-pattern because it disrupts conversation flow. For agents, spreadsheets (like Clay) make unfamiliar multi-step tasks familiar. Looking ahead, Hylak predicts less prompt engineering via sparse autoencoders for millions of ranked, personalized presets, shifting product evaluation from evals to user analytics as apps become increasingly personalized.

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.