The open calls

Eleven calls on the classification model that only you can make

How to answer this page. Every decision below ends with its own answer line. Reply in chat, one line per decision, in any order: ID: CONFIRM · ID: CHANGE: what you would change · ID: LEAVE OPEN: what you still need to see — plus anything else you want on the record. Every number on this page was read from the database on 2026-08-25; the queries are stored beside the values.

A-02The eight open calls on the classification page · short

Eight numbered calls are sitting on the classification page waiting for a pick each — do you walk that page this round, or defer it to the next sitting?

A beat is one moment inside a video — the two seconds where a hand picks up a phone — and when the machine watches a film it describes it beat by beat, one moment at a time; eight numbered calls about how those descriptions are organised sit on the classification page with their evidence already beside them, and exactly one of the eight is structural while the other seven are smaller repairs.

The structural one is a group called Shot Types, which holds two shelves — a shelf is simply a group you browse a list of words by — whose words the separate question about how a beat was filmed offers all over again, so the same fact gets written twice about films like the Commonwealth Bank case-study video below, which carries 31 described beats of its own; the seven smaller ones are these: one phrase used as the name of two different questions, four words that name a brand's campaign subject rather than a kind of beat (tennis challenge is the clearest), a group with nothing under it, a pricing answer stranded where nothing can reach it, three pairs that say the same thing twice, three beat words that repeat what the how-was-it-filmed question already answers, and words deliberately shared across two questions.

None of the eight changes anything by being written down, so the only thing this card asks is when you walk that page — this round, or explicitly at the next sitting.

My take: Walk it this round. It is the page where a wrong shape keeps costing us: every beat the machine files under a grouping you are going to dissolve is a beat somebody has to re-file later.

Commonwealth Bank set out to make AI a core capability at Australia's largest bank.
OpenAI · LinkedIn ad library · 2026-06-12 · written on it: case study video · source
Every enterprise deal comes with contracts full of details: start dates, billing terms, renewals — capturing that quickly and consistently is critical.
OpenAI · LinkedIn ad library · 2026-06-12 · written on it: case study video · source

What changes

If you walk it, eight picks land on that page and everything after them is engineering, not writing.

What stays exactly as it is

Every beat already described stays exactly as described. Not one of the eight calls changes a word written on a piece or a beat by being marked.

Beats in the library carrying a description today3,355
Different words the machine has invented for a kind of beat577

Where this was worked out: the classification page, where the eight calls live with their evidence in place

A-02: answer in chat with one line — A-02: CONFIRM · A-02: CHANGE: what you would change · A-02: LEAVE OPEN: what you still need to see

A-03The first promotion round for beat words · short

Do you walk the promotion list this round — the page where a line you leave standing executes as written — or defer it?

Underneath the beat shelves the machine is allowed to invent its own words for what a beat is, and it has invented 577 of them: 379 were used exactly once and nobody will ever read those, while 64 have been used five times or more and are real working vocabulary — Talking Head, UI Walkthrough, Logo Animation.

The list gives each of those 64 a written definition, folds each one's near-spellings into it line by line, and works by striking, so a line you leave standing executes as written; for scale, the Commonwealth Bank case-study video below carries 31 described beats of its own, one of them named “OpenAI & Commonwealth Bank Title Card”.

The 64 here is a coincidence and has nothing to do with your 64 approved labels for whole pieces — a label being the one word on a piece that says what kind of thing it is; these are beats inside a video.

My take: Walk it. The tail is the argument: 379 words used exactly once is what an open list looks like when nobody prunes it, and the pruning only gets more expensive as the library grows.

Commonwealth Bank set out to make AI a core capability at Australia's largest bank.
OpenAI · LinkedIn ad library · 2026-06-12 · written on it: case study video · source
Our holiday gift to you: Sora is here — generate entirely new videos from text, bring images to life, or extend, remix, or blend videos you already have.
OpenAI · TikTok · 2026-06-17 · written on it: product demo · source

What changes

The 64 words above the floor get written definitions and become the settled vocabulary underneath the shelves; each one's near-spellings fold into it in the same pass.

