Video yükleniyor...

Video Yüklenemedi

Ana Sayfaya Dön

We raised $8m to build self-healing software. In 2026, software moves fast. But monitoring and observability are still manual and slow. Sazabi is a next-generation observability platform for fast-moving engineering teams. Not another AI SRE. Not another LLM observability tool. A new, general solution to observability that works for...

shcallaway's profile picture

Sherwood

5,478 subscribers

1,312,399 görüntüleme • 1 ay önce •via X (Twitter)

Haberler & PolitikaBilim & Teknoloji
LIVE

Anya Rossi• Live Now

Private livecam show

0 Yorum

Yorum bulunmuyor

Orijinal gönderinin yorumları burada görünecek

Benzer Videolar

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 LOGS ARE ALL YOU NEED The "Three Pillars of Observability" is an outdated idea.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:
2:09

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

117,804 görüntüleme • 6 ay önce

Cekura is an automated testing and observability platform for AI voice and chat agents. Leading brands and AI contact centers are driving six-figure cost savings by using @cekuraAI to run simulated conversations in pre-production and automate QA.
1:03

Cekura is an automated testing and observability platform for AI voice and chat agents. Leading brands and AI contact centers are driving six-figure cost savings by using @cekuraAI to run simulated conversations in pre-production and automate QA.

Y Combinator

13,841 görüntüleme • 1 yıl önce

i decided to put together all my AI engineering posts in a single pdf. it covers: > LLM foundations > prompt engineering > fine-tuning > RAG > context engineering > AI agents > MCP > optimization > deployment > eval and observability 375+ pages. download link in next tweet!
0:23

i decided to put together all my AI engineering posts in a single pdf. it covers: > LLM foundations > prompt engineering > fine-tuning > RAG > context engineering > AI agents > MCP > optimization > deployment > eval and observability 375+ pages. download link in next tweet!

Akshay 🚀

160,143 görüntüleme • 8 ay önce

.Ramp Labs (the AI unit of Ramp) has been *cooking* with agentic innovation Here's Alex L discussing and demo'ing code self-maintaining software and the concept of AI software factories #DataDrivenNYC ______________ 00:04 - Intro 01:11 - The shift from writing code to code maintenance 01:59 - Introducing Ramp Inspect, the background coding agent 03:05 - The first experiment: Nightly AI code automation 04:23 - The limits of stateless monitoring in large observability surfaces 05:47 - Using Datadog monitors to give the AI state and focus 07:23 - Real-world example: AI autonomously fixing an authentication bug 08:14 - How to control noise and implement an AI triage pattern 09:27 - The old vs. new paradigm for continuous code observability 10:21 - Key learnings on building autonomous AI software factories
14:21

.Ramp Labs (the AI unit of Ramp) has been *cooking* with agentic innovation Here's Alex L discussing and demo'ing code self-maintaining software and the concept of AI software factories #DataDrivenNYC ______________ 00:04 - Intro 01:11 - The shift from writing code to code maintenance 01:59 - Introducing Ramp Inspect, the background coding agent 03:05 - The first experiment: Nightly AI code automation 04:23 - The limits of stateless monitoring in large observability surfaces 05:47 - Using Datadog monitors to give the AI state and focus 07:23 - Real-world example: AI autonomously fixing an authentication bug 08:14 - How to control noise and implement an AI triage pattern 09:27 - The old vs. new paradigm for continuous code observability 10:21 - Key learnings on building autonomous AI software factories

Matt Turck

67,829 görüntüleme • 3 ay önce

Introducing Coldtea. The ADE for shipping self-driving software. Purpose-built for the entire software lifecycle. Other IDEs optimise for one thing: Build. Run more agents in parallel, ship faster, orchestrate better. But software engineering is not just about building. Coldtea AI brings your coding agents, agentic end-to-end testing, and production monitoring agents into ONE development environment, so you can move at agent speed without breaking anything.
1:00

Introducing Coldtea. The ADE for shipping self-driving software. Purpose-built for the entire software lifecycle. Other IDEs optimise for one thing: Build. Run more agents in parallel, ship faster, orchestrate better. But software engineering is not just about building. Coldtea AI brings your coding agents, agentic end-to-end testing, and production monitoring agents into ONE development environment, so you can move at agent speed without breaking anything.

