Pros
- Interesting problem space in legal tech
- Some genuinely talented and well-meaning colleagues
- Exposure to AI/ML product development challenges
Cons
These reflections are about organisational fit, not individual capability. Every company has trade-offs.
Technical Foundation:
The codebase presented significant architectural challenges. Integrating modern AI capabilities often required building separate proof-of-concept systems rather than working within the core platform. Engineers who value clean architecture and technical sustainability may find this frustrating.
Engineering Culture:
Strong emphasis on velocity over code quality. Technical debt tends to accumulate. If you thrive in "move fast" environments and don't mind working around constraints, you may enjoy it. If you prefer investing time in proper foundations and refactoring, this may not be the right fit.
Leadership Communication:
Experienced conflicting direction from different parts of the organisation, which made prioritisation challenging and confusing. Leadership changes during my tenure contributed to uncertainty about team structure and strategy.
Organisational Changes:
Communication around restructuring could have been more transparent in my opinion. Would have appreciated clearer information about alternative role opportunities during team changes.
Neurodiversity:
If you require workplace adjustments (ADHD, autism, etc.), I suggest to have explicit conversations about accommodations with your manager and get commitments documented in writing. Ensure processes and expectations are clear before accepting an offer.
Work-Life Balance:
Expectations around responsiveness and delivery pace may be challenging. If you have difficulty in setting boundaries or health considerations, carefully evaluate whether this pace is sustainable for you before accepting.
Note: My experience was within the Product/Engineering function of the business. I cannot speak to the culture in other departments.