What stays exactly as it is

The level stays open underneath, so a genuinely new technique can still be named by the machine and reviewed later.

No described beat loses a read, and nothing written on a whole piece is involved.

Different words invented for a kind of beat577
Of those, used exactly once379
Of those, used five times or more — the ones this list promotes64
Beats in the library carrying a description today3,355

Left off this page on purpose: “76 near-spellings fold into the promoted words” — that figure was worked out on the promotion list page itself, by reading the words spelling by spelling and naming a survivor for each. It is not a number the database can be asked for, the way every count on this page can, so it is left off rather than printed on the same footing. The folds themselves are all still on that page, line by line, with the survivor named, for you to strike.

Where this was worked out: the promotion list — the detailed record behind the moments part of the classification page

A-03: answer in chat with one line — A-03: CONFIRM · A-03: CHANGE: what you would change · A-03: LEAVE OPEN: what you still need to see

A-04The eight further proposals on the same page · short

The same page carries eight standing proposals that run unless you strike them — do you let them stand?

These are the ones you have mostly already ruled, gathered so you can see what you would be letting stand: the two family names — the groups the database files the labels under today — still stored in their old spellings get the words you picked, the what-is-it-about question splits the way you ruled, the one shelf that sits inside another is pulled out beside it, the three typography sub-kinds you named are drawn in (full-screen titles, pricing end cards, opening titles), the three-way ranking every shelf carries today is replaced by one plain mark on each saying whether it is a shelf you browse by or one that only holds the record, two beat words that only repeat the name of their own shelf retire, one kind-of-thing value that nothing uses retires, and occasion — the yearly event or season a brand aims itself at, such as back-to-school, the holidays, or a sporting final — finally gets somewhere in storage to be written down, having been ruled a real thing in its own right while having nowhere at all to live.

One of them matters more than its position on the list suggests: the stored word list still reads “Proof & Advocacy” where you chose Social proof, so every surface built from that list — including the shelf the Commonwealth Bank case-study video would sit on — is still showing a name you rejected.

The typography ones are the visible half of the set, and the contracts film below is where you meet them: its own “OpenAI on OpenAI title card” beat is exactly the full-screen-title kind the split names.

My take: Let them stand, but read the name change twice before you do. It is the only one on the list that touches a word you already picked, and a name you rejected has been sitting in storage for a fortnight.

Commonwealth Bank set out to make AI a core capability at Australia's largest bank.
OpenAI · LinkedIn ad library · 2026-06-12 · written on it: case study video · source
Every enterprise deal comes with contracts full of details: start dates, billing terms, renewals — capturing that quickly and consistently is critical.
OpenAI · LinkedIn ad library · 2026-06-12 · written on it: case study video · source

What changes

Eight small changes run in the engineering lane, each one already argued on the page it lives on.

What stays exactly as it is

Nothing in the library moves. Renaming a stored word changes what a person reads, never which pieces sit under it.

Words a piece can be labelled with, on file today74
Of those, in active use53
Of those, sitting on a named shelf52

Where this was worked out: the classification page — its standing proposals, which work by strike-or-let-stand

A-04: answer in chat with one line — A-04: CONFIRM · A-04: CHANGE: what you would change · A-04: LEAVE OPEN: what you still need to see

A-05The two questions about the product that turned out to be one · full

Every described beat answers two questions about the product — how visible it is, and what part it plays — do we merge them into one?

What do we write about the product on every beat today?Two answers: how visible the product is, and what part it plays in the beat.
Why is that a problem?Five of the eight answers the machine gives to “how visible is it” are really answers to the other question. They sit on 1,613 beats.
How much of the visibility question is genuinely its own?Three words — shown on screen, on a device, in hand — carrying 1,403 beats.
What would change on a beat already described?Nothing a reader would notice: every stored beat maps across word for word, and no film is watched again.
What is the recommendation?One question — what part the product plays — keeping the three genuinely visual words as answers on it.

When the machine watches a film it does not only say what the film is; it walks through it beat by beat — one moment at a time, the two seconds where a hand picks up a phone. On each beat it answers a short list of questions, and two of them are about the product: how visible is it, and what part does it play?

