I wrote about a hard truth in RAG:
👉 Retrieval doesn’t eliminate hallucinations.
Even with good context, models can still give wrong answers.
In this blog:
* Where hallucinations come from
* Why retrieval isn’t enough (Dont trust the model!)
🔗 https://t.co/X5dxDIAenc
Been working with LLM systems lately and one thing stands out:
We track latency, tokens, cost… but barely look at the GPU.
which is where all the work happens.
Most debugging pain I’ve hit comes from this gap.
I wrote this blog to connect the dots:
https://t.co/QxiUXLbjFG
We wrote a quick guide on adding observability to LLM apps with OpenTelemetry.
Trace prompts, debug issues, and track latency/cost in minutes 👇
https://t.co/SYBI4VQylo
🚀 Python SDK v1.38.2 is out!
- Span name filtering
- VictoriaMetrics support
- Fix for eval LLM temperature
- Open WebUI pipeline improvements
- Dependency upgrades
Shoutout to new contributors 🎉
#AI#OpenSource#DevTools#openlit#llmops
Void Manticore didn't hack Stryker.
They logged into Stryker.
One phished token. Global Admin created at 3:14 AM. Every CA policy disabled. Bulk wipe- 214,839 devices, 79 countries, 28 minutes.
We rebuilt the entire kill chain as a 15-page manga. Page and PDF in the thread 🧵
Research sourced from @_CPResearch_@Unit42_Intel@cloudsa
#VoidManticore #Handala #Stryker #MicrosoftIntune #EntraID #ThreatIntelligence #ZeroTrust #InfoSec
Come along to the DevOps Society meetup. There's talks on challenges running K8 clusters in prod, and myself on observing AI applications with @openlit_io OTel signals and @elastic.
https://t.co/T1IYw7xwKq
See you there! 👋
Just dropped an episode on the AI Engineering Podcast with Tobias Macey
We covered what it takes to ship LLM apps to production — observability, cost tracking, vendor-neutral, and more @openlit_io
https://t.co/KplKAUr9lG
⭐ https://t.co/JPJK3n6dDT
#OpenTelemetry#AIEngineering
We were copy-pasting the same claude code skills across 5 projects like cavemen. update one, forget the other four, ship a bug on friday at 5pm. classic.
so we did the only logical thing, asked claude to build a project manager for claude projects.
introducing cldpm. open source, works today.
Github: https://t.co/j9kWn7Cw64
PyPI: https://t.co/mcFdXWrXqq
npm: https://t.co/oGVFy3q841
#ClaudeCode #AI #OpenSource #DevTools #BuildInPublic
Adding application instrumentation is important because it helps us diagnose issues and bottlenecks. AI agents are no different!
OpenLit can be configured within your agent to send #telemetry information to Elastic via the following initialization:
@elastic_devs 2025 was definitely an AI learning year for me. I enjoyed building my first #typescript agent leveraging #elasticsearch and context engineering, and observing another with @elastic and @openlit_io:
https://t.co/ygkh5mRgzM
https://t.co/88Xz6sbTeK
OpenLIT's Zero-code LLM Observability
🏅 Product Hunt Data
Ranking: 2025W41-rank45
Upvote: 149
🚀 Product Overview
OpenLIT offers zero-code observability for LLM applications and AI agents, allowing teams to monitor performance across models, vector databases, and GPU resources without modifying code or redeploying services.
📋 More Details
Built for teams managing production LLM workflows, OpenLIT eliminates friction by supporting both Kubernetes-native (via Helm) and cross-platform CLI installation. It works with existing tools like OpenAI, Anthropic, and LangChain, with flexible instrumentation and no vendor lock-in.
📊 Evaluation
AI Native Application Modernization: 91/100
OpenLIT is deeply AI-native, built specifically for LLM-based pipelines. Its zero-code model supports tight integration with language agents and prompt engineering, enabling rapid iteration in AI-based services.
🔗 Website
https://t.co/I8aMUNlufC
@openlit_io
Hey Everyone, We’re officially live on Product Hunt!
📷Introducing Zero-Code Observability for LLMs and AI Agents.
If you find our product useful, a quick upvote would mean a lot and help us reach more people:
https://t.co/oekxqOYudo
Hey 👋 My team and I just launched a product that makes it easy to track how AI tools perform — no setup changes and is Free! Takes under 5 minutes to use and works with most AI systems. Would mean a lot if you could check it out and upvote us here: 👉 https://t.co/Nn6TTEtbuE
🚀 Running LLMs on your own GPU?
Monitor memory, temp & utilization with the first OpenTelemetry-based GPU monitoring for LLMs.
⚡ OpenLIT tracks GPU performance automatically — focus on your apps, not hardware.
👉 https://t.co/BTEpV3epGJ
#LLMObservability#OpenTelemetry