Ohans Emmanuel

436,495 görüntüleme • 12 gün 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.
1:33

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

19,983 görüntüleme • 3 ay önce

At DevCon 6, Palantir Software Engineer Ankit Shankar unveils the Agent Stack, a set of products to help you build production agents for the enterprise, all built on the Ontology. ▪️Orchestrator for durable execution ▪️Agent Engine and Agent SDK for building agents of any shape ▪️Agent Manager for actionable telemetry and observability ▪️AIP Evolve for continuous, end-to-end optimization
2:08

At DevCon 6, Palantir Software Engineer Ankit Shankar unveils the Agent Stack, a set of products to help you build production agents for the enterprise, all built on the Ontology. ▪️Orchestrator for durable execution ▪️Agent Engine and Agent SDK for building agents of any shape ▪️Agent Manager for actionable telemetry and observability ▪️AIP Evolve for continuous, end-to-end optimization

Palantir

40,626 görüntüleme • 1 ay önce

🎉 Introducing New Relic Grok, the first generative AI assistant for observability. Now, any engineer (dev, DevOps, security, product, QA, support) can ask New Relic Grok, in plain language, to set up instrumentation, detect and fix issues, and manage accounts. 🧵
1:10

🎉 Introducing New Relic Grok, the first generative AI assistant for observability. Now, any engineer (dev, DevOps, security, product, QA, support) can ask New Relic Grok, in plain language, to set up instrumentation, detect and fix issues, and manage accounts. 🧵

New Relic

37,160 görüntüleme • 3 yıl önce

Its time Indian youth and parents give up on Engineering Graduation especially in IT AI will do a better job at building software. And to use AI to build software you do not need to go to the process of getting a Engineering Degree.
0:33

Its time Indian youth and parents give up on Engineering Graduation especially in IT AI will do a better job at building software. And to use AI to build software you do not need to go to the process of getting a Engineering Degree.

Woke Eminent

171,090 görüntüleme • 7 ay önce

Datadog is one of the largest infrastructure success stories of the last decade. Now they’re betting on AI: a SOTA in-house time series model, observability for AI, and more. I talked to Datadog CEO Olivier Pomel about Datadog’s AI strategy and where he thinks things are going:
56:03

Datadog is one of the largest infrastructure success stories of the last decade. Now they’re betting on AI: a SOTA in-house time series model, observability for AI, and more. I talked to Datadog CEO Olivier Pomel about Datadog’s AI strategy and where he thinks things are going:

Barr Yaron

10,386 görüntüleme • 11 ay önce

Sometimes the best way to build a UI for an agent is to not build the UI at all. I built an AI agent starter that lives in iMessage. Built on Nitro + Vercel Workflow SDK + evlog - Durable execution - Auto-retry on errors - Full observability
0:28

Sometimes the best way to build a UI for an agent is to not build the UI at all. I built an AI agent starter that lives in iMessage. Built on Nitro + Vercel Workflow SDK + evlog - Durable execution - Auto-retry on errors - Full observability

Hugo

11,692 görüntüleme • 3 ay önce

When the way software is built changes, we help companies adopt it. For over a decade, that meant bringing React Native to production across mobile, web, desktop, and TV. Now we are expanding that same mission to AI-native engineering: helping teams ship software with agents, safely and at scale. This is our new manifesto.
1:33

When the way software is built changes, we help companies adopt it. For over a decade, that meant bringing React Native to production across mobile, web, desktop, and TV. Now we are expanding that same mission to AI-native engineering: helping teams ship software with agents, safely and at scale. This is our new manifesto.

