正在加载视频...

视频加载失败

加载此视频时出现问题。这可能是由于临时网络问题，或视频可能不可用。

Observability on Cloudflare just got better! Create visualizations from natural language – "show me my cache hit rate". Within a chart you can also click a spike and investigate what happened much easier. Also really enjoying our animated quick start dialogs for products :) 5 new things in total:... show more

Brayden

8,275 subscribers

15,202 次观看 • 6 天前 •via X (Twitter)

Anya Rossi• Live Now

Private livecam show

14 条评论

sunil pai 的头像

sunil pai2 天前

um this needs a lot more attention

Daniel Lockyer 的头像

Daniel Lockyer6 天前

hello

Brayden 的头像

Brayden6 天前

hi

Nipsuli 的头像

Nipsuli6 天前

Nice! Was missing this the other day

Doug Standley 的头像

Doug Standley5 天前

.@Cloudflare I see you and you are killin’ it! Bravo!

Tornike Sirbiladze 的头像

Tornike Sirbiladze3 天前

Can you inspect and edit the SQL behind a generated chart? That would make the natural-language starting point much more useful for repeat investigations.

Alek 的头像

Alek6 天前

Brayden - which spike made cache-hit debugging fastest?

❀ Sofie p. 的头像

❀ Sofie p.4 天前

Couldn't agree more

René Cannaò 的头像

René Cannaò6 天前

Does the investigation link preserve the exact time window and filters? Being able to send a colleague the same view of a spike is very useful during an incident. A dashboard that opens on "last 15 minutes" can tell a different story by the time they click it.

Daniel Priscu 的头像

Daniel Priscu6 天前

clicking straight into a spike will save more time than the text-to-chart part

Raxit Majithiya 的头像

Raxit Majithiya2 天前

👀 Custom alerts on observability data

Coffee Cat 的头像

Coffee Cat2 天前

自然语言画图省的是上手成本，可观测性真正的瓶颈是数据量和采样成本：全量 trace 存下来，账单涨得比流量快。建议错误全留、成功按比例采，再用 trace id 反查——前提是 id 一路透传不断链。

Arjun Maniyani 的头像

Arjun Maniyani2 天前

There's no way generative UI has become this good. I'm seriously impressed

seridarivus 🇷🇴 的头像

seridarivus 🇷🇴6 天前

NL → chart is fine until "cache hit rate" silently means edge vs origin and nobody notices the wrong series. Does the prompt log which metric ID it actually picked?

相关视频

Your team deserves more from your agent observability platform - a single, connected place for instrumentation, investigation, and measurement, enhanced with intelligence. In Braintrust, you can start with an open-ended prompt about agent behavior and carry the investigation into code, evals, automation, and monitoring. New tools like Patterns and Debugger make it easier to find recurring behavior, get to root causes, and act on what you learn. The context you build in one step automatically follows to the next. Work in the platform with an enhanced Loop experience, or move to your coding agent of choice. Read more →

Your team deserves more from your agent observability platform - a single, connected place for instrumentation, investigation, and measurement, enhanced with intelligence. In Braintrust, you can start with an open-ended prompt about agent behavior and carry the investigation into code, evals, automation, and monitoring. New tools like Patterns and Debugger make it easier to find recurring behavior, get to root causes, and act on what you learn. The context you build in one step automatically follows to the next. Work in the platform with an enhanced Loop experience, or move to your coding agent of choice. Read more →

