Загрузка видео...

Не удалось загрузить видео

На главную

feedback is the bottleneck for building with AI Inflight fixes that now designers can get structured feedback on their prototypes which loops back into Claude/Codex as next steps how it works in ~60s 👇

ridd_design's profile picture

Ridd 🤿

74,973 subscribers

33,322 просмотров • 2 месяцев назад •via X (Twitter)

LIVE

Anya Rossi• Live Now

Private livecam show

Комментарии: 0

Нет доступных комментариев

Здесь появятся комментарии из оригинального поста

Похожие видео

how i vibecode an entire game in ONE DAY with AI here's exactly what I used (and which ones actually slapped): > claude for ideas & feedback > gemini + gpt for visuals > claude code + codex for building > suno for music > Build Anything for knowledge which AI tools do u trust for shipping products ?
1:22

how i vibecode an entire game in ONE DAY with AI here's exactly what I used (and which ones actually slapped): > claude for ideas & feedback > gemini + gpt for visuals > claude code + codex for building > suno for music > Build Anything for knowledge which AI tools do u trust for shipping products ?

icebearcute

21,574 просмотров • 2 месяцев назад

Claude Code creator, Boris Cherny: "Going from agents to loops is as big a jump as going from code to agents." 40 minutes of the head of Claude Code showing exactly how he works now. Loops running his code reviews, his maintenance, his fixes, on their own. Watch it, then read the full breakdown of loops below.
41:00

Claude Code creator, Boris Cherny: "Going from agents to loops is as big a jump as going from code to agents." 40 minutes of the head of Claude Code showing exactly how he works now. Loops running his code reviews, his maintenance, his fixes, on their own. Watch it, then read the full breakdown of loops below.

Anatoli Kopadze

376,156 просмотров • 1 месяц назад

Problem statement- I have seen many people posting resumes on x to get reviews Solution - A platform that lets user upload their resumes and get feedback from the audience in the comments section i have tried my best to keep the UI as neat as possible Would love to see how u like it Open to feedback This is v0 i will add ai feedback in next version repost and comment how u felt about it
1:53

Problem statement- I have seen many people posting resumes on x to get reviews Solution - A platform that lets user upload their resumes and get feedback from the audience in the comments section i have tried my best to keep the UI as neat as possible Would love to see how u like it Open to feedback This is v0 i will add ai feedback in next version repost and comment how u felt about it

Harish

14,966 просмотров • 1 год назад

"Our best features come from engineers prototyping an idea, shipping it to dogfood, and just listening to feedback." Here's my new episode with cat (Claude Code product lead) where she shared exactly how her AI-native team operates: ✅ Engineers own features end-to-end ✅ Designers commit production code ✅ Demos over Google docs ✅ Rapid feedback loops every 10 minutes Cat also shared her 3 best Claude Code tips and what's next for the product. 📌 Watch now:
0:52

"Our best features come from engineers prototyping an idea, shipping it to dogfood, and just listening to feedback." Here's my new episode with cat (Claude Code product lead) where she shared exactly how her AI-native team operates: ✅ Engineers own features end-to-end ✅ Designers commit production code ✅ Demos over Google docs ✅ Rapid feedback loops every 10 minutes Cat also shared her 3 best Claude Code tips and what's next for the product. 📌 Watch now:

Peter Yang

134,477 просмотров • 11 месяцев назад

We toned down the visual recoil based on your feedback. Keep in mind this is WIP, next step is to see how it plays in our next open playtest and get your feedback.
0:21

We toned down the visual recoil based on your feedback. Keep in mind this is WIP, next step is to see how it plays in our next open playtest and get your feedback.

BattleBit Remastered

78,919 просмотров • 5 месяцев назад

Today we’re officially announcing what we’ve been building for Clovr Labs Say hello to @mediandotsh. The first feedback engine for modern teams. It started as an internal tool while building Clovr and now we’re turning it into something bigger: rethinking how modern teams collect and manage feedback. Stay tuned for more updates over the next week.
0:39

Today we’re officially announcing what we’ve been building for Clovr Labs Say hello to @mediandotsh. The first feedback engine for modern teams. It started as an internal tool while building Clovr and now we’re turning it into something bigger: rethinking how modern teams collect and manage feedback. Stay tuned for more updates over the next week.

