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Earlier today, @the_prion asked me what the hardest part about starting @AkitaSoftware was.
My answer: figuring out how to build a team that balances user-focused product thinking with the deep technical expertise required to power it (in our case).
Thread. 🧵
My answer: figuring out how to build a team that balances user-focused product thinking with the deep technical expertise required to power it (in our case).
Thread. 🧵
@the_prion @AkitaSoftware At Akita, we're making it easier to detect the API regressions that matter. We want to do this as non-invasively as possible, with the highest information content possible.
This means keeping code changes/perf overhead as minimal as possible, while keeping false positives low.
This means keeping code changes/perf overhead as minimal as possible, while keeping false positives low.
@the_prion @AkitaSoftware Keeping code changes and perf overhead as low as possible is not easy, and constantly requires balancing software architecture decisions with user-facing tradeoffs.
Keeping false positives low is also a really hard trace analysis problem that also has many user-facing tradeoffs.
Keeping false positives low is also a really hard trace analysis problem that also has many user-facing tradeoffs.
