Use both. Here's where each one wins.
Observability tools see failures. Pisama acts on them. They are precondition layers; we are the action layer above. The comparison below is honest about where each one is stronger, not a zero-sum claim.
Pisama vs Braintrust
Braintrust is excellent at eval workflow: dataset versioning, scoring functions, regression dashboards, comparing model versions side-by-side. Pisama is failure detection: when an agent run goes wrong, name the failure and locate the step.
These are not competitors. Braintrust evaluates outputs against expected behavior; Pisama detects when execution itself misbehaves. Most teams shipping agentic systems need both.
- Best-in-class eval workflow UX (dataset diffs, scorer authoring)
- Tight CI integration: evals as part of the deploy gate
- Fast playground for prompt iteration
- 87 detectors, 6 externally validated at production grade, with published F1
- In-flight detection: failures caught while the agent is still running
- Single-agent, multi-agent, and sub-agent failures: coordination, loops, persona drift, silent cascades. Braintrust scorers do not target these
At a glance
| Dimension | Braintrust | Pisama |
|---|---|---|
| Primary job | Output evaluation workflow | Process-level failure detection |
| When detection runs | Post-hoc against datasets | Synchronous, mid-execution |
| Author scorer how | Custom code or LLM judge per scorer | Pre-calibrated detector packs |
| Agent failure depth | Trace UI; scorers per agent | Single, multi, and sub-agent detectors (coordination, loops, silent cascade) |
Externally validated at production grade: real-trace F1 0.80 or higher, precision 0.70 or higher, 30 or more external traces, external-grounded thresholds, and no per-difficulty blind spot (capability registry, external-only lane, 2026-06-14).
Recommendation
Braintrust for "did this prompt change regress the eval set?" Pisama for "did this run fail, and where?" Run both.
FAQ
- Is Pisama a Braintrust scorer?
- You can wrap Pisama detectors as Braintrust scorers. The detection happens locally; the result is a structured DiagnosisResult that maps cleanly to a Braintrust scorer output.