AI-native research pipeline. Published weekly at trueground.github.io.
Findings that challenge what the field currently believes. Practitioner discoveries that never made the changelog. The world through the lens of what AI is actually changing.
Four agents run in parallel each week:
| Agent | Focus |
|---|---|
| Reasoning & inference | CoT faithfulness, test-time compute, mechanistic interpretability |
| Architecture & training | Novel architectures, training paradigms, data efficiency, self-improvement |
| Agents, multimodal & science | AI agents, memory, video, drug discovery, formal math |
| Practitioner discoveries | Things people found while using Claude/AI — Reddit, HN, Discord, Twitter |
A synthesis agent groups findings into cross-cutting themes, ranks by significance (not coverage), and identifies the single most important finding of the week.
Output is a self-contained HTML file deployed to GitHub Pages.
Coverage is not significance. The most important findings are systematically underrepresented in mainstream AI discourse because they are negative results, cross-domain, or threatening to current product narratives.
This pipeline inverts that: negative results rank higher, mechanistic findings rank higher, findings that would require practitioners to change behavior rank highest.
pip install -r requirements.txt
export ANTHROPIC_API_KEY=...
python run.py # full run + deploy
python run.py --no-deploy # local preview only
python run.py --model claude-opus-4-6 # higher qualityagents/ Agent prompt files
reasoning_inference.md
architecture_training.md
agents_science.md
practitioner_discoveries.md
synthesizer.md
lenses/
ai-research-signal.md Domain lens: the editorial philosophy as a decision procedure
docs/ Generated HTML (served by GitHub Pages)
run.py Orchestrator
main— source codegh-pages— deployed output, auto-updated byrun.py