Why we need "Structured Signals": No more writing custom parsers for every damn API.
Before we had a standard format, the developer experience was a total nightmare:
You hook up a GitHub webhook, you get GitHub’s JSON. You switch to Slack, it’s Slack’s JSON.
You plug in the Steam API, and it’s a whole different story. Every single data source requires its own parsing logic—different field names, messy nesting, and those annoying timestamp formats.
But here’s the real kicker: feeding raw JSON directly to an AI agent is incredibly inefficient. You end up building a "translation layer" for every source just to turn raw data into readable context.
3 sources? 3 layers.
10 sources? 10 layers.
And if you switch your agent framework? Good luck rewriting everything from scratch.
W2A’s Structured Signals fix this by ensuring every source spits out the same format. The game-changer is the event.summary field—every signal must include a natural language summary. This allows the agent to "triage" information by reading just one field.
No more per-source parsers, no more framework lock-in, and you can mix and match sensors however you want.
TL;DR: Structured signals turn sensors into plug-and-play components. Without them, every sensor is just another one-off, custom engineering headache.