Those two were written down as if they were different questions, and only three of the visibility answers ever really were: shown on screen (965 beats), on a device (351), in hand (87). The other five — absent (1,064), implied (311), contextual (122), in active use (73) and focal (43) — are the other question's own words, and the machine has been giving them as visibility answers anyway. That is 1,613 beats answering a question they were not asked, against 1,403 answering the one they were.

An earlier version of this decision put the drift at 238 beats against 438, and it was wrong. That reading counted only three of the crossed words and left shown-on-screen out of the comparison — a word the recommendation itself keeps — so both halves were understated. Re-read on 24 August it is five of eight, 1,613 against 1,403: a stronger case for merging than the card first made, which is why the correction is printed here rather than quietly applied.

The two Sora pieces below are the whole argument at reading size. In the holiday release demo the interface is on screen and the product is also what the beat is about — one answer covers both readings, and writing two is writing the same thing twice. In the scuba-diver clip there is no product on screen at all, so today the machine answers “how visible is it” with the word absent — a word that only ever belonged to the other question. Merging is not a new idea being imposed on the data; it is writing down what the data has already been doing for months.

What you would be left with is one question — what part does the product play in this beat — whose answers include the three that are genuinely about visibility. Every beat already described keeps its answer, because every word survives the merge; the machine gets told the new shape once, and the browsing filters lose a line.

My take: Merge them. Two questions that share five of their eight answers are one question wearing two hats, and the only thing keeping them apart is that somebody once wrote them down as two.

Our holiday gift to you: Sora is here — generate entirely new videos from text, bring images to life, or extend, remix, or blend videos you already have.
OpenAI · TikTok · 2026-06-17 · written on it: product demo · source
Saturdays are for the new Sora drops — text-to-video generations, without modification: a scuba diver discovers a hidden futuristic shipwreck.
OpenAI · TikTok · 2026-06-17 · written on it: social clip · source
Every sales team has account notes, call transcripts, CRM fields, and research scattered everywhere — the hard part is turning that into a clear next move.
OpenAI · LinkedIn ad library · 2026-07-06 · written on it: product demo · source

What changes

One question instead of two, keeping shown on screen, on a device and in hand as answers on the survivor.

The machine is told the new shape once, and the stored beats map across word for word — 1,613 of them are already using words that survive.

What stays exactly as it is

No film is watched again and no beat is re-read. The Sora demo above is a product demo before and after, and its beats keep every other read they carry.

The 339 beats where that question was never answered at all stay blank — merging does not invent an answer where none was given.

Beats where the product is written as absent1,064
Beats where it is written as shown on screen965
Beats where it is written as on a device351
Beats where it is written as implied311
Beats where it is written as contextual122
Beats where it is written as in hand87
Beats where it is written as in active use73
Beats where it is written as focal43
Beats using a word that belongs to the other question1,613
Beats using one of the three words genuinely about visibility1,403
Beats where that question was never answered at all339
What the earlier, narrower reading counted as crossed238
What that same reading compared it against438

What this call does to everything else written on these pieces

This reaches no further than the beat. What is written on the whole piece — its one label, where it ran, who appears in it, which campaign it belongs to — is not touched, and neither are the crafts credited on it: the Codex sales film above still reads Logo Design, UI Design and Motion Graphics whichever way you rule. Inside the beat, the merged question sits beside three others — what is literally on screen, what the beat does for the story, and how it was filmed — and it shares no word with any of them, so nothing else has to move to make room. The only surface a person would notice is the filter list you browse beats by: one line disappears and three answers join another. And it makes one repair possible that is impossible today, because once the words live on one question the machine can no longer write a role word where a visibility word belongs.

The alternative, and its cost: Keep the two questions and write one sentence each saying what only that one answers. The cost is that the sentence has to hold a line the machine has already crossed 1,613 times without being told to — so you would be buying a check that catches the drift after it happens, every time, instead of a shape that cannot drift.

Where this was worked out: the review agenda, item 5 — raised while reading the live system on 11 August, with the full distribution re-read on 24 August

A-05: answer in chat with one line — A-05: CONFIRM · A-05: CHANGE: what you would change · A-05: LEAVE OPEN: what you still need to see

A-06The three things we write on every beat that no list governs · full

Three things get written on every described beat with no agreed list of words behind them — do we govern two of them and harvest the third?

