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Real-time film · 6:44 · production notes · 19 October 2026

What the Rain Made

What the Rain Made, 6:44. Watch on YouTube.

A six-minute, forty-four-second music video for your song The Celtic Fire, painted in white paper and blue watercolour by the weather itself: rain lands on the page, a pencil drawing appears under it and blue blooms from each drop, from Loch Lomond to the stones, the sea and the Saltire the rain made. One Fable 5.1 director and one Haiku researcher made it in a morning. This is where the time and the money went.

The session in four numbers

From a song to a finished music video

3 h 00 minfrom the brief at 06:26 to the commit at 09:26, with about an hour of that waiting on you or the GPU
3 h 03 minof agent working time
2 agentsone Fable 5.1 director and one Haiku 5.5 researcher
$27.69if every call had been billed at API list prices
6:44 film1920×1080 at 3063 shots106 generated images0 narrated lines1 song, your own570 lines of film code3,200 words of research
The morning

06:26 to 09:26

Each bar is one agent, from its first instruction to its last report; each thin mark is a tool call. The row below marks every picture the machine produced. The gaps in the director’s bar, about an hour in all, are times with no activity, while the GPU worked or the agent waited for you.

06:0007:0008:0009:0010:00Directorresearch: Scotland factsLocal: plates and pencil edits (106)pilot feedback 07:08MP4 written 09:21
Fable 5.1Sonnet 5.5Haiku 5.5Local machine, no API cost
The company

Who did what, for how long, at what price

Agent and assignmentRan (local)TimeAPI callsTool callsCost at list prices
Director · Fable 5.1
Director: orchestration, review and export06:26–09:263 h 00 min139224$27.58
Research · Haiku 5.5
Research Scotland facts for film07:10–07:133 min1366$0.11
2 agents152290$27.69
The bill

Where $27.69 went

By role

Director · $27.58 · 99.6%Concept, pilot, 63-shot storyboard, 106 image prompts, engine, review, export and the commit.
Researcher · $0.11 · 0.4%One fact sheet of about 3,200 words.

By model

Fable 5.1 · 1 agent$27.58 · 99.6%
Haiku 5.5 · 1 agent$0.11 · 0.4%

By kind of token

Cache reads (42 million tokens)$10.16
Cache writes (1 million tokens)$8.24
Output, thinking included (0.2 million tokens)$9.18

The director, hour by hour

export, video and publishing36 min · 30%
plates and images (generation)27 min · 23%
waiting on agents14 min · 11%
review and checking12 min · 10%
engine and film code12 min · 10%
waiting on the user7 min · 6%
score and sound5 min · 4%
docs, memory and notes3 min · 2%
agents: brief, launch, message2 min · 2%
research, script and brief1 min · 1%
other and unclassified1 min · 1%
clean-up0 min · 0%

Each gap between two transcript events is given to the tool call or message that ended it, then sorted by tool name, file path and command. The buckets are keyword matches, so read them as proportions. 1 h 59 min in all.

The film

What the morning produced

Nine frames from the film: a pencil outline of a loch and boat on white paper, the finished blue watercolour loch, washes blooming over the loch, a faded dry state of the loch, a blue waterfall in a ravine over pencil, lobster creels with one painted in, a whale blowing off a harbour town, the Saltire with cracked rain veins and a West Highland terrier by a hearth under a window.
Nine frames from 6 s to 395 s: the pencil, the painted loch, the blooming and fading washes, the waterfall, the creels, the whale, the slam and the hearth.

The local machine

106 images

Plates and pencil-drawing edits from 06:48 to 08:55: 52 base paintings and 54 edits, generated at a resolution of 1440 (1920 by 1088). The soundtrack is your own song, so nothing was voiced or scored.

The rain engine

570 lines

A shared pool of blooming masks, one scene per shot with special handlers, a per-shot table and measured anchors for the table, hearth, window and fork paths.