Braintrust

42,888 次观看 • 1 个月前

Introducing: Sazabi (Sazabi). The AI-native observability platform for fast moving engineering teams. Backed by engineering leaders from the world's top AI and dev tool companies: Graphite, Vercel, Browserbase, LangChain, Browserbase, and more. Sazabi is taking a radically different approach to observability, centered on three core principles: 1. LESS IS MORE Product engineers don't need more observability bells and whistles. They need clear, actionable answers. The best UX for observability is chat. 2. LOGS ARE ALL YOU NEED The "Three Pillars of Observability" is an outdated idea. Logs can do everything traces can do, and more. 3. MONITORING IS DEAD Creating static monitors for fast-evolving systems is a fool's errand. The future is something different entirely: agentic anomaly detection. I started Sazabi out of desperation. After years of working on observability systems at Crunchbase, Brex, and 11x, I was all too familiar with the toil and complexity. Dashboards. Monitors. Session recordings. Error tracking. APM. RUM. Instrumentation. OpenTelemetry. Endless screens and configuration. It was too much. And despite everything, my teams still struggled to find and fix production issues. I was fed up. I dreamed about a better way. AI makes it possible. Today, I'm proud to introduce Sazabi to the world and announce our closed alpha program. We're selecting 10 startups to participate. Learn more:

Introducing: Sazabi (Sazabi). The AI-native observability platform for fast moving engineering teams. Backed by engineering leaders from the world's top AI and dev tool companies: Graphite, Vercel, Browserbase, LangChain, Browserbase, and more. Sazabi is taking a radically different approach to observability, centered on three core principles: 1. LESS IS MORE Product engineers don't need more observability bells and whistles. They need clear, actionable answers. The best UX for observability is chat. 2. LOGS ARE ALL YOU NEED The "Three Pillars of Observability" is an outdated idea. Logs can do everything traces can do, and more. 3. MONITORING IS DEAD Creating static monitors for fast-evolving systems is a fool's errand. The future is something different entirely: agentic anomaly detection. I started Sazabi out of desperation. After years of working on observability systems at Crunchbase, Brex, and 11x, I was all too familiar with the toil and complexity. Dashboards. Monitors. Session recordings. Error tracking. APM. RUM. Instrumentation. OpenTelemetry. Endless screens and configuration. It was too much. And despite everything, my teams still struggled to find and fix production issues. I was fed up. I dreamed about a better way. AI makes it possible. Today, I'm proud to introduce Sazabi to the world and announce our closed alpha program. We're selecting 10 startups to participate. Learn more:

Sherwood

117,900 次观看 • 8 个月前

Wait Google might have killed 100s of startups You can now turn any Google Sheets into an app and the sheet is basically its database 🔥 And it's not just to visualize data but also inputing new things. Really powerful. Steps to use it: 1. Click on the Gemini icon on the top right 2. In the settings hit "Create canvas" 3. Describe the app you want And you're already done.

Wait Google might have killed 100s of startups You can now turn any Google Sheets into an app and the sheet is basically its database 🔥 And it's not just to visualize data but also inputing new things. Really powerful. Steps to use it: 1. Click on the Gemini icon on the top right 2. In the settings hit "Create canvas" 3. Describe the app you want And you're already done.

Paul Couvert

64,115 次观看 • 28 天前

0.32 has shipped, and it's a massive release from Rerun. There's a ton of cool new features, and I wanted to highlight 2 in particular 1. OSS Server streaming from disk 2. Dataset review I walk you through them in the video, so take a look. I'll have a much longer blog post next week about the entire pipeline. With 0.32, much of the foundation is set for a unified data layer for physical data, and I'll be getting into the details of it with all that I've built over the past year. This will cover 1. Raw Data Collection 2. Data Ingestion 3. Catalog Registration 4. Query and Review 5. Post Process 6. Training so lots to share

0.32 has shipped, and it's a massive release from Rerun. There's a ton of cool new features, and I wanted to highlight 2 in particular 1. OSS Server streaming from disk 2. Dataset review I walk you through them in the video, so take a look. I'll have a much longer blog post next week about the entire pipeline. With 0.32, much of the foundation is set for a unified data layer for physical data, and I'll be getting into the details of it with all that I've built over the past year. This will cover 1. Raw Data Collection 2. Data Ingestion 3. Catalog Registration 4. Query and Review 5. Post Process 6. Training so lots to share

