LabOS
LabOS is a small research lab where the researchers are AI agents. I supply the ideas and make the calls; agents do the reading, coding, and experiments. Negative results included.
For empirical pieces, the date is the last day of substantive research, not a later copy edit.
How the lab works: AI agents as the researchers
One person with a lot of ideas, AI agents as the research staff. How the lab runs many threads in parallel, keeps its memory in files, and kills most ideas cheaply.
Read the article →Findings
The query decides whether a repaired KV cache is safe
Splice a re-encoded edit into a stale KV cache and only the states after the edit stay wrong. That drift never flipped an unrelated query — 0/252 in each of two studies — but flipped a third of the queries that read the edit. A probe can rank the failures; compute and calibration kept it from becoming a method.
Prediction depth is a property of the ruler, not just the model
A translator-free lens for the layer where a transformer settles each token: keep the MLPs, silence the attention. It passed a three-family validation and out-tracked the tuned lens on GPT-2 — and then showed that swapping zeros for means flips verdicts, findings, and the sign of one result.
Does model editing store facts, or just answers?
A ladder of progressively stronger fact-free controls for knowledge editing. ROME nearly dissolves, SAKE dissolves at the first rung, REMEDI keeps a real residual.
Does a transformer snap between modes of computation?
The hope: discrete computational regimes you could read off a layer’s Jacobian. I preregistered the test and ran it — across 270 configurations, zero beat a plain continuous predictor.
Every importance gate is a Bayesian prior in disguise
I tried to beat uniform training by gating learning strength on input importance. What came back was an identity, not a method — and it lets you call the winner before running anything.
Auditing activation steering: how much is just pushing on the output?
For ActAdd, a static logit bias reproduces 96% of the steering effect — even though the steering vector is nearly orthogonal to the unembedding. Six methods audited.
Methods & process
In progress
Live in the lab, not written up here yet — either too early, or the interesting parts stay private for now.