How OpenTelemetry observes AI agents without code changes
OpenTelemetry eBPF Instrumentation captures LLM calls, MCP tool calls, embeddings, and reranks at the network layer, giving multi-agent apps full traces with no code.
Causely Feature Demo: Faster Investigations with AWS DevOps Agent
With the Causely MCP server, AWS DevOps Agent halved its investigation time and cut tool calls from 36 to 10. With an external fault, 3 minutes instead of 15.
How to make Claude background agents 3-5x faster and cheaper
In three regression scenarios, Claude Managed Agents with Causely produced correct fixes 3.6–5.7x faster and at 3.5–5x lower cost than the baseline agent.
What should trigger an autonomous agent in production?
A control band breach tells an autonomous agent only that a metric moved. A trigger carrying a causal chain tells it what broke and how far the problem reaches.
How to Check an Agent's Diagnosis Before It Touches Production
New Causely MCP tools show which diagnoses an agent ruled out and how far a failure would spread, so teams can verify the agent's reasoning before acting in production.
How to Operate AI Agents in Production: The Three-Layer Stack
Operating AI agents in production takes three layers: instrumentation, evaluation, and causal reasoning, including the root-cause analysis behind agent reliability.
Why A2A Joining the AAIF Matters
Causely joins the AAIF along with A2A from Google. Agents can now talk over an open standard, but what they say is only as good as the context they start from.
How Open-Inspect and Causely close the loop on autonomous remediation
Open-Inspect gives background agents an execution environment. Causely gives them a causal diagnosis. Together, they close the loop from finding to fixing.
Is access enough? Auth patterns for Claude Managed Agents
MCP tunnels let Claude Managed Agents reach and authenticate to real infrastructure, but access alone doesn't make an agent one you'd trust to run on-call.
Introducing Issues, one problem, one thread, start to finish.
On-call means re-triaging the same problem as diagnoses shift underneath you. Causely's new Issues give people and agents one stable thread instead.
Expanded Dynatrace Support: Better, Faster, Cheaper Agents
Causely turns Dynatrace entities, topology, and alerts into a causal model that names the root cause, making on-call agents better, faster, and cheaper.
Your on-call AI agent is wrong more than you think
Most frontier LLMs degrade badly by ~1,000 tokens of input, not the millions in their spec sheets. For on-call agents, that means accuracy drops exactly as an incident gets complex. The fix isn't a bigger model. It's not handing the LLM the raw data at all.