Jesse Berkeley
Senior Test Engineer

Hey folks, I am Jesse Berkeley and I'm here to learn from you all as I continue to grow in the craft of test engineering and quality engineering. Looking forward to learning from the community!

Open To
Write
Podcasting
Meet at MoTaCon 2026
Team Account Member
Attending MoTaCon 🤝
Ambassador

Achievements

Club Explorer
Bio Builder
TestBash Trailblazer
Career Champion
Avid Reader
Article Maven
MoT Community Certificate
The Testing Planet Contributor
MoT Streak
Unlimited Member
In the Loop
MoT Ambassador 2025
Bug Finder
Collection Curator
Glossary Contributor
Photo Historian
TestBash Brighton 2025 Attendee
TestBash Brighton 2024 Attendee
Cert Shaper
Bug reporting 101
99 and Counting
Social Connector
Open to Opportunities
Found at 404
Picture Perfect
Leading with Quality 2025 Attendee
Kind Click
Supportive Clicker
Encouragement Giver
Insights Taster
MoT Ambassador 2026
Chapter Discovery
Moment Maker
Moment Sharer
Leading with AI London 2026 Attendee

Certificates

MoT Community Certificate image
Awarded for: Achieving 5 or more Community Star badges

Activity

Jesse Berkeley
Jesse Berkeley
thanked contributors on:
Why teams miss system signals image
Why teams miss system signals
Jesse Berkeley
Jesse Berkeley
awarded Ady Stokes for:
Why teams miss system signals image
Why teams miss system signals
Jesse Berkeley
Jesse Berkeley
awarded WonderProxy for:
Why teams miss system signals image
Why teams miss system signals
Jesse Berkeley
Jesse Berkeley
awarded Hanisha Arora for:
Why teams miss system signals image
Why teams miss system signals

Contributions

Lead change through mentoring and shared ownership image
  • Preeti Gupta's profile image
The G.R.O.W FrameworkA human-centred approach to adopting AI in test engineering. G — Guide with Empathy R — Reskill the Team O — Ownership over AI W — Win Measurable Impact
Leading with AI — by testers, for testers image
  • Simon Tomes's profile image
  • Diana Dromey's profile image
Simon and Diana kicking things off with the LwAI where the testing community meets AI — and leads the change.
What's the hardest part of defining "expected behaviour" for a system that produces different output every time? image
  • Piotr Wicherski's profile image
  • Simon Tomes's profile image
  • Oleksandr Romanov's profile image
  • Lauren Lassey's profile image
  • Jesse Berkeley's profile image
  • James Pearce's profile image
  • Adam Davis's profile image
  • Demi Van Malcot's profile image
When a system improvises like a jazz soloist, "different" stops meaning "wrong"
How would you define a guardrail? image
  • Simon Tomes's profile image
  • Lauren Lassey's profile image
  • Jesse Berkeley's profile image
  • James Pearce's profile image
  • Preeti Gupta's profile image
  • Shawn Vernier's profile image
AI needs guardrails to play by the rules and work better
AI Guardrails Masterclass 🧡🚀 image
  • Cassandra H. Leung's profile image
  • Simon Tomes's profile image
  • Diana Dromey's profile image
  • Ady Stokes's profile image
  • Andy Flynn's profile image
  • Sharon O'Boyle's profile image
  • Giorgos Siamantas's profile image
  • Phillipe Bojorquez's profile image
  • Rosie Sherry's profile image
  • Gary Hawkes's profile image
  • Rahul Parwal's profile image
  • Jesse Berkeley's profile image
  • Tom Game's profile image
  • Jayanthi Vadivel's profile image
  • Joanna Negler's profile image
  • James Black's profile image
 Thank you to everyone who joined my AI masterclass yesterday!Loved the engagement, energy, and enthusiasm that you all brought.Of course, always grateful for the opportunities like these.Than...
How do we balance championing the Quality Assistance model with the reality that many early‑career quality engineers ... image
  • Jesse Berkeley's profile image
Interesting question from Jesse Berkeley on quality assistance model - https://www.ministryoftesting.com/moments/ama-about-transitioning-to-quality-assistance-modelI took a few days to think about ...
Sandbox image
  • Jesse Berkeley's profile image
A Sandbox is an isolated environment used to safely run, test, or experiment with software without affecting live systems, real users, or production data. It provides a controlled space where changes can be made, code can fail, and unexpected behaviour can be explored without risk outside the sandbox. For example, a team building an online checkout feature might use a sandbox version of their application to test new payment logic. In the sandbox, testers can create fake users, place dummy orders, and deliberately trigger errors like failed payments or timeouts without charging real customers or impacting the live website. Once the team is confident the change behaves as expected, it can then be safely promoted to production. 
Login or sign up to create your own MoT page.
Subscribe to our newsletter