Pablo Vela

11,264 次观看 • 4 个月前

Today we're launching Observability Exports in Jitsu. Everything you see in Live Events can now stream into Datadog, Inc., Grafana Cloud, New Relic, Elastic, or your own OpenTelemetry Collector. Here's how it works: 1. Go to your Jitsu account's Settings → Observability exports. Set your OTLP endpoint: 2. Add your auth header. Datadog wants dd-api-key. 3. Send test log, toggle Enabled, then go find it: service:jitsu-live-events Four record types land: function, bulker_batch, bulker_stream, dead-letter. Your raw event traffic is never exported. These are operational logs about your pipelines. Datadog takes OTLP directly, so there's no agent or collector sitting in between. Jitsu is one of the fastest growing open-source CDPs with 5,000+ GitHub stars. Capturing events is unlimited and free, and delivery is free up to 200k events a month. Observability Exports is on Jitsu Enterprise plan. DM me to enable it for your org. More in comments!

Today we're launching Observability Exports in Jitsu. Everything you see in Live Events can now stream into Datadog, Inc., Grafana Cloud, New Relic, Elastic, or your own OpenTelemetry Collector. Here's how it works: 1. Go to your Jitsu account's Settings → Observability exports. Set your OTLP endpoint: 2. Add your auth header. Datadog wants dd-api-key. 3. Send test log, toggle Enabled, then go find it: service:jitsu-live-events Four record types land: function, bulker_batch, bulker_stream, dead-letter. Your raw event traffic is never exported. These are operational logs about your pipelines. Datadog takes OTLP directly, so there's no agent or collector sitting in between. Jitsu is one of the fastest growing open-source CDPs with 5,000+ GitHub stars. Capturing events is unlimited and free, and delivery is free up to 200k events a month. Observability Exports is on Jitsu Enterprise plan. DM me to enable it for your org. More in comments!

Soham Mehta

209,141 次观看 • 22 天前

I'm pretty bad at a lot of things but one thing I've (accidentally or not) have been pretty good at is being early at trends A lot of these trends are in my head in some way and I wanted to visualize those on a chart. So I built another dynamic blog post (on my new vibecoded blog platform that lets me do these kinds of pages) with this chart above. The first disclaimer of course is this is completely subjective and essentially a chart based brain dump. And the second disclaimer is I don't think I'm right, it's just my own beliefs visualized! I'll keep updating the chart You can select different trends on the legend or by clicking on a line, and you can also go fullscreen! Also you can select [x] indexed view which is pretty cool too :D Let me know what I should add or change!

I'm pretty bad at a lot of things but one thing I've (accidentally or not) have been pretty good at is being early at trends A lot of these trends are in my head in some way and I wanted to visualize those on a chart. So I built another dynamic blog post (on my new vibecoded blog platform that lets me do these kinds of pages) with this chart above. The first disclaimer of course is this is completely subjective and essentially a chart based brain dump. And the second disclaimer is I don't think I'm right, it's just my own beliefs visualized! I'll keep updating the chart You can select different trends on the legend or by clicking on a line, and you can also go fullscreen! Also you can select [x] indexed view which is pretty cool too :D Let me know what I should add or change!

@levelsio

486,844 次观看 • 3 个月前

This week's ChatGPT feature drop - Sept 11: 1/ We upgraded ChatGPT Images: it's much faster, more precise at edits, and better at understanding complex instructions. It's remarkable how much people love generating images, and it's only accelerating! 2/ Two fun features on the iOS app: when you send a message, the animation is faster and smoother. You can also pull down from anywhere in the conversation to start a new chat. 3/ When ChatGPT creates a file for you – a note, a document, a presentation or a spreadsheet – it's now much easier to share it. You can give other email addresses view or edit rights, and they'll see those files in their ChatGPT Library. 4/ We've improved 'location' use in answers (with user permission). A few weeks ago we improved the use of time in answers. Now, "what events are happening in my neighborhood" should be a lot better. 5/ Voice got smarter - When you select the 'higher intelligence' options in Voice, you can now use GPT-6 Astra, our latest frontier model. Warning, it's slow, but it's the best intelligence, hands-free. We're making answers better, and making the app much easier to use! 🚀

