Bryan Cox retweeted
We are no longer just traces. Now we support logs + traces.
console.logs/prints just get captured alongside traces and shown inline. It's a great way to add random context as your agent runs without creating spans.
You can also just send logs from random services :)
Send your application logs to Braintrust.
Connect app logs to agent traces to understand what went wrong and why. Debug with the context from both in one view without switching tools.
Learn more → braintrustdata.link/applicat…
we are building agents for gtm. we use @braintrust to make them great. but … you still need to pick up and the phone and get on planes. off to nyc to be with my east team and our customers. excited for the @usopen tomorrow night. let’s go
What’s better than being with the people you love! Big city and good food. Hope everyone had a great Labor Day! Mango mochi in Chinatown was a vibe. Kids are obsessed with counting Waymo’s 😂.
🔥
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 → braintrustdata.link/agent-ob…
Bryan Cox retweeted
Very excited to ship a major overhaul to Loop. It is now capable of running in the background, finding issues in your traces automatically, and sending you useful alerts.
Loop is architected as a single agent which has access to a broad set of tools and skills, all exposed through our MCP. The stuff we shipped today are not new features. They are effectively emergent behaviors that solve a bunch of important use cases.
This architecture has a number of advantages:
* Features compose (eg "find issues on traces that cost more than $5", "create a dataset of compaction issues")
* You can chat with anything, eg ask for more details on a pattern it found
* You can recreate 100% of Loop's features with your own agent, using our MCP
The last bullet is especially important to us. We do not want you to feel like you have to use our agent to access these features. Instead, we want to prove its value by building a great user experience and dealing with orchestration for you.
Take it for a spin. We'd love your feedback!
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 → braintrustdata.link/agent-ob…
Bryan Cox retweeted
If you want to reduce agent costs without trading away quality, the right unit of analysis is cost per resolved request, measured against the quality bar your product needs.
We evaled different strategies for optimizing agent cost-efficiency, and found that the strongest approach is routing plus guarded escalation, not a single-model replacement.
Read more → braintrustdata.link/cost-eff…
Bryan Cox retweeted
Being an Agent Lab also means collaborating with the best in the industry to define what comes next in agent observability.
Replit has been running this at scale for months👇
Bryan Cox retweeted
Cloudflare's dashboard agent spans its entire developer platform, from deploying Workers to debugging production instances. Keeping that much surface area performing well requires more than gut checks.
Their team uses Braintrust to run LLM-as-a-judge scorers to measure conversation resolution, gates every skill and prompt change with evals in CI/CD, and benchmarks sub-agents against models of varying capacity before choosing which to use.
Read more → braintrustdata.link/evals-cl…
Since coming to @braintrust, I’ve mostly used X to learn. AI moves fast, and I’ve spent a lot of time listening.
Figured I’d start sharing some. Expect thoughts on AI, sales as a craft, Bay Area sports analogies … looking forward to connecting with all of you!




