Which three?What kind of interest a beat holds, whether anything is moving, and what the scene looks like.
Who decides the words?Nothing does. No list, no definitions, no check — the machine invents each word as it goes.
What has that produced?17 interest words, 5 motion words, and 550 free-text phrases for the look of the scene.
What is the tell that this is a real problem?One word, kinetic type, is being written as an answer to two of the three questions at once.
What is the recommendation?Govern the first two with written definitions; leave the look of the scene open and promote the phrases that keep recurring — the loop you already ruled.

Beside the big questions, every described beat carries a handful of small ones: is this beat interesting because of the craft, the data, or something the product does; is anything moving; what does the room look like. Three of those small reads have no agreed list of words at all — nothing says which words are allowed, nothing defines them, and nothing rejects a new one on the way in.

Left to itself the machine still produced something that looks like real vocabulary: 17 interest words — brand lore, category signal, craft detail, data proof, data visualisation, ecosystem, identity update, interaction detail, kinetic type, lifestyle, lifestyle detail, micro detail, new release, none, product behavior, interface detail, visual motif — and 5 motion words. That is genuinely the good news, and it is the argument for keeping an open level at all: an open list is how a technique nobody has named yet gets a name.

Here is the bad news, and it is one word. Kinetic type is written as an interest word on 8 beats and as a motion word on 2 others — the same word answering two different questions, which is exactly the drift a written list exists to prevent and exactly the kind of thing nobody catches by reading. It is small today because the numbers are small. It is not small in a library ten times this size.

The look of the scene is a different animal: 550 free-text phrases, of which the eight most common are technical/UI (461), clean UI (247), modern office (166), casual office (108), minimal clean (82), minimal UI (72), office interview (69), minimal studio (57). Read that list and the clustering is obvious — offices, interfaces, minimalism — which is the argument for not governing it yet. It goes through the harvest-then-promote loop you already ruled for beat details: let the words come in freely, and on a schedule promote the ones that keep coming back, with definitions.

The Commonwealth Bank case-study film below is where all three land at once. It carries 31 described beats, and every single one of them got an interest word, a motion word and a phrase for the look written on it by a machine with no list to check any of them against. Nothing about that film is wrong today; it is simply unverifiable, and that is the condition this decision ends.

My take: Govern the first two and harvest the third. The word sitting on two lists at once is not a tidiness complaint — it is a defect that keeps being written, every day nobody rules on it, because the words are still on both lists.

Commonwealth Bank set out to make AI a core capability at Australia's largest bank.
OpenAI · LinkedIn ad library · 2026-06-12 · written on it: case study video · source
Wait for it — Sora can be prompted with text, images, or video inputs, and can interpolate between two input videos for seamless transitions.
OpenAI · TikTok · 2026-06-17 · written on it: social clip · source
Our holiday gift to you: Sora is here — generate entirely new videos from text, bring images to life, or extend, remix, or blend videos you already have.
OpenAI · TikTok · 2026-06-17 · written on it: product demo · source

What changes

Two agreed lists get written, one definition per word, and the machine is told to use them and nothing else.

The look of the scene stays open and comes back later as a short promotion round, exactly the way the beat words are coming back now.

What stays exactly as it is

All 3,355 described beats keep every read they already carry. Writing a list down does not erase anything already read.

The big questions on a beat — where it files, what is on screen, what it does for the story, how it was filmed — are untouched.

Beats in the library carrying a description today3,355
Different interest words in use17
Different motion words in use5
Different free-text phrases for the look of the scene550
Beats calling kinetic type an interest word8
Beats calling the same word a motion word2

What this call does to everything else written on these pieces

These three reads sit at the beat level and today nothing hangs off them: no label on a whole piece is worked out from them, no shelf is built on them, and no campaign, product or company fact depends on them. So governing them breaks nothing — what it changes is what a person can do with them. An interest word becomes something you can browse and filter by rather than a word that happens to be sitting on the beat, and the two readings of kinetic type can be told apart on purpose instead of by accident. The phrases for the look of the scene stay exactly where they are until a promotion round moves them, so nothing on the Sora pieces above changes on the day you confirm; when that round comes, it will look like the beat-word round earlier on this page.

