Built This Week

This week on Built This Week, we break down one of the most interesting new AI product launches in recent memory: Claude Design.No demos. No fluff. Just what happens when AI starts replacing traditional design workflows.We cover: • What Claude Design is and how it works • Creating ad campaigns, decks, and full product redesigns with simple prompts • Why it could become a serious competitor to tools like Figma • How teams are exporting AI designs directly into production code • The rumored xAI / Cursor deal and what it means for the coding race • ChatGPT Images 2.0 and whether it lives up to the hype • Why Google might be quieter now—but still dangerous long termIf you're building with AI, working in design, or trying to understand where creative tools are heading next, this episode is for you.⏱ TIMESTAMPS[00:00] Intro [00:45] Claude Design overview [01:50] First impressions after using Claude Design [03:00] How the interface works [04:20] Building decks, ads, and redesigns with prompts [06:10] Creating ad campaigns for Hip Train [07:45] Exporting projects, sharing, and production handoff [10:15] Full internal app redesign with AI [12:45] Is Claude Design a Figma killer? [13:00] xAI / Cursor acquisition rumors [16:15] ChatGPT Images 2.0 reactions [18:30] Why AI is still in the early innings [21:40] Google’s new TPUs and staying in the race [22:40] Wrap up & what’s next for Built This WeekLinksBuiltThisWeek.comNew episodes every FridayJordan Metznerhttps://x.com/mrjmetzSam Nadlerhttps://x.com/Gravino05

This week on Built This Week, we break down how AI helped a non-technical teammate build a real internal product that now helps teams move faster across the company.No buzzwords. No fake use cases. Just real AI in production.We cover: • The AI tool that automates meeting follow-up work • How transcripts become tickets, reports, and dashboards • Why internal AI products are becoming a huge advantage • How companies can train non-technical teams to build • What happens when everyone can create software • Why the next wave of AI is about empowermentIf you're serious about using AI to improve your business, this episode is for you.⏱ TIMESTAMPS(00:00) Intro (00:32) Welcome back (00:40) Guest introduction (01:28) Inside the Radar tool (02:36) Solving workflow bottlenecks with AI (03:23) Instant task generation from meetings (04:45) Smarter project visibility with dashboards (05:56) Real productivity gains (07:00) From personal tool to company product (08:08) Future roadmap (09:24) AI-generated business reviews (10:19) Building an AI-first culture (11:30) Teaching non-technical teams (12:49) Real examples across departments (13:57) Why this changes work forever (15:06) News segment (17:44) Closing thoughts🎙 HOST INFOHosted by Jordan Metzner and Sam Nadler Co-founders of Ryz LabsWe build AI-native companies and tools used by startups, enterprises, and investors.🔗 CTA + LINKSSubscribe for weekly breakdowns of real AI builds and what actually matters New episodes every FridayFollow along: YouTube: Built This Week Spotify: Built This Week Apple: Built This Week

This week on Built This Week, we break down a real AI tool we built that’s already saving days of work in production.No demos. No fluff. Just how AI is actually being used inside a real business.We cover: • The internal tool that replaced complex spreadsheets and cut turnaround time in half • How we generate client-ready presentations instantly with AI • Why tool selection matters more than ever in the agentic era • Google AI Studio and how we use it to prototype fast • Anthropic’s unreleased model and what it means for AI safety • Meta’s latest push into AI and why competition is heating upIf you're building with AI or thinking about how to apply it inside your company, this episode is for you.⏱ TIMESTAMPS00:00 Intro 00:40 What we’re covering this week 01:30 The problem with planning large offsites 02:28 How you lose money without perfect cost visibility 03:23 The AI tool we built (Offsite estimator) 04:29 Hidden costs AI catches that humans miss 05:36 From spreadsheets to automated workflows 06:04 Instant client presentations with AI 07:19 Cutting turnaround time from 10 days to 3 08:09 Tech stack behind the tool (Codex, Supabase, React, AWS) 08:58 Real customer impact and results 10:05 What we’re building next (automation + client portal)10:40 Google AI Studio deep dive 11:14 How we actually use it for prototyping 12:55 Image, music, and video generation tools 14:48 When to use which AI tool15:33 The real framework for choosing AI tools 16:45 Anthropic’s unreleased model 17:54 Why it might be a security risk 18:32 Who should control powerful AI19:45 Meta’s new AI push 21:10 Why competition is accelerating22:30 Wrap up🎙 HOST INFOHosted by Jordan Metzner and Sam NadlerCo-founders of Ryz LabsWe build AI-native companies and tools used by startups, enterprises, and investors.