This week's ChatGPT feature drop - Sept 11: 1/ We upgraded ChatGPT Images: it's much faster, more precise at edits, and better at understanding complex instructions. It's remarkable how much people love generating images, and it's only accelerating! 2/ Two fun features on the iOS app: when you send a message, the animation is faster and smoother. You can also pull down from anywhere in the conversation to start a new chat. 3/ When ChatGPT creates a file for you – a note, a document, a presentation or a spreadsheet – it's now much easier to share it. You can give other email addresses view or edit rights, and they'll see those files in their ChatGPT Library. 4/ We've improved 'location' use in answers (with user permission). A few weeks ago we improved the use of time in answers. Now, "what events are happening in my neighborhood" should be a lot better. 5/ Voice got smarter - When you select the 'higher intelligence' options in Voice, you can now use GPT-6 Astra, our latest frontier model. Warning, it's slow, but it's the best intelligence, hands-free. We're making answers better, and making the app much easier to use! 🚀

Adam Fry

93,774 次观看 • 26 天前

You can now create a REAL-TIME chatbot with any voice and customize its personality. Steps: 1. Go to ElevenLabs 2. Click on voices 3. you can type in a name for the voice 4. then you can drag in an audio file to use for your voice 5. then go to the agents tab in side panel 6. and create a new agent 7. the voice 8. Create system instructions 9. Optional (Upload knowledge docs) 10. Test This can be easily implemented into your applications. I'll make a tutorial on that soon.

You can now create a REAL-TIME chatbot with any voice and customize its personality. Steps: 1. Go to ElevenLabs 2. Click on voices 3. you can type in a name for the voice 4. then you can drag in an audio file to use for your voice 5. then go to the agents tab in side panel 6. and create a new agent 7. the voice 8. Create system instructions 9. Optional (Upload knowledge docs) 10. Test This can be easily implemented into your applications. I'll make a tutorial on that soon.

Riley Brown

40,108 次观看 • 1 年前

"I've spent $30K on a launch video, now you can make one with code." Here's my new episode with Bin Liu and Jake Moran, where they shared their 5-step playbook for using HyperFrames to make professional launch videos in Codex and Claude Code: 1. Gather video assets and create a frame.md 2. Create a storyboard.md with the scenes 3. Pull animations from the HyperFrames repo 4. Generate and review static frames 5. Build the video with HyperFrames Studio You can also start simple by using the built-in /website-to-video skill to one shot a launch video from any URL. HyperFrames is 100% free and I love how it democratizes video creation for everyone. 📌 Watch now: Thanks to our sponsors: Wispr Flow: 4x faster than typing with your voice Riverside: All-in-one AI studio for podcasts and video

"I've spent $30K on a launch video, now you can make one with code." Here's my new episode with Bin Liu and Jake Moran, where they shared their 5-step playbook for using HyperFrames to make professional launch videos in Codex and Claude Code: 1. Gather video assets and create a frame.md 2. Create a storyboard.md with the scenes 3. Pull animations from the HyperFrames repo 4. Generate and review static frames 5. Build the video with HyperFrames Studio You can also start simple by using the built-in /website-to-video skill to one shot a launch video from any URL. HyperFrames is 100% free and I love how it democratizes video creation for everyone. 📌 Watch now: Thanks to our sponsors: Wispr Flow: 4x faster than typing with your voice Riverside: All-in-one AI studio for podcasts and video

