This New Way

• How Designers Become Builders with AI with Filip Skrzesinski of Subframe

  Aydin sits down with Filip Skrzesinski, co-founder of Subframe, to unpack how AI and code-native design tools are collapsing the classic PM → design → engineering handoffs. Filip explains why “pictures to code” is an unfair ask of engineers, shows how Subframe lets teams design directly in the same material as production code, and demos building a Fellow feature—from screenshot → design system match → working prototype—without access to Fellow’s codebase. They close on what’s next: organizations training their own “house models” to reflect product taste, patterns, and constraints so more people across the company can truly build.Key takeawaysDesign in the same material as code: Subframe treats UI work as editable code, eliminating fidelity loss from design handoffs.Fewer stages, faster loops: PMs, designers, and engineers collaborate in one artifact; prototypes look and behave like the real app.AI as a trained teammate, not a slot machine: Teams will shape models with system prompts, snippets, and feedback—like mentoring a junior designer.Front-end ownership shifts: Designers can own front-end structure and components; engineers wire up backends and complex logic.Prototype to PRD: High-fidelity prototypes beat docs for alignment, user testing, and speed.Timestamps00:00 - Introduction 01:00 Fil's path: audio engineering → CS → design → startup co-founder03:48 Builders everywhere: from Dreamweaver → Webflow → Shopify → now “apps”04:01 What Subframe is: a design tool rooted in code05:48 Bridging LLMs (great at code) with visual design context08:09 The architect vs. printer analogy for product design12:23 Back to the show: “The new way” is collapsing steps and handoffs14:07 “Five-year” vision (sooner than you think): design → code with agents in the loop16:31 Training models on your org’s taste: like raising a puppy—examples & theory19:15 Today’s demo plan: build a Fellow feature in Subframe without codebase access21:04 Recreating Fellow’s UI: import colors/typography; screenshot → layout23:07 Don’t fight the AI: let it rough-in, then designers perfect in visual mode24:11 Why prototypes should look native (not “off-brand” sandboxes)26:07 Syncing components to codebases; where Subframe stops (front-end) and engineers continue (backend)28:33 Programmatic (deterministic) UI code & generative for visuals30:00 PMs in the tool: prompt to add a Share dialog with transcript and video context35:08 Exploring multiple design variations; mix-and-match patterns (“snippets”)37:57 From design to interactive prototype via annotations (“do this on click…”)45:22 First build runs: working Share flow; alert updates after sending47:02 Export code → Cursor/GitHub; hand off real components48:08 The next 12 months: more ideas shipped, more makers, less gatekeepingTools & technologies MentionedSubframe — Code-native design tool for building UI/UX; designs directly edit the underlying code; syncs components to your repo.Fellow.ai — AI meeting assistant with privacy controls; accurate summaries, actions, decisions; broad SaaS integrations.Cursor — AI-assisted code editor; good for continuing from exported Subframe code to production.GitHub — Repo hosting and collaboration for shipping the generated/edited UI code.AI code agents — Used by engineers to wire front-end to backend services and data.Squarespace / Webflow / Dreamweaver — Prior waves that democratized web creation; backdrop for today’s “apps layer.”Shopify — Example of no-code/low-code e-commerce; analogy for app building’s democratization.Lovable / Bolts / V0 — AI code/prototyping tools referenced as peers for generating working app scaffolds.Slack / Asana / HubSpot / Salesforce / Linear / Jira / Confluence — Systems Fellow integrates with to push notes, actions, and records.Subscribe at⁠ thisnewway.com⁠ to get the step-by-step playbooks, tools, and workflows.