The alternative, and its cost: Stop writing the three reads altogether. It is honest and it is cheap, and it throws away the only evidence we have of what a beat is interesting for — including the 550 phrases that are the raw material for a shelf of scene types nobody has built yet.

Where this was worked out: the review agenda, item 6 — raised on 11 August, with every word re-read on 18 August and again today

A-06: answer in chat with one line — A-06: CONFIRM · A-06: CHANGE: what you would change · A-06: LEAVE OPEN: what you still need to see

A-07Where a product lives — one thing, two homes · short

A product lives in two connected places at once — do you confirm that the smaller of the two is the detail layer beneath the other?

A product shows up twice in the live system: 394 things inside their companies have been marked as product lines — Sora and Codex among them, the two products named on the pieces below — and a separate list holds 139 products, every single one of them tied back to the company that owns it, and each able to carry its own identity, its parent product and its launch date.

Nothing is lost between the two and nothing is duplicated, so the natural reading is that the smaller list is the detail layer beneath the larger one; this card exists so that you say so, rather than so that I assume it.

The one thing that reading does not settle is which of the two a person browsing should meet first, and that is worth a sentence from you while you are here.

My take: Confirm it, and lead with the product lines inside the company. This item is not a defect — two homes, both populated, nothing missing — so the only real choice left is which door a person walks through.

Every sales team has account notes, call transcripts, CRM fields, and research scattered everywhere — the hard part is turning that into a clear next move.
OpenAI · LinkedIn ad library · 2026-07-06 · written on it: product demo · source
Our holiday gift to you: Sora is here — generate entirely new videos from text, bring images to life, or extend, remix, or blend videos you already have.
OpenAI · TikTok · 2026-06-17 · written on it: product demo · source

What changes

One sentence on the Products page of this site — the page that explains what a product is — saying the products list is the detail layer, and a second saying which home a browsing surface leads with.

What stays exactly as it is

Nothing in storage moves at all.

Both homes keep everything they hold, and the Codex sales film above keeps both of its product links exactly as they read today.

Things marked as a product line, counting every one ever written394
Of those, still live today — three have since been removed391
Products on the separate list139
Of those, linked back to the company that owns them139

Where this was worked out: the review agenda, item 7 — raised while reading the live system on 11 August, re-read on 17 August and again today

A-07: answer in chat with one line — A-07: CONFIRM · A-07: CHANGE: what you would change · A-07: LEAVE OPEN: what you still need to see

A-08The middle level of the services tree · short

The middle level of the services tree still has no name — do you confirm your own July word for it, Discipline?

The outer two levels are already yours: the top is a Service — what a client actually buys, like creative production or brand strategy — and the bottom is a craft, which is the only finished vocabulary this system holds, because every one of the 73 crafts in use carries a full written rulebook saying when to tag it and when never to.

The last round printed that rulebook figure as 95 rather than 73, and both readings are true: 95 is the same tree counted whole — every live entry at all three levels, each one carrying its rulebook as well — and nothing in that tree has been created or edited since 21 July, so what changed between the two rounds is the set being counted, not the data underneath it.

What has never been named is the level in between — animation, copywriting, design, photography and post-production underneath creative production, which is exactly the level the contracts film below is credited at (Cinematography, Graphic Design and UI Design) — and your own July frame already calls that level Discipline, with Specialization and Execution below it, so this card puts your word back in front of you instead of assuming it; group and family are the alternatives if you want a different one.

My take: Confirm Discipline. It is your word, it is the only one of the three that does not already mean something else somewhere in this system, and the crafts sitting underneath it are the standard every other list here gets measured against.

Every enterprise deal comes with contracts full of details: start dates, billing terms, renewals — capturing that quickly and consistently is critical.
OpenAI · LinkedIn ad library · 2026-06-12 · written on it: case study video · source
Our holiday gift to you: Sora is here — generate entirely new videos from text, bring images to life, or extend, remix, or blend videos you already have.
OpenAI · TikTok · 2026-06-17 · written on it: product demo · source

What changes

One word gets written down, and the reference pages say Discipline where today they say nothing at all.

