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How to enable full observability and automatic analytics for your LLM-based application. It takes one library + one line of code, and you get a ton of information for free. This is a no-brainer.

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Santiago

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17,506 görüntüleme • 2 ay önce •via X (Twitter)

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This is literally the simplest way you can improve your LLM-based application. It takes 2 lines of code to integrate Lilypad, and you'll get full observability into everything your app is doing: • Automatic traces • Costs • Tokens consumed • Metadata On top of that, you can annotate your traces to evaluate different versions of your prompts. Here is Lilypad's GitHub Repository: This is a no-brainer. Check out the video and you'll see how cool this is.
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This is literally the simplest way you can improve your LLM-based application. It takes 2 lines of code to integrate Lilypad, and you'll get full observability into everything your app is doing: • Automatic traces • Costs • Tokens consumed • Metadata On top of that, you can annotate your traces to evaluate different versions of your prompts. Here is Lilypad's GitHub Repository: This is a no-brainer. Check out the video and you'll see how cool this is.

Santiago

42,170 görüntüleme • 1 yıl önce

When you prompt an LLM for code, you get one deterministic program. However, the LLM actually defines a distribution over many programs, and existing methods discard it‼️ PPoT uses this distribution to extract free performance and efficiency gains. 🧵👇
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When you prompt an LLM for code, you get one deterministic program. However, the LLM actually defines a distribution over many programs, and existing methods discard it‼️ PPoT uses this distribution to extract free performance and efficiency gains. 🧵👇

Daniel Israel

11,655 görüntüleme • 2 ay önce

Most underrated skill today: Observability. I feel you can build a career just on this and have 2 decades of guaranteed money if you learn the skill well, and I'll tell you how below. Reality: Most teams I help look at me with dead eyes when I ask them about observability. That's sad, but it's the current state of the industry: • No tracing • No structured data • No way to understand what's happening when things break Outside of the most sophisticated companies, that's still where most teams are. AI is now writing a ton of code, and people are shipping this code to production. However important observability was before, it is 10x more important today. Believe me, you don't want to be the one pushing slop into production and then guessing how it works, with no way to understand what happens. Here is your first step: Honeycomb is running a FREE, 3-day virtual event focused entirely on observability. The event is running May 12-14. Did I mention it's completely free? Everything will revolve around observability for the agent era. Register here: Thanks to the Honeycomb.io System Status Updates team for partnering with me on this post.
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Most underrated skill today: Observability. I feel you can build a career just on this and have 2 decades of guaranteed money if you learn the skill well, and I'll tell you how below. Reality: Most teams I help look at me with dead eyes when I ask them about observability. That's sad, but it's the current state of the industry: • No tracing • No structured data • No way to understand what's happening when things break Outside of the most sophisticated companies, that's still where most teams are. AI is now writing a ton of code, and people are shipping this code to production. However important observability was before, it is 10x more important today. Believe me, you don't want to be the one pushing slop into production and then guessing how it works, with no way to understand what happens. Here is your first step: Honeycomb is running a FREE, 3-day virtual event focused entirely on observability. The event is running May 12-14. Did I mention it's completely free? Everything will revolve around observability for the agent era. Register here: Thanks to the Honeycomb.io System Status Updates team for partnering with me on this post.

Santiago

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💥 OSS product analytics for LLM apps. Launching PostHog x langfuse.com integration 🤝 🫳 Day 1 drop of Langfuse Launch Week: We’re marrying product analytics and LLM observability. This integration pipes Langfuse events/metrics/evals into your PostHog project. This allows you to access all of your LLM metrics straight from your Posthog dashboards. I've used it to reality-check our evaluations by correlating them with user retention and ingestion metrics that we already measure in PostHog. This integration is now in public-beta and you can enable it within your Langfuse project settings. Thank you james hawkins, timgl and Lior Neu-ner for working on this over the past couple of weeks and to everyone who joined the private beta. More details: Quick tour of the integration 👇
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💥 OSS product analytics for LLM apps. Launching PostHog x langfuse.com integration 🤝 🫳 Day 1 drop of Langfuse Launch Week: We’re marrying product analytics and LLM observability. This integration pipes Langfuse events/metrics/evals into your PostHog project. This allows you to access all of your LLM metrics straight from your Posthog dashboards. I've used it to reality-check our evaluations by correlating them with user retention and ingestion metrics that we already measure in PostHog. This integration is now in public-beta and you can enable it within your Langfuse project settings. Thank you james hawkins, timgl and Lior Neu-ner for working on this over the past couple of weeks and to everyone who joined the private beta. More details: Quick tour of the integration 👇