Alby Churven

11,223 просмотров • 3 месяцев назад

Vibecoding is great for prototypes. But what about building real components you can plug into production systems? We used Claude Opus 4.6 to build a custom TTS plugin (Kitten TTS) and hook it into Vision Agents. Here's how it works 🧵
0:32

Vibecoding is great for prototypes. But what about building real components you can plug into production systems? We used Claude Opus 4.6 to build a custom TTS plugin (Kitten TTS) and hook it into Vision Agents. Here's how it works 🧵

Stream

3,553,017 просмотров • 4 месяцев назад

This is how a top designer uses Claude as a design partner Every designer should copy this AI workflow to improve their designs Especially solo designers at startups or designers working on small teams because they don't have the luxury of weekly design critiques or colleagues available to give them immediate design feedback 👀 Watch the full interview on Sneak Peek: Hammed shows how the Jump design team uses Claude as a design thought partner to improve Figma designs👇
2:35

This is how a top designer uses Claude as a design partner Every designer should copy this AI workflow to improve their designs Especially solo designers at startups or designers working on small teams because they don't have the luxury of weekly design critiques or colleagues available to give them immediate design feedback 👀 Watch the full interview on Sneak Peek: Hammed shows how the Jump design team uses Claude as a design thought partner to improve Figma designs👇

Jayneil Dalal

82,240 просмотров • 10 месяцев назад

Manually dealing with user feedback is about to become a thing of the past. Extracting insights from feedback used to take hours every week. Now AI can do it for you, automatically. Introducing Cycle: the fastest way for your team to manage feedback – on autopilot. Start your free trial:
0:46

Manually dealing with user feedback is about to become a thing of the past. Extracting insights from feedback used to take hours every week. Now AI can do it for you, automatically. Introducing Cycle: the fastest way for your team to manage feedback – on autopilot. Start your free trial:

Mehdi Boudoukhane

15,790 просмотров • 2 лет назад

Introducing MagicPath 2.0. MagicPath is now a multiplayer canvas for humans and agents like Codex or Claude Code to design and build with AI. Use your codebase, grab data from anywhere, and see the agents work in real time as a team while building fully functional prototypes.
1:29

Introducing MagicPath 2.0. MagicPath is now a multiplayer canvas for humans and agents like Codex or Claude Code to design and build with AI. Use your codebase, grab data from anywhere, and see the agents work in real time as a team while building fully functional prototypes.

Pietro Schirano

339,039 просмотров • 3 месяцев назад

Boris has Claude Code loops running on cron all day - One babysits his PRs and fixes CI - Another keeps CI healthy - Another pulls Twitter feedback every 30 min and clusters it His Claude Code setup is simple and pretty close to mine That's what I like about Claude Code. Hundreds of options, but the simplest setup just works, you probably don't need more than that And since one of those loops reads Twitter every 30 min, Boris Cherny (or his Claude on cron) is reading this post whether he wants to or not 😅
1:16

Boris has Claude Code loops running on cron all day - One babysits his PRs and fixes CI - Another keeps CI healthy - Another pulls Twitter feedback every 30 min and clusters it His Claude Code setup is simple and pretty close to mine That's what I like about Claude Code. Hundreds of options, but the simplest setup just works, you probably don't need more than that And since one of those loops reads Twitter every 30 min, Boris Cherny (or his Claude on cron) is reading this post whether he wants to or not 😅

Daniel San

121,354 просмотров • 3 месяцев назад

CODEX SKILL THAT TURNS CUSTOMER FEEDBACK INTO A ROADMAP! Most feedback analysis stops at positive or negative. I made a Codex skill that turns support tickets, interviews, surveys, reviews, sales calls, and churn notes into evidence-backed product priorities and credible customer proof. Give it your feedback files and Codex maps recurring pains, ranks what to build next, and links every recommendation back to exact evidence IDs. It keeps four things separate: -what customers said -the underlying problem -what to validate or build next -what you can honestly claim -> feedback clustering with source traceability -> product opportunity scoring -> Now / Next / Later roadmap -> customer proof + case-study candidates -> objections, churn risks, and unsupported claims -> searchable Startup Customer Evidence Map -> privacy-first quote and consent handling -> one-command install What would you analyze first: support tickets, interviews, or churn notes? Install: npx --yes startup-feedback-engine@latest 100% open source. Repo in Bio.
0:36