Training gets the headlines.Inference is where the money is.In Episode 37 of Built This Week, we sit down with Mitesh, CEO of Positron AI, to break down one of the biggest bottlenecks in AI today: inference infrastructure.While the world focuses on trillion-parameter models and frontier labs, the real constraint isn’t intelligence — it’s memory, bandwidth, energy, and cost.We cover:• Why inference is where 90% of AI spend happens • The memory wall problem in large models • Why GPUs weren’t designed for text generation • How Positron is building terabyte-plus memory chips • The economics of 10 trillion parameter models • Why memory bandwidth utilization matters • Why CPUs are suddenly back in demand • The difference between speed-optimized and cost-optimized AI systems • The slider bar future of AI infrastructureWe also dive into:• OpenAI’s $122B valuation • Anthropic vs OpenAI secondary market dynamics • Why Nvidia isn’t going anywhere • Why commodity memory might beat premium stacks in certain use cases • The rise of agentic workflows and what that means for computeIf you care about the future of AI, silicon, infrastructure, or trillion-dollar companies — this episode is for you.New episodes every Friday.⏱ TIMESTAMPS(0:00) Why inference is the real AI bottleneck (2:00) What Positron AI is building (4:30) The memory problem in trillion-parameter models (6:30) Why GPUs struggle with inference economics (9:00) Energy, bandwidth, and supply chain constraints (12:00) Memory capacity vs memory speed tradeoffs (16:00) The “slider bar” model of AI infrastructure (18:30) OpenAI’s $122B valuation discussion (21:00) Anthropic vs OpenAI secondary markets (23:30) CPUs making a comeback (26:00) Agentic workflows and compute demand explosion (28:00) Closing thoughts on AI infrastructure

Our recruiters are not video editors.But now they can cut highlight reels in minutes.In Episode 36 of Built This Week, we break down a tool we built internally at Ryz Labs that lets our recruiting team generate polished candidate highlight videos without touching Premiere, Final Cut, or CapCut.The problem:When presenting candidates to clients, resumes are standard. But seeing a candidate speak for 60 seconds changes everything.The issue was speed. Editing sizzle reels required our video team, added delays, and was not scalable.So we built a highlight reel generator powered by:• EntreVista AI interview transcripts • Claude and Codex for clip selection • Remotion for video rendering via code • AWS S3 for instant share linksThe system automatically: • Analyzes transcripts • Identifies high signal clips • Groups them by communication, role fit, and personality • Allows light manual adjustments • Renders a branded video in 5 to 10 minutesNo editing experience required.Then we dive into Remotion and why “video as code” is one of the most underrated AI enabled workflows right now.Finally, we discuss the growing cost of AI usage inside organizations: • Token spend management • Surprise AI bills • Model access guardrails • Productivity vs cost tradeoffsAI is democratizing building.But it is also introducing a new management layer.New episodes every Friday.⏱ TIMESTAMPS(0:00) The problem: recruiters are not video editors (0:25) Welcome to Episode 36 (1:20) Why highlight reels improve candidate selection (2:30) The scalability issue with manual video editing (3:30) Demo: AI Highlight Reel Builder (4:15) How transcripts power automatic clip selection (5:00) Communication, role fit, personality grouping (6:10) Manual adjustments for recruiters (7:00) Rendering time and infrastructure challenges (8:00) Final sizzle reel output demo (9:00) How it was built with Codex (10:00) What is Remotion (11:30) Video editing as code explained (12:30) Other Remotion use cases: product trailers, documentation videos (13:45) Democratizing creative production (14:30) AI token costs inside organizations (15:15) Surprise AI bills and infrastructure lessons (16:30) Managing model access across teams (17:30) Productivity vs spend tradeoffs (18:15) Closing thoughts🔗 LINKSBuilt This Week New episodes every Friday https://builtthisweek.comJordan Metzner https://x.com/mrjmetzSam Nadler https://x.com/Gravino05