Perplexity reports a 21% fall in failed tool calls after retraining its agent
single source· 1 articles · confidence: low · first seen 2026-09-25 14:30 UTC
What this means for you
Nothing to act on. This is an internal training run on one company's own agent: no published method, no weights, no date. The transferable point is that logged production failures are training data — if you serve an agent, you probably already have them.
Perplexity Research says retraining its Perplexity Computer agent cut failed tool calls from 2.24% to 1.77%, a 21.2% relative fall, in a live A/B test between two trained checkpoints. The method pairs rejection sampling fine-tuning, which keeps only generated attempts that pass a check, with hint-guided self-distillation — the model learns from its own outputs, with hints supplied, rather than from a separate teacher. Training draws on real user sessions, failures included. The write-up gives no evaluation date, no harness and no comparison against an untrained checkpoint.
Key facts
- ·Perplexity Research trained a model inside Perplexity Computer on real user sessions, including failed ones source
- ·Tool-call failures fell from 2.24% to 1.77% between two trained checkpoints in a live A/B test source
- ·Perplexity reports the drop as a statistically significant 21.2% relative reduction source
- ·The method pairs rejection sampling fine-tuning with hint-guided self-distillation source
- ·The write-up gives no evaluation date, no harness and no comparison against an untrained checkpoint source
What the sources say
- MarkTechPost — Short summary of Perplexity's post-training write-up, covering the method and the reported failure-rate drop
Sources
The original reporting. Follow these — they did the work.
- MarkTechPostPerplexity Trains Its Computer Agent on Real Mistakes With Hint-Guided Self-Distillation2026-09-25