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• AI + n8n: From YouTube Insights to Sales Funnels in Minutes with JD Fiscus

  JD Fiscus (nerding.io) shares how a late-night hack connecting MCP to n8n exploded to ~1M downloads, then demos practical MCP workflows: indexing YouTube channels for Q&A, and auto-building n8n flows from natural language. We dig into the Agentic Commerce Protocol, real security pitfalls (like destructive commands), and how to turn MCPs into products with OAuth and Stripe for authentication and metered billing. He closes with how he teaches this hands-on at the Vibe Coding Retreat.Timestamps1:00 Why build it: “MCP shouldn’t be Claude-only”—bridging MCP into n8n early (Dec/Jan)2:09 Shipping under the pseudonym nerding.io; surprise seeing creators use it2:25 n8n later ships its own MCP server/client; they nod to nerding.io & Simon3:59 “N8n is useful, but so much more useful with MCP”5:12 What MCP means for software: every smart company is exposing an MCP; new login/usage patterns6:27 Agentic Commerce Protocol (ACP): Stripe + OpenAI; agents checkout across the web8:02 Marketing to agents not humans? SEO shifts as agents comparison-shop9:10 Early “agent mode” attempts vs protocol-based purchases (less hacky)10:58 Likely adopters: platforms (Shopify) & big retailers; echoes of early MCP evolution14:11 Security realities: token passing evolved to OAuth; hallucination + destructive actions risk16:04 Personal mishap: agent ran supabase reset on a dev DB—imagine prod! Guardrails matter17:03 Designing MCP servers: don’t just “wrap your API”; use resources/prompts for agentic UX19:04 Demo 1—Influencer MCP: index a YouTube channel, embed transcripts, ask questions in Claude20:54 Storage: embeddings into Postgres; per-channel tables24:46 Keeping it fresh: daily cron to ingest new videos25:18 Demo 2—Build n8n workflows from chat using N8N MCP (by Ramullet); live docs + API27:00 “Create a webhook → send leads to Sheets” built conversationally, with allow/deny prompts31:02 Zapier, Gumloop: agents that build automations via natural-language steps34:00 Next frontier: custom connectors (Claude/Cursor/OpenAI), OAuth auth flows for MCPs39:03 Turning MCPs into products: login with Twitter → Stripe subscription → metered billing41:12 Paid tool call demo: “paid echo” → Stripe usage event logged per user43:41 How to learn this fast: vibecodingretreat.com (small cohorts, hands-on builds)Tools & Technologies Mentioned (quick guide)MCP (Model Context Protocol) — Standard for connecting models to tools/data; supports tools, resources, prompts.n8n — Open-source automation platform; JD wrote an MCP node that went viral; also has native MCP server/client now.Claude / Cursor / OpenAI (custom connectors) — LLM IDEs/chats that can load MCPs; custom connectors enable OAuth + productized access.Agentic Commerce Protocol (ACP) — Early protocol (Stripe + OpenAI) for agent-initiated purchases with confirmations.Web MCP (W3C-oriented idea) — Emerging patterns for agent↔︎website interactions beyond human UI flows.OAuth — Secure, user-consented authentication for MCPs (vs passing raw tokens).Stripe (subscriptions + metered billing) — Attach billing/usage limits to MCP calls; track per-user consumption.YouTube API + Transcripts — Source data for the “Influencer MCP” indexing pipeline.Embeddings + Postgres — Store vectorized transcript chunks in Postgres for retrieval (JD self-hosts).Cron — Schedules daily ingestion of new content.Google Sheets — Target destination in demo for simple lead funnels.Zapier / Gumloop — Natural-language automation builders; early NLA/agent patterns.Git / CLI commands — Cautionary tale: agents running destructive commands (e.g., resets).Do Browser / Comet Browser — Agentic browsing tools referenced for web actions.Fellow.ai — AI meeting assistant with security-first design; generates precise summaries/action items.Subscribe at⁠ thisnewway.com⁠ to get the step-by-step playbooks, tools, and workflows.

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• Compound Engineering: Manage Teams of AI Agents with Kieran Klaassen of Cora