What stays exactly as it is

Nothing already written down is renamed by this call. Renaming anything in storage is engineering work and runs in the same pass as the rest.

Crafts on file, in use and retired together134
Crafts in use today73
Of those, carrying a complete written rulebook73
The whole tree counted at every level — the figure the last round printed as the craft count95
Of the whole tree, entries carrying a complete written rulebook95

Where this was worked out: the review agenda, item 8 — your July correction pass, checked against the live services tree

A-08: answer in chat with one line — A-08: CONFIRM · A-08: CHANGE: what you would change · A-08: LEAVE OPEN: what you still need to see

A-09Crew roles at the level of a single beat · short

Do we keep a vocabulary of crew roles at the level of one beat — who operated, who lit, who graded that moment inside the video — or park the question deliberately?

The craft ruling in August settled which parents a craft may have and left exactly one thread hanging: whether the beat level — one moment inside a video — gets its own vocabulary of crew roles.

Nothing is stored at that level today, so this is a question about what we start collecting rather than about repairing anything — the Commonwealth Bank case-study video below carries 31 described beats and not one of them names who shot it.

Its neighbour one level up is unaffected either way: the 65 credit roles written on a whole piece stay as they are, and parking is not losing, because a parked question goes on the ledger with today's date and comes back when the moments work needs it.

My take: I have no lean to offer here, and the agenda deliberately carries none either — this is a question about how deep you want the moments work to go, and dressing a guess as a recommendation would be worse than saying so. If you park it, park it with a date on it.

Commonwealth Bank set out to make AI a core capability at Australia's largest bank.
OpenAI · LinkedIn ad library · 2026-06-12 · written on it: case study video · source
Saturdays are for the new Sora drops — text-to-video generations, without modification: a scuba diver discovers a hidden futuristic shipwreck.
OpenAI · TikTok · 2026-06-17 · written on it: social clip · source

What changes

Rule it now and a new list gets designed, and the machine is eventually asked to fill it in. Park it and one dated line goes on the ledger; nothing else happens.

What stays exactly as it is

Credits on the whole piece are untouched either way, and no described beat changes.

Credit roles on file for a whole piece — the neighbour this would sit beneath65
Beats in the library carrying a description today, none of which name a crew3,355

Where this was worked out: the review agenda, item 9 — the craft question left open at the August walk

A-09: answer in chat with one line — A-09: CONFIRM · A-09: CHANGE: what you would change · A-09: LEAVE OPEN: what you still need to see

A-10The definitions queue · full

Most of the words this system can write have never been defined in writing — do the drafted definitions stand as the start of a standing queue?

How many words does the system hold?973 in use, across every list it has.
How many of them say what they mean?379 — well under half.
What do the rest carry?Nothing at all, or on 12 of them an engineer's note in brackets, sitting where a definition should be — a smaller number than this card first carried, and the walkthrough says why.
What does a finished one look like?The crafts: all 73 in use say when to tag them, when never to, and what they get confused with.
What is being asked here?Let the drafted definitions stand as the seed of a queue, and amend any that read wrong.

Every word this system can write on a piece or on a beat lives in one place, and that place holds 973 words in use. 379 of them say what they mean. The rest are a word and nothing else — which is perfectly workable while one person classifies from memory, and stops being workable the moment a second reader, human or machine, has to decide whether something is a Documentary or simply a film shot in a documentary style.

You named this yourself before anyone measured it. Reading the craft rulebooks you said the definitions were “definitions still a little off”, and the reference page built afterwards found the same thing at scale: the reference page cited 370 defined of 973 when it was written on 11 August, and the same set of words read again today gives 379 of 973 — with nothing in it created since 11 August and nothing edited since 21 July, so the difference is a different way of counting, not a change in the words themselves. Take either figure and the conclusion is the same — most of the vocabulary has never been written down.