Peter Yang

70,122 次观看 • 3 个月前

gpt2-chatbot is back. Capabilities seem to exceed GPT-4, Gemini 1.5, Claude, and anything else currently available. The only way to access it is by testing a prompt in battle mode on the Chatbot Arena and getting a lucky draw. A quick tutorial: 1. Go to chat. lmsys. org 2. Make sure you are in Arena (battle) mode 3. Enter a prompt (shorter is better so you can do them quicker) 4. Rate the response, and the Chatbot Arena will show you what model you were using at the bottom of the chatbox 5. If you don't get 'im-a-good-gpt2-chatbot' or 'im-also-a-good-gpt2-chatbot', refresh and try again until you do Here's a quick video of me getting really lucky and getting them BOTH side-by-side. It took me 5 attempts :^)

gpt2-chatbot is back. Capabilities seem to exceed GPT-4, Gemini 1.5, Claude, and anything else currently available. The only way to access it is by testing a prompt in battle mode on the Chatbot Arena and getting a lucky draw. A quick tutorial: 1. Go to chat. lmsys. org 2. Make sure you are in Arena (battle) mode 3. Enter a prompt (shorter is better so you can do them quicker) 4. Rate the response, and the Chatbot Arena will show you what model you were using at the bottom of the chatbox 5. If you don't get 'im-a-good-gpt2-chatbot' or 'im-also-a-good-gpt2-chatbot', refresh and try again until you do Here's a quick video of me getting really lucky and getting them BOTH side-by-side. It took me 5 attempts :^)

Rowan Cheung

316,405 次观看 • 2 年前

Today, we're making Error Tracking by Better Stack generally available. Sentry-compatible. AI-native. At 1/6th the price. Here's why we built it, and how to get the most out of it. What's wrong with error tracking today? Most teams use Sentry. It's solid! But at scale, the bills get brutal. Just 100M exceptions with 90 day lookback? ~$30,000 on Sentry. We charge ~$5,000 for the exact same thing. The math isn't subtle. And so most teams still end up sampling. Which means missing the exact exception that caused the outage. The bigger problem: errors are orphaned data. Your exception lands in Sentry. Your logs are in Datadog. Your traces are somewhere else. Root cause analysis becomes a multi-tab archaeology project at 3 am. We built error tracking natively inside Better Stack: the same platform where your logs, traces, metrics, uptime checks, and on-call schedules already live. Errors are just another signal. They belong together. The part that changes how your team works: Our AI SRE doesn't just surface errors. It fixes them. See a new exception? One click. The AI SRE analyzes the full context, from stack traces, environment variables, browser sessions, related logs and recent deploys, and opens a pull request. Not a ticket. Not a summary. A pull request with the fix. This is what happens when error tracking is fully integrated with the rest of your observability stack instead of bolted on separately. The AI has everything it needs to actually act. The migration is trivial: 1. Keep your existing Sentry SDK. Don't touch a single line of instrumentation code. 2. Point the DSN at Better Stack. 3. Done. Errors flow in. Your dashboards work. Your alerts work. 4. New exception appears. Click "Fix with AI SRE." Pull request lands in your repo. 5. Review, merge, close. That's the whole workflow. The AI angle is real, not a marketing badge. LLMs are genuinely good at fixing bugs if they have full context. The reason AI coding assistants sometimes frustrate engineers is incomplete information, not the model. We solve that by giving the AI SRE your entire telemetry stack as context. Stack traces, logs, traces, service maps, previous incidents and much more. All of it, in one place, at the moment it matters. Observability tools are only useful if you actually ingest all your data. At current prices of other tools, most teams can't afford to. Now you can, and your AI SRE can actually do something about it.