  Aydin and Kieran Klaassen (Cora) unpack Compound Engineering—treating every task as an investment so the next time is faster. Kieran shares his path from film composer to startup CTO and live-demos how he plans → prototypes → ships a feature using AI agents (Claude Code), then runs multi-agent reviews. They discuss why managers are primed to orchestrate agents, how to capture your own feedback patterns, and why there’s “no excuse not to have a prototype” anymore.Timestamps0:07 — “Every piece of work should be an investment.”2:15 — What Cora is: an AI Gmail layer that auto-archives ~80% and briefs you twice daily.3:32 — Launch notes & early user reactions.5:21 — The Claude Code pricing saga and “finding the limits.”8:06 — Compound Engineering defined (codify how you work so AI does it next time).15:01 — From “automation” to pattern-capturing systems; natural-language rules over brittle workflows. 22:03 — Demo kickoff: planning the “Invite friends” improvement inside Cora.26:11 — Rapid mockups from a screenshot + voice description; iterate in seconds.33:06 — Multi-agent planning: repo research, best-practices scout, framework researcher.41:01 — Human judgment on plans; simplify when encryption/perf add hidden complexity.50:00 — Feature running end-to-end; agentic PR + test flow; sub-agent code reviews.Tools & Technologies MentionedCora — AI inbox copilot for Gmail that prioritizes, summarizes, and drafts replies; batches the rest into twice-daily briefs.Claude Code (Anthropic) — Agentic coding/terminal assistant used for planning, building, and reviews.Monologue — Voice-to-text for quickly describing UI and generating mockups.Every.to — Partner/design/content hub Kieran collaborates with; also publishes his writing on Compound Engineering.GitHub + GitHub CLI — Issues, branches, PRs automated by agents from plan → code → review.VS Code (with Claude Code extension) — IDE setup for hands-on edits when needed.Anthropic Console Prompt Generator — Used to scaffold robust prompts/agents, then refined manually.Model mix for reviews (e.g., “GPT-5 Codecs,” “Claude Opus”) — Alternative model passes for plan/code critique.Fellow.ai — Aydin’s AI meeting assistant for accurate notes, actions, and privacy-aware summaries.Subscribe at⁠ thisnewway.com⁠ to get the step-by-step playbooks, tools, and workflows.

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• AI Lets Every Team Create Marketing-Ready Videos Instantly with Emily Kensley

  Content marketer and video lead Emily Kensley (Fellow) walks through a near-zero-friction workflow for creating polished product videos fast. She records clean, auto-animated screen demos with Screen Studio, fixes (or replaces) audio with Podcastle (Magic Dust + AI voices), and drafts scripts by riffing into a Fellow meeting then refining the transcript in ChatGPT. The result: 11-minute, brand-consistent tutorials produced in hours instead of days—repeatable by any team (marketing, CS, product, sales).Timestamps01:19 — Daily use of AI; from occasional to constant over last 6 months01:53 — What you’ll learn: a minimal-human, video-centric content workflow03:41 — Tool #1 intro: Screen Studio for screen recordings05:27 — Live capture of an AI meeting recap demo (click-through highlights, actions, decisions)06:23 — Raw → instant output: auto-smoothing cursor paths & smart zooms (no manual keyframes)07:23 — Host example: using Screen Studio for a Zapier + Fellow automation video07:44 — “Done is better than perfect”: quick crop fixes, branded backgrounds, cursor presets08:24 — Team presets = consistent brand across departments09:44 — Tool #2 intro & story: Podcastle rescues a day of bad mic audio10:59 — Podcastle audio editor: noise reduction, levelling, silence removal12:10 — Magic Dust AI demo: echoey room → studio-quality voice13:38 — AI Voices in Podcastle: when to clone vs. pick a preset (e.g., “Abigail”)16:12 — Long-form scripts → generated narration in minutes; edit/regenerate on typos17:54 — Brand consistency: shared voice so any team can ship VO18:29 — Putting it together: Screen Studio video + Podcastle narration19:24 — Finished example: Fellow YouTube settings walkthrough (11-minute tutorial)21:06 — Syncing visuals to VO: record screen while listening to the generated narration22:59 — Script creation workflow: Fellow call → transcript → ChatGPT → clean script23:34 — Full recap of the end-to-end pipeline25:01 — Repurposing: scripts → blogs, help center, CS clips; scale breadth of tutorials26:28 — Looking ahead: excitement about fast-evolving AI agentsTools & Technologies Mentioned (with quick notes)Screen Studio — Smart screen recorder that auto-smooths mouse movement, adds tasteful zoom/pan animations, and supports brand presets for consistent output.Podcastle — Audio suite used here to edit audio clipsMagic Dust AI: one-click studio-quality enhancement (denoise, de-reverb, leveling).AI Voices & Voice Cloning: generate narration from text; keep brand-consistent VO.Fellow — AI Meeting assistant used to host a solo “idea dump,” generate transcripts, AI recaps, chapters, and action items; doubles as the seed for scripts.ChatGPT — Refines raw Fellow transcript into a clean, concise voiceover script.YouTube — Publishing destination for finished tutorials.Zapier — Example in host’s Screen Studio demo (automation with Fellow).Google Meet / Zoom — Where the solo Fellow “recording” session can happen.Adobe (Premiere/After Effects) — Old manual workflow stand-ins (contrast to auto animations).Subscribe at⁠ thisnewway.com⁠ to get the step-by-step playbooks, tools, and workflows.