The same honesty is owed on the smaller of the two figures. An earlier version of this card counted 21 words carrying an engineer's note where a definition belongs. Read again today it is 12, and the shortfall is not a matter of where you look for the brackets — under the loosest test, a bracket anywhere in the entry rather than only at the start, it is still 12: the six families of beat — a different list from the family names in A-04; these group moments, not labels — and the six words for how a piece speaks. Nothing in that set has been created since 11 August and nothing has been edited since 21 July, so the 21 was a wider hand-count rather than a figure the data has moved away from. It is the weaker of the two numbers, which is why it is printed here rather than quietly swapped in — the same way the larger correction earlier on this page is printed.

One part of the system is finished, and it is the model for the rest. All 73 crafts in use carry a real rulebook — when to tag it, when never to, what it is confused with — which is why both podcast pieces below can be credited Brand Copywriting without anybody needing to argue about it. The last round printed 95 of 95 here instead; that is the whole services tree counted at every level rather than the craft level alone, it is equally complete, and nothing in that tree has been created or edited since 21 July. Nothing else in the system has that, and everything else in this review quietly assumes it does.

The two podcast pieces below are the whole problem at reading size. They are two episodes of the same show, five days apart, with the same two guests — the researcher's surname is even spelled two different ways across them, Hata and Hara. But the machine did not read them as the same thing at all: one is credited to ChatGPT and Microsoft and is about what people are making with images, the other to DALL-E and about how the text inside those images got good. The one thing they genuinely share is the word written on them — podcast video, which 56 pieces in the library carry. So if a third person had to decide whether either of them is really an Interview instead, there is not one sentence written anywhere in this system that would help them, and knowing what each episode is about is no help either, because that is a difference of subject and the question is a difference of kind. The outside review named six of these boundary terms — Documentary, Interview, Testimonial, Product Demo, Music Video and User-Generated — and each one is a kind of piece only when that structure is the spine of the whole thing; otherwise it is a style, a job the piece does, or a single beat inside it. Those six get a written line saying what each is confused with, in the same pass.

The reference page already carries a batch of drafted definitions, every one of them marked as a draft. The proposal is the cheapest possible version of this work: they stand as the seed, you amend the ones that read wrong, and the remainder becomes a queue worked a batch at a time — instead of waiting for one heroic pass that never gets scheduled.

My take: Let them stand. The undefined words are the quiet reason this review keeps re-arguing the same three boundaries, and a queue that moves a batch at a time will beat the perfect pass nobody ever starts.

People are generating over 1.5 billion images a week in ChatGPT — Product lead Adele Li and researcher Kenji Hata on new use cases and trends since Images launched.
OpenAI · TikTok · 2026-06-02 · written on it: podcast video · source
Together with host Andrew Mayne, Product lead Adele Li and researcher Kenji Hara trace the progress from the early DALL-E days to the latest capabilities, including better text rendering.
OpenAI · TikTok · 2026-06-07 · written on it: podcast video · source
Commonwealth Bank set out to make AI a core capability at Australia's largest bank.
OpenAI · LinkedIn ad library · 2026-06-12 · written on it: case study video · source

What changes

The drafted definitions become the first approved batch, and the remainder of the 973 words becomes a queue worked in order.

The six boundary terms each gain a line saying what they are confused with — the part that stops the same argument coming back every round.

What stays exactly as it is

No word is renamed, retired or re-filed by having its definition written. Nothing on any stored piece or beat moves.

The crafts are already done and are not re-opened by this.

Words in use across every list973
Of those, carrying a written definition today379
Carrying an engineer's note in brackets where a definition should be12
Crafts in use — the finished standard73
The whole services tree counted at every level — the figure the last round printed as the craft count95
Of those, carrying a complete rulebook73
Families of beat, every one of which holds a note rather than a definition6
Pieces carrying the one word the two podcast episodes share56

What this call does to everything else written on these pieces

A definition is not a fact about a piece, so confirming this moves nothing in the library — and yet it is the item everything else in this review leans on. The instructions the machine is given are meant to be generated from this same set of words, so a word with no definition is a word the machine guesses at every time it reads a film. The shelves you browse by are built from these words, so an undefined word is a shelf nobody can explain to a new person. The six boundary terms are precisely the pairs that put a piece on the wrong shelf in the first place. And the two podcast pieces above keep the same one word between them, with nothing on file that says whether that word — or Interview — is the right one for either of them.