Today, we're making Error Tracking by Better Stack generally available. Sentry-compatible. AI-native. At 1/6th the price. Here's why we built it, and how to get the most out of it. What's wrong with error tracking today? Most teams use Sentry. It's solid! But at scale, the bills get brutal. Just 100M exceptions with 90 day lookback? ~$30,000 on Sentry. We charge ~$5,000 for the exact same thing. The math isn't subtle. And so most teams still end up sampling. Which means missing the exact exception that caused the outage. The bigger problem: errors are orphaned data. Your exception lands in Sentry. Your logs are in Datadog. Your traces are somewhere else. Root cause analysis becomes a multi-tab archaeology project at 3 am. We built error tracking natively inside Better Stack: the same platform where your logs, traces, metrics, uptime checks, and on-call schedules already live. Errors are just another signal. They belong together. The part that changes how your team works: Our AI SRE doesn't just surface errors. It fixes them. See a new exception? One click. The AI SRE analyzes the full context, from stack traces, environment variables, browser sessions, related logs and recent deploys, and opens a pull request. Not a ticket. Not a summary. A pull request with the fix. This is what happens when error tracking is fully integrated with the rest of your observability stack instead of bolted on separately. The AI has everything it needs to actually act. The migration is trivial: 1. Keep your existing Sentry SDK. Don't touch a single line of instrumentation code. 2. Point the DSN at Better Stack. 3. Done. Errors flow in. Your dashboards work. Your alerts work. 4. New exception appears. Click "Fix with AI SRE." Pull request lands in your repo. 5. Review, merge, close. That's the whole workflow. The AI angle is real, not a marketing badge. LLMs are genuinely good at fixing bugs if they have full context. The reason AI coding assistants sometimes frustrate engineers is incomplete information, not the model. We solve that by giving the AI SRE your entire telemetry stack as context. Stack traces, logs, traces, service maps, previous incidents and much more. All of it, in one place, at the moment it matters. Observability tools are only useful if you actually ingest all your data. At current prices of other tools, most teams can't afford to. Now you can, and your AI SRE can actually do something about it.

Juraj Masar

15,134 次观看 • 6 个月前

Factory is better than Devin, Codex, and Jules, and it's not even close. This is not just a fully autonomous software engineer but also a product manager and researcher. It's the entire package you need to build a new project or dramatically expand an existing one. I recorded a quick video so you can see how it works. You can use these autonomous Droids from Factory. Here is what they can do: 1. Build a full production-grade app from scratch 2. Develop new features for an existing codebase 3. Migrations or refactors on your codebase 4. Build integrations 5. Generate complete feature specifications 6. Solve and close issues from your issue management system 7. Do deep research on any software topics And Factory can connect to Linear, GitHub, Google Drive, Slack, Jira, Sentry, GitLab, and Notion to do its work. You can use any of the big models to do what you need.

Factory is better than Devin, Codex, and Jules, and it's not even close. This is not just a fully autonomous software engineer but also a product manager and researcher. It's the entire package you need to build a new project or dramatically expand an existing one. I recorded a quick video so you can see how it works. You can use these autonomous Droids from Factory. Here is what they can do: 1. Build a full production-grade app from scratch 2. Develop new features for an existing codebase 3. Migrations or refactors on your codebase 4. Build integrations 5. Generate complete feature specifications 6. Solve and close issues from your issue management system 7. Do deep research on any software topics And Factory can connect to Linear, GitHub, Google Drive, Slack, Jira, Sentry, GitLab, and Notion to do its work. You can use any of the big models to do what you need.

Santiago

70,099 次观看 • 1 年前

I set up Gemini Spark to write my own weekly AI news digest for me, and I'm still stuck on how little effort I had to put in. This is the exact prompt I gave it, just once: "Every Tuesday at 12:15 PM, create a new Doc in my Drive, find the 5 biggest AI stories from that week, and format each one properly." And here's what it actually produces, every week: 1. A new Doc, created and named on its own 2. The 5 biggest AI stories from that week, found and picked automatically 3. A bold headline and a summary for each one 4. The key impact spelled out, not just the news 5. A source link on every single story This runs on a schedule so I never have to think about it again. I didn't ask anything on Tuesday, I just opened the drive and the news digest doc was already there. Just like this, you can use Spark to automate any recurring task.

I set up Gemini Spark to write my own weekly AI news digest for me, and I'm still stuck on how little effort I had to put in. This is the exact prompt I gave it, just once: "Every Tuesday at 12:15 PM, create a new Doc in my Drive, find the 5 biggest AI stories from that week, and format each one properly." And here's what it actually produces, every week: 1. A new Doc, created and named on its own 2. The 5 biggest AI stories from that week, found and picked automatically 3. A bold headline and a summary for each one 4. The key impact spelled out, not just the news 5. A source link on every single story This runs on a schedule so I never have to think about it again. I didn't ask anything on Tuesday, I just opened the drive and the news digest doc was already there. Just like this, you can use Spark to automate any recurring task.