Callstack Engineers

24,718 görüntüleme • 2 ay önce

🚨We’re excited to Introduce AI HQ — your home for building, activating, and supervising AI agents across your enterprise 🚨 We’re giving IT and business teams an end-to-end platform to co-create AI agents that don’t just assist. They act. These agents are fully integrated, grounded in company data, and built to execute high-impact business processes autonomously. New capabilities in AI HQ include: ⚡ Agent Builder (Beta): Your shared development environment where IT and business teams collaboratively build AI agents. Low-code tools make it easy to map out logic with reusable blocks, connect to systems and data, design interfaces with drag-and-drop simplicity, and more. 🏠 Writer Home: Your personalized AI workspace with 100+ prebuilt agents for every function - from support to sales to HR - ready to go and accessible via desktop, browser, or extensions. It’s your new front door to real AI-powered work. 🛡️ Observability Tools (Beta): Gain full control and visibility into every agent with enterprise-grade observability: monitor activity activity, detect anomalies, and resolve issues before they escalate. It’s how AI moves from experimental to operational. Companies like Uber Commvault and Franklin Templeton (Franklin Templeton) are already using Writer AI agents to reinvent knowledge management, accelerate revenue workflows, and deliver smarter client experiences. This isn’t hype. It’s happening now. 👀 Dive into today’s announcement:
1:28

🚨We’re excited to Introduce AI HQ — your home for building, activating, and supervising AI agents across your enterprise 🚨 We’re giving IT and business teams an end-to-end platform to co-create AI agents that don’t just assist. They act. These agents are fully integrated, grounded in company data, and built to execute high-impact business processes autonomously. New capabilities in AI HQ include: ⚡ Agent Builder (Beta): Your shared development environment where IT and business teams collaboratively build AI agents. Low-code tools make it easy to map out logic with reusable blocks, connect to systems and data, design interfaces with drag-and-drop simplicity, and more. 🏠 Writer Home: Your personalized AI workspace with 100+ prebuilt agents for every function - from support to sales to HR - ready to go and accessible via desktop, browser, or extensions. It’s your new front door to real AI-powered work. 🛡️ Observability Tools (Beta): Gain full control and visibility into every agent with enterprise-grade observability: monitor activity activity, detect anomalies, and resolve issues before they escalate. It’s how AI moves from experimental to operational. Companies like Uber Commvault and Franklin Templeton (Franklin Templeton) are already using Writer AI agents to reinvent knowledge management, accelerate revenue workflows, and deliver smarter client experiences. This isn’t hype. It’s happening now. 👀 Dive into today’s announcement:

WRITER

10,837 görüntüleme • 1 yıl önce

Excited to announce the new preview for Microsoft Foundry Agents 🎉! You can now build, run, and deploy your agent using any model, any framework, any harness in the cloud 🧑‍💻 - check out the demo below This is not just any cloud compute environment; it's an agent-optimized platform with: 🖥️ Persistent microVMs - securely scale up and down without losing context 🛠️ Built-in tools (1000+) 👀 Observability and evaluations 👷 Guardrails 🔐 Private networking... and more
8:10

Excited to announce the new preview for Microsoft Foundry Agents 🎉! You can now build, run, and deploy your agent using any model, any framework, any harness in the cloud 🧑‍💻 - check out the demo below This is not just any cloud compute environment; it's an agent-optimized platform with: 🖥️ Persistent microVMs - securely scale up and down without losing context 🛠️ Built-in tools (1000+) 👀 Observability and evaluations 👷 Guardrails 🔐 Private networking... and more

Jeff Hollan

157,915 görüntüleme • 4 ay önce

Introducing HydraDB. The graph native context infrastructure for agents. Purpose built to deliver precise context & observability into why agents act the way they do. We've always believed graphs are the best way to manage AI context, but they've been too expensive to scale or impractical for storing full context. Until now. HydraDB combines in memory, NVMe, and object storage into a single graph layer, making context delivery faster, cheaper, and more precise. We want context delivery to be extremely fast, 1000x cheap, and highly precise. Give your agents a brain.
1:18

Introducing HydraDB. The graph native context infrastructure for agents. Purpose built to deliver precise context & observability into why agents act the way they do. We've always believed graphs are the best way to manage AI context, but they've been too expensive to scale or impractical for storing full context. Until now. HydraDB combines in memory, NVMe, and object storage into a single graph layer, making context delivery faster, cheaper, and more precise. We want context delivery to be extremely fast, 1000x cheap, and highly precise. Give your agents a brain.

Nishkarsh

2,299,606 görüntüleme • 2 ay önce