How to design a system that keeps serving when its parts fail — the vocabulary of availability, the patterns that contain failure, and the Go primitives that make retries, limits, and fallbacks safe rather than dangerous.
Designing systems that survive failure: the nines and SLI/SLO/error budgets, eliminating single points of failure, timeouts and retries with backoff+jitter made safe by idempotency, circuit breakers, rate limiting and load shedding, and graceful degradation.
Anyone can stay motivated when things are going well. The test — and the skill — is what happens when the project stalls, the code won't work, the feedback stings, or the effort drags on with no payoff in sight. Motivation and resilience are the emotional-intelligence skills of managing your own drive and bouncing back from setbacks, and they're what turn talent into sustained achievement. Without them, ability leaks away in the face of the frustration and failure that all real work involves.
Anyone can stay motivated when things are going well. The test — and the skill — is what happens when the project stalls, the code won't work, or the feedback stings. Motivation and resilience are the EQ skills of managing your own drive and bouncing back, turning talent into sustained achievement.
The network will time out mid-transfer. The only safe assumption is that every request runs zero, one, or many times — so make "many" behave like "one."
The network times out ambiguously, so every request runs zero, one, or many times. Idempotency keys make many behave like one; full resumability lets a crashed money flow resume from its last committed step.
Fallback agents plus a CI step that replaces the primary agent with one that always errors. If the fallback doesn't produce a usable answer, the PR can't merge.