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Build better examples from what went wrong

One engineering source, a connection to training and evaluation, and an eight-minute English task.

Reviewed today · source published October 2. The exercise is our teaching adaptation; we have not independently reproduced the experiments.

Engineering · 01

Turn an agent failure into a task you can verify

ServiceNow CoreAI · Esakkivel Esakkiraja et al. · AutoSynthData: Generating Training Data for Enterprise Agents ↗

Original · Reviewed
Intermediate · 8 min · suggested practice
Original ServiceNow CoreAI article · 2026-10-02

Why it matters

Before asking for more training examples, decide what a useful example must prove.

Reading note

AutoSynthData turns capability gaps into executable tasks, then checks valid and invalid outcomes. The authors report improvements in EnterpriseOps Gym; transfer to your workflow still needs testing.

Before this step: Agent · Tool · Workflow

Source excerpt
“Do relevant incorrect outcomes fail?”

One English pattern

A valid example must …; the check should reject …

Use must for an acceptance condition and should reject to name a failure case. This is our practice pattern, not a source quotation.

Try it at work

Choose a support-ticket task. Write three English sentences: what tools make it feasible, what a correct final record looks like, and one plausible wrong record your check must reject.

Check your draft

Did you explain the mechanism, name a condition, and make a concrete work decision? Saving records your draft, not a mastery score.

Back to the roadmap → Understand the technology · STEP 3
KEEP THE CONNECTION

Let the next useful idea come to you.

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2026-10-04 · Build better examples from what went wrong

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