Eyisha Zyer

41,454 次观看 • 2 个月前

Reports are getting a MAJOR update starting today (buckle up, this is a big one 🤯): 1) You can now create your own report that perfectly fits your needs by specifying the structure, style, tone, and more. 2) We've added the language picker to reports, so you can now create a report in any of our 80+ supported languages. 3) Notebook will now offer dynamic suggestions for topics or themes all based on your sources, from overviews to deep dives. For example, uploading scientific papers might suggest creating a white paper, while news articles could generate explainers. 4) You can now fully customize prompts to any of your reports 5) We're introducing a new stock report— blog posts!

Reports are getting a MAJOR update starting today (buckle up, this is a big one 🤯): 1) You can now create your own report that perfectly fits your needs by specifying the structure, style, tone, and more. 2) We've added the language picker to reports, so you can now create a report in any of our 80+ supported languages. 3) Notebook will now offer dynamic suggestions for topics or themes all based on your sources, from overviews to deep dives. For example, uploading scientific papers might suggest creating a white paper, while news articles could generate explainers. 4) You can now fully customize prompts to any of your reports 5) We're introducing a new stock report— blog posts!

Gemini Notebook

905,331 次观看 • 1 年前

1/ FLEX YOUR VIBIES 📸✨ New site update: You can now create a custom grid of all your vibies instantly! No more screenshotting, downloading, and manually designing your own grids. We got you 🫶 1. Head to the official GVC website (link in next post) 2. Click “My Collection” 3. Connect your wallet 4. Select “Create Grid Layout” 5. Customize your grid, export it, and share it on X! Choose how many vibies to display, adjust the layout order, and flex your perfect grid all in one spot 🎨🤙 Drop your grids below! 👀👇

1/ FLEX YOUR VIBIES 📸✨ New site update: You can now create a custom grid of all your vibies instantly! No more screenshotting, downloading, and manually designing your own grids. We got you 🫶 1. Head to the official GVC website (link in next post) 2. Click “My Collection” 3. Connect your wallet 4. Select “Create Grid Layout” 5. Customize your grid, export it, and share it on X! Choose how many vibies to display, adjust the layout order, and flex your perfect grid all in one spot 🎨🤙 Drop your grids below! 👀👇

Good Vibes Club 🤙

25,623 次观看 • 1 年前

The biggest update to DefiLlama's dashboard editor ever. Building and customizing dashboards is now more intuitive and faster. Some highlights from the new version our llamas cooked: 1) Quick add: cmd+k in edit mode, type "uniswap fees" or "aave vs compound revenue" and the card is added 2) Parameters: dashboard level chain / protocol switch in the top bar, all connected cards update; build one dashboard and use it for multiple protocols or chains 3) Sections and tabs: group cards into collapsible sections or split the dashboard into tabs 4) Custom data: upload CSVs and chart them ui polish kit for the whole dashboards area 5) Hover tooltips sync between charts, add annotations, and more Reminder that you can create one custom dashboard for free:

The biggest update to DefiLlama's dashboard editor ever. Building and customizing dashboards is now more intuitive and faster. Some highlights from the new version our llamas cooked: 1) Quick add: cmd+k in edit mode, type "uniswap fees" or "aave vs compound revenue" and the card is added 2) Parameters: dashboard level chain / protocol switch in the top bar, all connected cards update; build one dashboard and use it for multiple protocols or chains 3) Sections and tabs: group cards into collapsible sections or split the dashboard into tabs 4) Custom data: upload CSVs and chart them ui polish kit for the whole dashboards area 5) Hover tooltips sync between charts, add annotations, and more Reminder that you can create one custom dashboard for free:

DefiLlama.com

15,105 次观看 • 23 天前