The timing authority

A song map

Cuts and blooms are keyed to song-map.md, copied from the third Celtic Fire version. The part-two turn at 2:08 is a single drop that falls upward, and the slam at 5:41 floods the Saltire.

The MP4

404 s, 473 MB

1920 by 1080 at 30 fps, CRF 20 with no denoise, about 9 Mbit/s, with an 81.6 MB single-file page. A 195 MB share copy at 4 Mbit/s keeps the paper tooth and pencil in a check of the St Kilda cliff.

What the checks caught

Eleven findings from the pilot and the rough cut

The review log records each diagnosis with the frames inspected, from the four pilot versions to the first full render.

FoundWhat went wrongHow it was fixed
Pilot v1: the rain editCame out as night, with chorus frames nearly black-blue and the paper gone; blooms read as dark bubblesReprompted as a soft shower in pale tones with white paper kept; blooms redrawn as crinkled blots
Pilot v1: rings and streaksWater rings were invisible on blue and rain streaks too faintRings as pale screen ellipses with a thin dark inner line; streaks wider and darker, then slanted into the wind
Pilot v2: the rimA rim band far too wide and dark, a crackle pattern over the hillsNarrowed to 0.965 to 1.03 of the blot and faded with the age of the bloom
Pilot v3: the rimThe rim now reads as a real wet edge and the 40 s picture is clean; the edits were still at the default sizeRegenerated at a resolution of 1440 (1920 by 1088), and build.py given a hung-job watchdog
First full renderA page error: the scene context was passed to drawImage instead of its canvas, which the Node smoke stub acceptsFixed so every handler draws the scene canvas
Glencoe stagThe stag was literally red in the first plateReprompted with a russet-brown coat and a new seed
Letter shotA tan desk and tan paper, so the whole frame left white paperReprompted on white writing paper and a pale desk
The slamThe Saltire’s blue was near navy and dirty from the dark mottleA cleaner base blue with a lighter mottle
Gallery pull-backIt ended at 1x, so the 54 cards were too smallEnds at 1.4x
LuskentyreUsed twice within 30 secondsThe second shot became the St Kilda stac with gannets, painted upward
Table plateThe empty-table edit kept the tartan rug, so the rug appears before its item bloomsLeft: it reads as part of the chair; minor
The GPU

Two times the card looked hung

You noticed high utilisation with a cool card twice, and asked the director to check.

WhenWhat you sawWhat it was
07:50GPU utilisation high but temperature lowA stall. The director added a five-minute watchdog to build.py that restarts the server and retries a hung job
08:30The same symptoms againNot a hang: the puffins’ pencil edit had just landed, and the card was pulling 426 W at 71 °C on the next job
What it taught

Six things the numbers say

Method

How these figures were measured

Measured from the session's own transcripts: the director's, and one for each of the 1 agents it launched. Assistant messages are deduplicated by message id and the last entry's usage is kept. Models come from each agent's metadata. The director ran on claude-fable-5-1, priced from the published rates: $10 per million input tokens, $12.50 for five-minute cache writes, $20 for one-hour writes, $0.25 for cache reads and $50 for output. Figures run to the commit at 09:26, and the transcript contains three stretches of activity separated by gaps of more than 20 minutes.

Cost is what the usage would have cost at API list prices in October 2026: Opus 5.5 at $4 per million input tokens and $20 per million output, Sonnet 5.5 at $2 and $10, Haiku 5.5 at $0.10 and $0.50 (higher rates above a 100,000-token prompt), cache reads at 0.05 times input, cache writes at 1.25 times (five minutes) or 2 times (one hour). A subscription session was not billed this way, so treat the dollar figures as a measure of work, not an invoice.

Times are UK local time (BST, UTC+1). Local-machine marks are the modification times of the generated files. The pilot and rough-cut findings come from the project’s review log, the GPU notes from the director’s messages, and the share copy and commit from its final report. The hour-by-hour split sorts tool calls by keyword, and gaps of more than 20 minutes with no events are left out of it.