What should I use for LLM observability on a small team?

For a small team, I’d optimize for fast setup, good tracing, and low operational overhead rather than a heavyweight platform.

Best default options

1) Langfuse — best overall for small teams

Good if you want:

• LLM tracing / prompt tracking
• Cost and token usage
• User/session-level debugging
• Open-source + hosted options
• Easy integration with common stacks

Why it’s a strong default:

• You can get useful observability in place quickly
• It works well for debugging chains/agents
• It’s affordable and doesn’t feel overbuilt

2) OpenTelemetry + your existing backend observability

Good if your team already uses:

• Datadog
• Grafana/Tempo/Prometheus
• Honeycomb
• New Relic

Why:

• Keeps everything in one place
• Better if you want one observability stack for app + infra + LLM
• More flexible, but usually more setup than a purpose-built LLM tool

3) Helicone

Good if your main need is:

• API gateway/proxy-style logging
• Request/response capture
• Cost monitoring
• Quick visibility into OpenAI/Anthropic usage

Why:

• Very easy to start
• Nice for small teams that want “turn it on and see what’s happening”
• Less rich than some tracing-first tools for complex agent workflows

My practical recommendation

If you’re a small team building an LLM app today:

• Start with Langfuse if you care about debugging chains/agents and prompt iteration
• Start with Helicone if you mainly want logging + cost tracking with minimal effort
• Use OpenTelemetry if your team already has a mature observability stack and wants to standardize

What to look for

A good small-team LLM observability tool should have:

• Traceability across prompts, tool calls, retrievers, and model outputs
• Prompt/version tracking
• Latency + token/cost metrics
• Error capture and replay
• PII redaction / data controls
• Sampling so you don’t log everything forever

If you want the simplest answer

• Best overall: Langfuse
• Simplest logging/proxy: Helicone
• Most “enterprise standard” path: OpenTelemetry + existing backend stack

If you tell me your stack (Python/JS, OpenAI/Anthropic, agents vs simple chat, and whether you already use Datadog/Grafana/etc.), I can recommend the best fit more precisely.