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Building with AI gets easier every day. Here is an open-source library that makes integrating AI into an application extremely easy: Star the repository! This library alone can make React the best front-end framework out there! There are a bunch of cool things I like about CopilotKit. Here are 3 of them: 1. It allows you to take any -powered agent and bring it into your application. (This is a brand-new feature!) 2. You can build an AI-powered chatbot in your application. The chatbot will have access to your context and can act on the application. 3. You can build a RAG workflow to process and answer questions from a real-time knowledge base. I recorded a video to show you how simple it is to make some of this happen. A few lines of code, and you are in business. Here is a link to the sample application: CopilotKit is open-source. You can self-host it. You can use it with any LLM. Thanks to the team for showing me their tool and collaborating with me on this post!
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Building with AI gets easier every day. Here is an open-source library that makes integrating AI into an application extremely easy: Star the repository! This library alone can make React the best front-end framework out there! There are a bunch of cool things I like about CopilotKit. Here are 3 of them: 1. It allows you to take any -powered agent and bring it into your application. (This is a brand-new feature!) 2. You can build an AI-powered chatbot in your application. The chatbot will have access to your context and can act on the application. 3. You can build a RAG workflow to process and answer questions from a real-time knowledge base. I recorded a video to show you how simple it is to make some of this happen. A few lines of code, and you are in business. Here is a link to the sample application: CopilotKit is open-source. You can self-host it. You can use it with any LLM. Thanks to the team for showing me their tool and collaborating with me on this post!

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Reading papers and taking notes for literature review takes a lot of time. You can install ChatGPT in your Zotero to supercharge your literature review. It will answer your questions based on papers in your library, so no fake citations or references. Here's how to do it:
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Reading papers and taking notes for literature review takes a lot of time. You can install ChatGPT in your Zotero to supercharge your literature review. It will answer your questions based on papers in your library, so no fake citations or references. Here's how to do it:

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BUY ONE GET ONE FREE 🤩 click the link BUY ANY CBD OIL from @supremecbd tonight and get a FREE oil the same strength absolutely free, you still get 40% of with code Fowler40 this a limited time only as no profit in it for me 😅 #supremecbd #mybrand
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BUY ONE GET ONE FREE 🤩 click the link BUY ANY CBD OIL from @supremecbd tonight and get a FREE oil the same strength absolutely free, you still get 40% of with code Fowler40 this a limited time only as no profit in it for me 😅 #supremecbd #mybrand

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This library will blow up for a simple reason: It's the best for building a chatbot that doesn't hallucinate and knows how to answer questions. It's open-source, and it literally takes a few lines of code to run. Check the attached video.
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This is huge for production applications! Literally every developer has to deal with server errors they can't reproduce, and it doesn't matter how many logs they have. You don't have to be "every developer" anymore. Look into Hud's Runtime Code Sensor. Hud is one of my collaborators, and their code sensor is a game-changer for production applications. Watch the video I'm attaching here. For those of you who'd prefer a TL;DR; Hud captures how code behaves in production and puts those insights in context right in your IDE. This is really cool! You can see on top of every function data about how it works in production: • How long does it take to run? • How many times has the function failed? • Are the number of failures going up or down? All of this information is accessible to Cursor, Copilot, or WindSurf via an MCP server. That means that you can use the IDE to act on these issues! The way Hud works: • They provide a lightweight SDK • It takes one line to configure • All insights are right in your code • No dashboard necessary The best part: Their free plan includes ALL features they offer, so you can actually try it out properly and see how it fits your workflow. No paywall, no trial. Here is the link: Logging everything is great, but getting production insights right next to the code is definitely next-level!
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This is huge for production applications! Literally every developer has to deal with server errors they can't reproduce, and it doesn't matter how many logs they have. You don't have to be "every developer" anymore. Look into Hud's Runtime Code Sensor. Hud is one of my collaborators, and their code sensor is a game-changer for production applications. Watch the video I'm attaching here. For those of you who'd prefer a TL;DR; Hud captures how code behaves in production and puts those insights in context right in your IDE. This is really cool! You can see on top of every function data about how it works in production: • How long does it take to run? • How many times has the function failed? • Are the number of failures going up or down? All of this information is accessible to Cursor, Copilot, or WindSurf via an MCP server. That means that you can use the IDE to act on these issues! The way Hud works: • They provide a lightweight SDK • It takes one line to configure • All insights are right in your code • No dashboard necessary The best part: Their free plan includes ALL features they offer, so you can actually try it out properly and see how it fits your workflow. No paywall, no trial. Here is the link: Logging everything is great, but getting production insights right next to the code is definitely next-level!

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Want one? I have a discount code available. Say "CODE" and I'll send it to you. Get your strike in shape - even at home - ready for the start of the season
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One of the best ways to win your time back with GitHub Copilot is to have it generate Git commit messages for you. Everyone has their own style - share yours with Copilot using Custom Instructions and save yourself a ton of time.
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