Ileanell Perez, an engineering manager at Honeycomb, responded to the company's push for AI tool adoption by creating dedicated time for connection, collaboration, and discussion rather than writing a…
AI model drift, a gradual decline in performance as production data diverges from training baselines, threatens reliability even when infrastructure metrics stay healthy, according to a guide by Dan J…
Honeycomb announced the general availability of AI BubbleUp, an AI-powered feature that summarizes significant correlations in BubbleUp results, available to all customers who have enabled Honeycomb I…
Douglas Soo, a 30-year software developer at startups, reports that LLM-driven coding is exhausting senior engineers and stressing junior engineers, with teams shipping more but understanding less. So…
Fred Hebert's team at Honeycomb deliberately leaned into the code review bottleneck caused by AI-generated code, choosing to maintain thorough reviews rather than reduce them. The team found that velo…
Honeycomb processes 2 million agent-initiated query runs per month, up from a $0.60 eight-tool-call demo a year ago, with average tool calls per session doubling between February and June, according t…
Honeycomb engineering team 2.5x-ed their throughput using AI without breaking quality, but the key lesson is that AI amplifies existing practices—it cannot fix a dysfunctional organization. The team e…
Honeycomb's engineering team more than doubled peak-weekday merges from ~30 to ~74 by April 2026, with AI-attributed code rising from near-zero to 82.6% of new code by June 2026, according to a blog p…
Honeycomb completed a multi-month migration of its Kafka infrastructure from self-hosted Confluent Platform and ZooKeeper on AWS EC2 to open-source Apache Kafka 4.1.1 running in KRaft mode on AWS EKS.…
Fin CTO Darragh Curran writes that AI is an amplifier of existing engineering practices, not a magic wand, and that engineering rigor remains essential. The second edition of Observability Engineering…
A new guide from Shabih Syed compares 15 leading AI observability tools for production teams in 2026, evaluating them on tracing depth, evaluation support, token cost visibility, OpenTelemetry compati…
Monitoring catches the failures you predicted, but AI systems fail in ways you didn't, according to Kale Bogdanovs in a post on the Honeycomb blog. The post argues that AI workloads demand observabili…
Honeycomb built a multi-agent collaboration architecture for its Canvas investigation tool, where multiple engineers' AI agents operate independently in the same runtime session while sharing awarenes…
Honeycomb has shipped a production integration with Amazon Bedrock AgentCore, surfacing agent telemetry in its Agent Timeline tool. The company chose AgentCore for its modularity and production-grade …
Reid Savage, an engineering manager at Honeycomb, reflects on his first year leading the SRE team, emphasizing the importance of investing in relationships, seeking feedback, and distinguishing betwee…
At O11yCon, engineering teams from Mixpanel, Gem, and StarSling reported using AI to boost code velocity by up to 50%, with observability tools like Honeycomb critical for managing the increased volum…
Honeycomb released the second edition of Observability Engineering, a near-complete rewrite addressing AI-era challenges like validating AI-generated code in production and the risk of shipping faster…
Honeycomb released a technical guide on instrumenting AI agents with OpenTelemetry's GenAI semantic conventions to enable debugging via the Agent Timeline, which captures tool calls, multi-agent hando…
Honeycomb conducted scheduled Kafka maintenance on May 4 (EU) and May 7 (US), 2026, replacing a decade-old cluster with a newer, more scalable one. The maintenance caused up to 90 minutes of query dow…
Honeycomb announced the general availability of Agent Timeline, a tool that provides a unified view of LLM behavior and multi-agent workflows to help developers debug agent conversations faster. The f…