CODEX SKILL THAT TURNS CUSTOMER FEEDBACK INTO A ROADMAP! Most feedback analysis stops at positive or negative. I made a Codex skill that turns support tickets, interviews, surveys, reviews, sales calls, and churn notes into evidence-backed product priorities and credible customer proof. Give it your feedback files and Codex maps recurring pains, ranks what to build next, and links every recommendation back to exact evidence IDs. It keeps four things separate: -what customers said -the underlying problem -what to validate or build next -what you can honestly claim -> feedback clustering with source traceability -> product opportunity scoring -> Now / Next / Later roadmap -> customer proof + case-study candidates -> objections, churn risks, and unsupported claims -> searchable Startup Customer Evidence Map -> privacy-first quote and consent handling -> one-command install What would you analyze first: support tickets, interviews, or churn notes? Install: npx --yes startup-feedback-engine@latest 100% open source. Repo in Bio.

Kappaemme

138,192 просмотров • 12 дней назад

Steering is heavy with a lot of feedback. The biggest advantage of Jimny on hills is it’s narrowness which means you can dart it into very tight spaces.
0:59

Steering is heavy with a lot of feedback. The biggest advantage of Jimny on hills is it’s narrowness which means you can dart it into very tight spaces.

Throttle and Tech

50,902 просмотров • 2 месяцев назад

v0 helps product leaders turn ideas into interactive prototypes in minutes. In this demo, you'll learn how to: • Use screenshots and references to guide v0 • Customize UI with Design Mode • Preview across devices as you iterate • Deploy and share prototypes for real-time team feedback using the Vercel Toolbar Get started today at
5:09

v0 helps product leaders turn ideas into interactive prototypes in minutes. In this demo, you'll learn how to: • Use screenshots and references to guide v0 • Customize UI with Design Mode • Preview across devices as you iterate • Deploy and share prototypes for real-time team feedback using the Vercel Toolbar Get started today at

v0

24,915 просмотров • 7 месяцев назад

Fable is my favorite model ever. Stuff that never worked suddenly works. The factory is running! Feedback from Slack -> auto-processed -> PRs written –> merged while I sleep. Showing how it runs using Claude and Cursor 👇
7:45

Fable is my favorite model ever. Stuff that never worked suddenly works. The factory is running! Feedback from Slack -> auto-processed -> PRs written –> merged while I sleep. Showing how it runs using Claude and Cursor 👇

Kieran Klaassen

22,434 просмотров • 2 месяцев назад

UI/UX Designers, did you know you can get real-time UX/UI feedback on your designs and gather valuable insights directly in Figma? Spec AI is a Figma plugin that allows you to get real-time UX/UI feedback, helping you refine your designs and create user-centred experiences directly within Figma with just one click. Repost to share with others 💜
0:33

UI/UX Designers, did you know you can get real-time UX/UI feedback on your designs and gather valuable insights directly in Figma? Spec AI is a Figma plugin that allows you to get real-time UX/UI feedback, helping you refine your designs and create user-centred experiences directly within Figma with just one click. Repost to share with others 💜

Abraham John 🦄🦓

56,500 просмотров • 1 год назад

UI/UX Designers, did you know you can get real-time UX/UI feedback on your designs and gather valuable insights directly in Figma? Spec AI is a Figma plugin that allows you to get real-time UX/UI feedback, helping you refine your designs and create user-centred experiences directly within Figma with just one click. Repost to share with others 💜
0:33

UI/UX Designers, did you know you can get real-time UX/UI feedback on your designs and gather valuable insights directly in Figma? Spec AI is a Figma plugin that allows you to get real-time UX/UI feedback, helping you refine your designs and create user-centred experiences directly within Figma with just one click. Repost to share with others 💜

Abraham John 🦄🦓

28,726 просмотров • 1 год назад

Notion's Head of Product Max Schoening : "I actually don't care at all whether designers write code that lands in production. The reason I like designers thinking in code is that it forces you to consider the medium. I would much rather take a designer or PM who has a deep affinity for understanding how agent loops work than someone who can ship PRs. And the only way that you can actually get to understanding agent loops is by building them in the material that they're made of, which is currently code. That's why I care that designers 'code.' Not because of the utility of shipping to production, but because it forces you to really interrogate the material that you're designing with."
0:56

