Learn when to use System One models, then build 3 real projects with Jev: Playwright testing, code triage and AI observability.
Why Attend
Most AI systems today run on System Two: slow, expensive, generative LLM calls that reason at length. But most decisions inside engineering pipelines don’t need that. Is this test result suspicious? Which code issue matters most? Should this workflow act or escalate?
Those are System One decisions: fast, repeatable and structured, and your software needs to act on them immediately.
Jev is a System One decision model. You provide state, ask typed questions, and get back structured decisions with confidence scores that your application can branch, rank or route on directly. It is built to work alongside System Two LLMs, not replace them.
This workshop is about System One models in practice. Instead of an API demo, you’ll build three projects across testing, code health and observability. You’ll see when a System One decision is the right tool, when to hand off to an LLM, and how to combine the two in production.
Meet Your Instructor
Renata Andrade
Quality Engineer Lead | Test Automation Engineer & Architect
Renata is passionate about software quality and she helps teams build the best strategy to practice quality in the easiest, fastest and most reliable way possible, adding more value to the business. She is driven by excellence, innovation and creativity and loves making a difference, learning, sharing knowledge, and inspiring people.
Lineup
Renata Andrade
Good to know
Highlights
- 2 hours
- Online
Refund Policy
Location
Online event
Agenda
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Intro - What is Jev, architecture, LLM comparisons, Jev vs Laya
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Project 1 - Exploratory Testing with Jev & Playwright (hands-on)
Use Jev alongside Playwright to analyse application behaviour and return structured test decisions. You’ll learn how to turn observations from a live application into confidence-aware verdicts that can drive testing and escalation.
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Project 2 - Code Health with Repowise / CodeScene
Take output from RepoWise or CodeScene and use Jev to classify, score, and prioritise findings. Instead of manually reviewing every issue, you’ll build a decision layer that helps identify what deserves engineering attention first.