Show HN: It Happened Again – Track recurring events with evidence(ithappenedagain.fyi)
ithappenedagain.fyi
Show HN: It Happened Again – Track recurring events with evidence
https://ithappenedagain.fyi
1 comments
A few examples on how IHA works in practice:
Major cloud service outages: https://ithappenedagain.fyi/rec/another-major-cloud-service-...
New SOTA model released: https://ithappenedagain.fyi/rec/new-sota-model-released-2116...
Or something different, like countries withdrawing from EuroVision: https://ithappenedagain.fyi/rec/another-country-withdraws-fr...
I’m just curious whether people here would use something like this for tech incidents, politics, or maybe something else entirely.
Major cloud service outages: https://ithappenedagain.fyi/rec/another-major-cloud-service-...
New SOTA model released: https://ithappenedagain.fyi/rec/new-sota-model-released-2116...
Or something different, like countries withdrawing from EuroVision: https://ithappenedagain.fyi/rec/another-country-withdraws-fr...
I’m just curious whether people here would use something like this for tech incidents, politics, or maybe something else entirely.
I’m Robert, the developer behind It Happened Again (https://ithappenedagain.fyi).
Let’s start with an example: "AWS us-east-1 outage": A structured timeline of every outage since 2017, with sources, verification, and a "live days since last incident" counter.
The Problem
I built this after realizing I had personally argued about the same repeating topics like SaaS outages, breaking changes, and AI claims multiple times, with no shared reference to point to.
Social media feeds are built on recency. They do not have any long-term memory. When a provider has its 5th outage of the year, that context is buried under new content. To stay updated, you have to constantly refresh, which generates high noise and low signal.
What it does
IHA lets you create a single, shared timeline for things that keep happening - outages, broken promises, policy reversals - and attach evidence each time they recur.
You can think of it like Imgur was for Reddit, but for context instead of images. You create a Record (the pattern) and add Occurrences (each time it happens) to provide chronological evidence.
Key Features
- Structured Timelines: A strict chronological record of recurring events (e.g., "Steam Deck on sale", "Feature X promised but not delivered").
- Active Monitoring: Subscribe to specific Records. Instead of refreshing a feed, you get notified (in-app or email digest) only when "it happens again."
- Privacy First: No tracking pixels, no data selling. Analytics via anonymized Posthog (EU Cloud).
Weighted Verification (An Experiment)
We intentionally started with a simple, transparent scoring model (implemented in our Verification Service) so the community can ‘attack it’ and help us improve it. We don't use black-box AI to try to determine truth.
Current Weights (launch version):
- Moderators: 3x multiplier
- Trusted Contributors: 2x multiplier
- Account Age: up to +20% boost
- Evidence Quality: Currently +5% per link. (Yes, we know this linear scaling is naive - we are specifically looking for feedback on better distinct-domain heuristics!)
Under the Hood
IHA was developed over the last 12 months using a Modular Monolith architecture to keep the codebase sane:
1. Stack: Next.js 15, Drizzle ORM, Postgres, Redis, BullMQ.
2. Service Layer: We use a Service Registry pattern to isolate business logic (like verification rules) from the web layer, ensuring the "truth logic" is testable.
3. Infrastructure: EU-based. Hetzner (App/DB), Posthog (Analytics), Backblaze B2 (Storage).
Common Questions
Wait, "AI" helped you build it, but does it "run it"?
No. LLMs are not used to verify submitted information. AI (Claude/Codex/Gemini) acted as a force multiplier to write the code, but the logic is deterministic and always reviewed by a human.
How do you prevent brigading or misinformation?
We use a two-tier moderation system (Local Moderators assigned by the Record's creator/owner, similar to subreddits, alongside Global Moderators’ oversight) and a "Trusted Contributor" reputation system to weight verification scores.
Why I built it
I started this as a way to stop re-litigating the same facts in comment threads - as much for myself as for everyone liking evidence-based data. The goal isn't to replace social networks, but to build the "memory layer" that they lack - effectively bringing OSINT-style tracking to everyday recurring events (and, hopefully, making it fun).
The app is live here: https://ithappenedagain.fyi
I’m specifically looking for feedback on how you would game or attack the verification model - assume bad actors and incentives.
Thanks!