Notion's Head of Product Max Schoening : "I actually don't care at all whether designers write code that lands in production. The reason I like designers thinking in code is that it forces you to consider the medium. I would much rather take a designer or PM who has a deep affinity for understanding how agent loops work than someone who can ship PRs. And the only way that you can actually get to understanding agent loops is by building them in the material that they're made of, which is currently code. That's why I care that designers 'code.' Not because of the utility of shipping to production, but because it forces you to really interrogate the material that you're designing with."

Lenny Rachitsky

76,527 просмотров • 3 месяцев назад

Studies have shown ChatGPT outperforms human annotators for Structured Data by about 25% and costs 30x less. 1 In just 2 months, miners on SN33 running ChatGPT without optimization can’t survive. Today we announce SN33 is now ReadyAI to fully align with our mission 👇 SN33 is building a more performant and significantly cheaper alternative to Scale AI Today structured data is performed primarily by human annotation services like Amazon’s Mechanical Turk and Scale AI It is now more important than ever for every business and individual to make their data AI Ready. However, taking unstructured data and making it Structured Data using today’s tools is extremely costly. SN33 revolutionizes this process, unlocking immense opportunities for commercialization. We lay out the vision for it in this detailed blog post: Validators TODAY can monetize access to this structured data pipeline independently, but we’re streamlining this process, launching a frontend soon that any validator can opt into to provide bandwidth. We've received great feedback from the community, recognizing that what we're building goes far beyond Conversational AI. Building the world's largest annotated conversational dataset (which we've already accomplished) is just one of countless real-world applications for SN33's Structured Data pipeline. We're building a decentralized Scale AI, offering a full suite of Structured Data commodities—from text metadata tagging (available today) to fully customizable queries for company-specific data annotation use cases and image metadata tagging coming soon 👀. Thanks for all the feedback! It has been invaluable so keep bringing it to us! 🙏$TAO Openτensor Foundaτion 1 “ChatGPT Outperforms Crowd-Workers for Text-Annotation Tasks” shows “The zero-shot accuracy of ChatGPT exceeds that of crowd-workers by about 25 percentage points on average [...] Moreover, the per-annotation cost of ChatGPT is less than $0.003—about thirty times cheaper than MTurk”
1:16

Studies have shown ChatGPT outperforms human annotators for Structured Data by about 25% and costs 30x less. 1 In just 2 months, miners on SN33 running ChatGPT without optimization can’t survive. Today we announce SN33 is now ReadyAI to fully align with our mission 👇 SN33 is building a more performant and significantly cheaper alternative to Scale AI Today structured data is performed primarily by human annotation services like Amazon’s Mechanical Turk and Scale AI It is now more important than ever for every business and individual to make their data AI Ready. However, taking unstructured data and making it Structured Data using today’s tools is extremely costly. SN33 revolutionizes this process, unlocking immense opportunities for commercialization. We lay out the vision for it in this detailed blog post: Validators TODAY can monetize access to this structured data pipeline independently, but we’re streamlining this process, launching a frontend soon that any validator can opt into to provide bandwidth. We've received great feedback from the community, recognizing that what we're building goes far beyond Conversational AI. Building the world's largest annotated conversational dataset (which we've already accomplished) is just one of countless real-world applications for SN33's Structured Data pipeline. We're building a decentralized Scale AI, offering a full suite of Structured Data commodities—from text metadata tagging (available today) to fully customizable queries for company-specific data annotation use cases and image metadata tagging coming soon 👀. Thanks for all the feedback! It has been invaluable so keep bringing it to us! 🙏$TAO Openτensor Foundaτion 1 “ChatGPT Outperforms Crowd-Workers for Text-Annotation Tasks” shows “The zero-shot accuracy of ChatGPT exceeds that of crowd-workers by about 25 percentage points on average [...] Moreover, the per-annotation cost of ChatGPT is less than $0.003—about thirty times cheaper than MTurk”

David Fields

13,639 просмотров • 2 лет назад