Minimum required pacing: finish aligning it before you train the next one

On the AI Alignment Forum, an author writing as orthonormal proposes a minimum pacing rule: a lab may not train its next, more capable generation of models until significant alignment problems in the current one are adequately resolved, as judged by several independent alignment organizations. The author calls it a vague heuristic, not a concrete proposal, and lists open questions.

Why it matters

The same thing, for different readers.

What it means for you

The idea is simple: an AI company should fix the problems in today's AI before building a more powerful one, and outside experts should check that it did.

For lawmakers

Sketches a trigger for coordinated slowdowns: training the next generation waits on independent sign-off, restricted deployment first, and pulling a model when a significant problem appears.

For researchers

Frames a gate that both optimists and pessimists about current alignment methods could accept, and leaves open what counts as a model generation or a significant issue.

The question it raises

Who should decide when an AI is aligned enough, and should progress wait for that judgement?

In their own words

Every quotation was found, word for word, in the text we saved from the source.

From the source’s own text.

“My proposal for a minimum requirement: a lab cannot train the next generation of models (in terms of capabilities) until they have adequately… resolved all significant alignment issues in the present generation of models.”
orthonormalThe post's core proposal, in its opening lines; the "…" replaces only a footnote marker.
Matches the source exactly
“Multiple independent alignment organizations examine and red-team the newest model at many checkpoints throughout training, with full access to the data and with the best tools available.”
orthonormalThe first step of the author's 'vague, qualitative' process for judging whether alignment issues are adequately resolved.
Matches the source exactly
“And it creates much better incentives for labs: in order to advance in capabilities, they'd have to push the frontier on alignment and interpretability techniques.”
orthonormalThe author's argument for why the rule would change labs' incentives.
Matches the source exactly
“I still wouldn't say that this is fully adequate, but I'd treat it as a minimum requirement.”
orthonormalThe author's own verdict after laying out the deployment and reset steps.
Matches the source exactly
“Hardware/economics/industry will already be coincidentally pacing the scaling, starting pretty much right now, for reasons unrelated to (the risk of) AI incidents.”
Vladimir NesovA reader comment under the post, replying when the author asked what the commenter's scaling predictions imply for the proposal.
Matches the source exactly

The record

Questions
Who can demand evidence, delay a release or stop an unsafe deployment? · Are AI companies putting stronger safeguards into practice?
People
orthonormal (Wrote it) · Vladimir Nesov (Speaks)
What we read
We read the whole source.
Found by
The Radar, run of October 12, 2026, via ai-alignment-forum (tier 1: the source’s own channel or an official record)
Cite this
AI Alignment Forum, “Minimum required pacing: finish aligning it before you train the next one”, October 11, 2026. Entry in the Ctrl AI Base, https://ctrlai.com/base/alignmentforum-2026-10-11-finish-aligning-before-next-model
Our notesForum post, not peer reviewed. The author writes under the pseudonym orthonormal; no real name or affiliation is given in the source. The commenter appears as the username Vladimir_Nesov; the name 'Vladimir Nesov' is derived from that username, no title given. The comment also argues that scaling will slow by itself and that Meta, Google and SpaceX could catch up with OpenAI and Anthropic in 2027; these are the commenter's predictions, not facts. In quote 1 the '…' stands in for a footnote marker [1], not for any words. At fetch time the post showed 13 points and 3 comments.