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  3. Continuum
Anonymous builderabout 1 hour agoJudging locked: Event build

Continuum

Continuum is a long-running research agent that remembers its work, survives restarts, keeps contradictions visible, and refuses to state anything its memory can't support, for teams that need AI research they can audit.

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Project description
Agents break on long jobs: they forget, lose work in a crash, and invent answers when asked why. Continuum is a research agent built to stay reliable over hours. How it works: Nimble searches the live web and fetches full pages when snippets lack the value. Liquid AI's LFM2.5-2.6B, running locally via llama.cpp, extracts each value with an exact quote; ungrounded quotes are dropped. Deterministic code normalizes values (128K = 131,072), rejects off-type ones, and marks a claim supported only when two different websites agree. Real disagreements trigger a follow-up search; if one source explains the conflict, the claim becomes "qualified". Every step is stored append-only in RawTree (Tinybird): state checkpoints plus a flight log of searches, failures, retries and restarts. A crashed run resumes where it stopped and never blindly repeats a paid call. "Ask the memory" retrieves records from RawTree, lets Liquid phrase an answer, then checks every citation, number, URL, time and model attribution; wrong answers are withheld. Black Forest Labs FLUX produced the brief's artwork only (cover, emblems, clip), never data. Live result: 20 claims on five small models, 40 quotes from 18 sites, 9 sessions survived, a verified "why", and one answer caught blaming the wrong model.
Tools used
  • Codex
  • Liquid AI
  • Nimble
  • Tinybird
  • Black Forest Labs
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Project links
  • GitHub repository
  • Project website
Tools used
  • Codex
  • Liquid AI
  • Nimble
  • Tinybird
  • Black Forest Labs