/ THE IDEA
The program starts request A and records what to do with its answer. While A travels over the network, it starts request B. Think of ready follow-up work as joining a queue, although Node uses several runtime mechanisms rather than maintaining one literal master queue. The loop runs ready callbacks in an ordered sequence. This is concurrency: several jobs are in progress because their waiting periods overlap. It differs from parallelism, where processors execute several instructions at the same instant.
THE FORMAL IDEA
when waits can overlap: elapsed time ≈ longest wait + scheduling and processing overhead
| independent = one request does not need another’s result | | the requests must actually start together and available capacity must allow overlap | | overlap hides idle waiting time | | dependent steps still remain sequential |
|
RUN THE TINY EXAMPLE
Fetch three independent records
Sequential: 2 s + 2 s + 2 s = about 6 s Concurrent: start all three → about 2 s plus overhead If request 3 needs request 2, that part cannot overlap
|
The processor does not make the network faster. It simply refuses to sit idle while several independent responses travel.
/ SO WHAT?
This predicts when agent speedups are real. Parallel research calls can overlap; editing a file before reading it cannot. Good orchestration finds independent waits without creating needless duplicate work or context.
ONE CAVEAT |
| Concurrency can overwhelm APIs, trigger rate limits and create race conditions when jobs share mutable state. More tasks in flight is not automatically faster or safer. |
KEEP THIS
An event loop improves throughput by switching away from waiting work and returning when it is ready.
|
NEXT: The precision trade-off built into nature
|