The alternative, and its cost: Write nothing and lean on the machine's own consistency. The cost is that consistency is all you ever get: it will keep calling the same thing by the same word, and nobody will be able to say whether that word was the right one — and the six boundary terms will be re-argued in every review round, exactly as they have been in this one.

Where this was worked out: the review agenda, item 10 — the vocabulary reference, measured on 11 August and re-read today

A-10: answer in chat with one line — A-10: CONFIRM · A-10: CHANGE: what you would change · A-10: LEAVE OPEN: what you still need to see

A-11A last-reviewed date on every page · short

Do we stamp every model and decision page with the date it was last reviewed, and flag the ones nobody has touched since?

This call and the last one on the page are the two that are not about how a piece is classified at all — they are about the written pages themselves — and this one starts from a plain gap: our checks are good at catching a bad edit and completely blind to a page nobody edited, which is the failure that actually happens here, and the one this window's audits kept catching by hand, six pages at a time.

The proposal is the smallest thing that fixes it: every model and decision page carries the date it was last read, and the review loop flags any page that has gone past a set window untouched, which is the same freshness stamp the large documentation teams use.

It changes nothing about what any page says; it only makes a stale page visible before somebody trusts it, and that matters most for the pages that define words — the two podcast episodes below are about different things and credited to different products, yet both are filed under the same one word, and whether that is the right word for either of them rests on a definition page nobody has been told to re-read.

My take: Adopt it. Every other item on this agenda is about getting a word right once; this is the only one about noticing when a right answer has quietly gone stale.

People are generating over 1.5 billion images a week in ChatGPT — Product lead Adele Li and researcher Kenji Hata on new use cases and trends since Images launched.
OpenAI · TikTok · 2026-06-02 · written on it: podcast video · source
Together with host Andrew Mayne, Product lead Adele Li and researcher Kenji Hara trace the progress from the early DALL-E days to the latest capabilities, including better text rendering.
OpenAI · TikTok · 2026-06-07 · written on it: podcast video · source

What changes

One date at the top of each page, and one check that reads it and complains.

What stays exactly as it is

Not a word of any page's content, and nothing whatsoever in the library.

Where this was worked out: the review agenda — raised at the best-practices round on 17 August

A-11: answer in chat with one line — A-11: CONFIRM · A-11: CHANGE: what you would change · A-11: LEAVE OPEN: what you still need to see

A-12Renaming the site · short

You raised renaming this site from Atlas to the BrandTrackers docs and said it was not urgent — so when should the rename happen?

Like the call before it, this one is about the site rather than about how anything is classified, and it is your own thread — your words, banked on 16 August: “our atlas which we should really just rename as our brandtrackers docs… done whenever it makes sense.”

So this card is about timing: the rename touches the site's title, the language on the front door, and the name it is hosted under — and nothing else.

The scuba-diver clip below is filed identically the day before and the day after; a rename changes the sign on the door, not one word written on one piece.

My take: Do it at the next promote. It is a small job that only gets bigger, and every week the old name stays is another week of writing that has to be corrected later.

Saturdays are for the new Sora drops — text-to-video generations, without modification: a scuba diver discovers a hidden futuristic shipwreck.
OpenAI · TikTok · 2026-06-17 · written on it: social clip · source
Wait for it — Sora can be prompted with text, images, or video inputs, and can interpolate between two input videos for seamless transitions.
OpenAI · TikTok · 2026-06-17 · written on it: social clip · source

What changes

The site's title, the wording on its front door, and the name it is hosted under.

What stays exactly as it is

Every page keeps its content and every piece keeps its label. Nothing in the library is aware this happened.

Pieces in the library, not one of which this touches13,938

Where this was worked out: your own words, banked on 16 August at the schema-view walk

A-12: answer in chat with one line — A-12: CONFIRM · A-12: CHANGE: what you would change · A-12: LEAVE OPEN: what you still need to see