Today, we're proud to announce DeepEval 4.0 — the AI evaluation harness for vibe coding agents. Our biggest and boldest release yet.
A long thread 🧵 @deepeval :
Vibe coding is dead. Vibe coding without vibing is the way forward.
Coding tools like @Claude code, @cursor_ai, and more don't make real progress in improving agents.
The last mile is what's difficult.
I’m running LLM eval office hours today with @confident_ai 🧪
If you’re building anything with AI, drop a prompt + model output, and I’ll show where it breaks.
I’ll look at:
correctness
completeness
where it might fail in real use.
Just quick, specific feedback
#ai#LLM
My sister just got released, DeepTeam v1.0, 100% open-source, Apache 2.0 red teaming for LLMs.
⭐ Star on GitHub to stay on top of the latest developments in AI security and safety: https://t.co/FwtIQ5xiSA
Most people run single-turn evals on chatbots.
But that’s not enough.
Conversations aren’t Q&A — they happen over multiple turns.
This means your chatbot must stay context-aware across the dialogue, not just accurate in isolated responses.
@deepeval, we’ve seen too many teams evaluate chatbots the wrong way.
So, we wrote a comprehensive guide on how to evaluate all chatbots properly, end-to-end.👇
🔗 https://t.co/L0iGyIct9X
At @confident_ai, we’re focused on making evals great.
But since we love our users very much, we’ve also just 5×’d the tracing analytics on our platform.
Now you can:
🔍 Trace analytics — follow every request end-to-end
⏱️ Span analytics — see latency and cost per component
📊 Model analytics — compare performance, latency, and cost across models
👥 User analytics — understand usage patterns and behavior
⚠️ Error analytics — track and reduce failures over time