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• AI Designs Products, Ads & Growth Strategies Faster Than Ever with Eddie Yoon

  Eddie Yoon, Sr Director, Paid Media at NP Digital, shows how CMOs can spin up a full creative campaign in ~30 minutes using AI. He breaks down a rapid “three-tab” workflow—Meta Ad Library for competitive research, GPT for strategy and prompts, and an image generator (Reeve) for instant mood boards—then extends it into testing (Trial Reels, TikTok hooks), product R&D, and agentic pipelines. We also riff on why the next decade could normalize solo billionaire founders, how Netflix foreshadowed AI-driven content, and what real-time, stylized, monetizable media will look like.Timestamps1:07 Meet Eddie Yoon—NP Digital, paid social × creative × AI background.1:49 “AI is redefining growth”: blistering company speed and scale.2:16 The solo-founder era & agentic executive teams.4:39 Enterprise example: HubSpot’s leadership going all-in on AI.5:29 Founder example: Tyler at Beehive—shipping fast by listening + acting.6:30 Design & media: Netflix’s early AI play; House of Cards data story.11:29 The 30-minute campaign challenge—Eddie’s live plan.12:53 The three tabs: Meta Ad Library → GPT prompts → Reeve mockups.14:37 Copy/paste every active ad into GPT; ask for strategy synthesis.16:06 Five “board-level” ideas; forcing a single high-acceptance pitch.17:56 Image prompt for “Comfort 2.0” (eco-luxury, performance lifestyle).20:27 Prompting hack: “200+ IQ” to push for originality (avoid clichés).21:06 Locking on Comfort 2.0—“performance tech meets everyday life.”23:06 Iterating the mood board; feeding outputs back into GPT.23:30 If the client has the shoe already: do it all in AI (no photoshoot).24:39 Rapid tests: ethnicity, angle, color; Instagram Trial Reels.26:03 Beyond ads: full-funnel → product design & R&D with agents.27:24 100-page competitor deep dives from public signals.28:26 Scoring system (cutoff 85; 95+ are “winners”) to prioritize assets.30:13 Spinning GPT outputs into 10 TikTok hooks for creators/founders.31:32 Domain-tuned agents that deliver 90%-ready work.33:13 What’s next: automatic video analysis and creative fixes.34:13 Next 12 months: IP-driven brands, real-time stylized video, avatars.35:43 Meta: capturing AI audio; partner via your agent in the future.36:12 Why solo $1B is realistic (and $100M solos even more so).Tools & Technologies Mentioned (with quick notes)Meta Ad Library — Public index of active FB/IG ads; great for competitive creative research.GPT — Used to analyze competitor ads, generate board-level strategies, image prompts, TikTok hooks, and run scoring frameworks.Reeve — Static image generator (Midjourney-like) for fast mood boards and spec creative.Midjourney — Alternative image generation tool for photorealistic concepts.VO3 — Motion/video generation tool referenced for animated concepts.Instagram Trial Reels — Organic test surface to gauge hooks/creatives with cold audiences before spend.TikTok — Distribution + hook testing via short scripts for creators/founders.Semrush — Search/keyword intel to complement social competitive analysis.SocialPeta — Creative/spend intelligence (legacy use; less relied upon now).AI Avatars & Agentic Flows — Persona-based creators and multi-agent pipelines to speed research, ideation, testing, and post-mortems.Subscribe at⁠ thisnewway.com⁠ to get the step-by-step playbooks, tools, and workflows.

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