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Distributed energy management at scale requires a holistic approach.
Mission: Real-time platform processing gigabytes/sec across thousands of electrical grid assets for sustainable power
Fix:
→ Embedded partnership
→ Elixir/Elm expertise
→ Distributed, fault-tolerant architecture
→ Automated testing frameworks
→ Team mentoring & process improvement
Results:
→ Massive scale
→ Market leadership position
→ Successful acquisition by Generac
Staff Consultant Brian Hughes shares an 80/20 rule for test coverage in your software application, along with practical tips.
🔧 Legacy code: rewrite or refactor?
Key factors:
- Security risks?
- Framework support?
- Team understanding of features/usage?
- Risk tolerance?
- Team's ability to maintain existing vs new system?
Pro tip: There is no magic answer. It's always situational.
We've seen incremental refactors that unlocked business value and speed super quick, and also glacially slow refactors.
We've seen big bang rewrites turn into snail's-pace, expensive disasters, and also super successful iterations.
Remote work reality check: Scheduled meetings build efficiency. Unstructured time builds trust.
Our consultant Tyler Sloane discovered that "coffee and code" sessions - open video calls with no agenda - create the serendipitous connections that make remote teams actually work.
His approach for virtual relationship building: https://link.testdouble.com/e704e9
Slow investigations, inconclusive root causes, and recurring bugs are observability problems. But fixing them isn't primarily a tooling problem.
Gabriel Côté-Carrier spent months turning observability from a team pain point into a genuine advantage. The technical work was only half of it.
"In a world where every meeting has an agenda, sometimes the most valuable thing we can offer is purposeless presence."
Tyler Sloane's take on building real connections in remote work is worth the read: https://link.testdouble.com/e704e9
Python devs, is this familiar: Your team writes beautiful snake_case code, but every external API wants camelCase.
You could:
- Pollute your codebase with non-Pythonic naming
- Write manual conversion layers
- Live with the friction
Or you could use Pydantic's field aliases to solve this once and for all.
New guide: How to handle non-Pythonic naming conventions seamlessly 👇
https://link.testdouble.com/e357d1
AI can pattern-match. It can’t always tell you when the pattern doesn't apply ... because it doesn’t always have (and sometimes loses) context.
Senior engineers and product managers who've shipped real products, untangled real legacy systems, and made real calls under pressure bring something different to the table.
Test Double's free office hours give you access to exactly that. No strings attached.
We can help you discern when patterns actually apply.