ChronoScholar is a temporally-aware research memory agent that ingests arXiv papers into a Cognee knowledge graph and detects when stored scientific beliefs are contradicted by incoming literature. Built for the WeMakeDevs ...
The thing that finally broke me wasn't my agent forgetting stuff. Forgetting is
annoying but it announces itself the agent asks again, you sigh, you re-explain.
What broke me was the silent version: my agent confidently re-proposed an
approach we'd tried and abandoned a month earlier. Another time it planned
against a decision we'd replaced two week...
I still remember the first time I opened a legacy payment module and saw a monster‑sized if/else chain stretching over a hundred lines. Each new payment method meant another branch, another copy‑paste of validation logic, and a prayer that I hadn’t missed a case. One Friday night, after deploying a tiny tweak that somehow broke Apple...
Hi everyone! 👋
I'm Amit Gupta, a Mobile Engineer with 10+ years of experience building Android, iOS, Flutter, and React Native applications.
Over the years, I've worked on production-scale mobile SDKs, push notification systems, APIs, app monetization, and applications used by thousands of users.
Recently, I've started exploring a new direction—combining mobile developm...
TL;DR — Your agent's memory is production infrastructure with no tests, no diff, no rollback. SOBER is a
b...
Problem: Current LLM agent frameworks treat the chat history as the single source of truth for state. This is architecturally equivalent to a kernel persisting its state only through stdin/stdout logs. It works temporarily, but predictably fails under load.
Three measurable failure modes: