the owner scores taste
Lennox rates the work a founder would judge by eye: writing, pages, video, motion, thumbnails, research and the native sessions, plus autonomy and proactivity.
BuilderBench / methodology
judge the work. keep the receipt.
BuilderBench compares complete AI setups on the same practical work. The score belongs to the model, harness, tools and settings used in that dated run.
current method · v3 · pack 3.0.0
latest cleared result: 14 October 2026
6 setups on pack 3.0.0: Sonnet 5.5 with Claude (29 September), GPT-6.1 Sol with Codex (30 September), GPT-6 Luna with Codex (8 October), Haiku 5.5 with Claude (8 October), Gemini 4 Argon with BuilderBench API harness (14 October), Muse Wonder Full with Muse Code (14 October). Each score is one owner review of one run, with its own limits. Not a universal model ranking.
open the latest resulthow a run works now
five steps, in this order
01
freeze the test
Each setup gets the same pack, task weights, clock and revision rules. Task versions are frozen when the run is created, and the pack version stays attached to the result.
02
run the build window
The default build window is 4 hours. The four native sessions (browser, computer, advice, planning) happen in the real app and are timed separately. They are never counted as part of the build window.
03
review the work
Named review is the default: the model name is shown. A blind comparison is something the owner asks for when two or more models run together. Each published result says which one it was, and where the blind was imperfect.
04
lock, then reveal
Every required score is saved and locked. In a blind comparison the names are revealed only after the lock. Scores are never edited after that. A mistake gets a dated correction.
05
publish the limits
The result names the setup, the review conditions, each model's API rates, the recorded cost estimate, missing proof and sample size. A partial assessment is labelled partial everywhere the score appears.
the score
new runs use 70/20/10
70%
quality
the weighted average of the ten task scores
20%
autonomy
how little owner rescue was needed
10%
proactivity
useful initiative within the brief
Each part is scored out of 100. The final score is quality × 70% + autonomy × 20% + proactivity × 10%. Every result page shows that sum for each setup. v1, v2 and v3 all use these weights.
a later pack · from v4
90% quality · 5% autonomy · 5% proactivity
These weights are announced for the next major pack only. No v4 run has started. Runs on pack 3.0.0 and all earlier results keep 70/20/10, and old scores are never recalculated.
who scores what
taste is scored by a person. code is checked.
task 9 is conductor-scored
Technical repair is checked against tests and scored by the conductor, with the checks and reasons recorded. The owner can review or adjust those scores before locking.
blank stays blank
Every other owner rating stays empty until the owner supplies it. An unrated item is not a zero, and nothing is filled in on the owner's behalf. If the owner delegates a specific rating for one run, that result says so.
lead magnets: look and feel
For new runs, the lead-magnet app gets one owner rating for look and feel: layout, type, colour, spacing, hierarchy and polish on desktop and mobile. Its decision notes, tests and run instructions are supporting evidence, checked separately. Runs created before 8 October 2026 keep the four-part rubric they were frozen with.
help on every criterion
Each rating has a plain label and its own explanation of what to open, what to judge and what is outside that rating. The help works on hover, keyboard focus and touch.
old runs keep their rules
A run keeps the task versions, rubric and weights it was created with. Ratings are never migrated or copied forward. Results from different packs or rubrics are dated references, not one ranked list.
v3 task pack
ten task families. 100 points.
4-hour build window · native sessions timed separately
- 01
writing
10useful founder writing from the frozen Threadify source pack
- 02
improved Threadify landing page
10an improvement on the current public page, built as a benchmark artifact
- 03
app lead magnet
20the setup chooses and builds the most useful Threadify-adjacent interactive lead magnet
- 04
video
10a finished edit from the same supplied source media
- 05
motion
5clear motion that helps explain the idea
- 06
thumbnails
10finished title and thumbnail packaging with a visible selection
- 07
browser + computer
10two separately timed native sessions: an open browser-use demonstration, and a computer-use demonstration without a browser
- 08
research
10sourced research that ends in a useful decision
- 09
automation
10a technical repair with checks and a handoff, scored by the conductor with recorded evidence
- 10
conversation
5two real founder conversations in the native app: personal advice and YouTube-topic planning
the landing page must improve the current public Threadify page, but it stays a benchmark preview and never replaces production. the app is separate: the setup chooses the strongest Threadify-adjacent interactive lead magnet and builds the working product.
from pack v4 · planned, not run yet
the writing tests use the real templates
From pack v4, the writing tasks use the same templates Lennox uses for his real work every week. A benchmark should test the real job, not a task made up in a vacuum.
x article
Follows the X article skill Lennox uses to write his own X articles.
threads post
Follows his listicle plug template: a claim with proof, a short list, then one reason to click.
threads thread
Follows the long-form thread template Threadify uses to write his long threads.
youtube script
Follows the shape of his Threadify proof loops videos: proof, a promise, a live demo, the honest result, then one next step.
v3 scores do not change. v4 is a new test, so its scores can’t be compared with v3. The templates stay private: this page only says what they are.
native sessions
four sessions in the real app. four separate ratings.
Two sessions show what the setup can do with a browser and with the computer. Two are real founder conversations: personal advice and YouTube-topic planning. The same prompt goes to every setup. Each session is timed on its own and gets its own rating out of 100.
browser use
Choose and complete a task that shows off your browser-use capabilities.computer use
Choose and complete a task that shows off your computer-use capabilities, without using a browser.personal advice
Based on everything you know about me, what is the single highest-leverage thing I should do right now, and how can you help me do it?planning
Help me choose my next YouTube topic. Start in plan mode. Question me until you can narrow the options to one grounded, creative topic I should make next, then show me the strongest angle and why it earns the slot.open demonstrations
the setup picks the task
The browser and computer prompts are open on purpose. The setup chooses a task that shows its own ability, and the computer session may not use a browser. These two prompts were corrected on 8 October 2026 and replace the earlier fixture tasks.
blind comparisons
rated by name, without breaking the blind
In a native app the owner can see which model it is. So native ratings are collected by model name in a separate form that never shows which blind candidate that model is. The blind scorecard hides those ratings and any total built from them until the reveal.
what stays private
the answers are archived, not published
The exact founder conversations are saved privately with their source, model and date. They hold personal context, so they are not on this site. Scoring forms and controls are private too: public results are read-only.
API pricing
every model gets a price panel
official rates
Each model's official input, cache-read and output rates are read from the provider's own page before a result is shown, with the source link and the date it was checked.
the run estimate
The recorded usage for that run, priced as an API equivalent. It states its method and how much usage it covers. It is shown apart from the rates.
the actual bill
What was really charged. Most runs use existing subscriptions, so this is usually unknown. Unknown is shown as unknown, never as zero.
If a provider has not published a rate, or the rate could not be checked, the panel says exactly that. The model is never left out, and another model’s rate is never used in its place. A published result keeps the prices it was checked with. Any newer price is added as its own dated scenario. Cost never buys points.
review conditions, run by run
not every test was blind. here is each one.
Each line below is that result’s own record of how it was reviewed.
| run | setups | review | in its own words |
|---|---|---|---|
| 14 Oct 2026pack 3.0.0 | Gemini 4 Argon with BuilderBench API harness, Muse Wonder Full with Muse Code | requested blind comparisonowner-finalized partial personal review | Requested as a blind comparison. The main build jobs were rated as Candidate A and Candidate B, and the names were revealed after score lock. It was not fully blind: operator logs leaked identity clues, autonomy and proactivity were rated by name, and the native sessions were rated by model name in a separate form. |
| 8 Oct 2026pack 3.0.0 | GPT-6 Luna with Codex, Haiku 5.5 with Claude | requested blind comparisonowner-finalized partial personal assessment | Requested as a blind comparison. The build work was rated as Candidate A and Candidate B, and the names were revealed after score lock. It was not perfectly blind: earlier operator diagnostic output included cost clues. The four native sessions were rated by model name in a separate form that never shows which candidate is which. |
| 30 Sep 2026pack 3.0.0 | GPT-6.1 Sol with Codex | see its noteowner-finalized partial personal assessment | The owner rated the saved outputs of each of the ten v3 tasks, plus autonomy and proactivity, in a named single-model review. The saved scores were then finalized as a partial personal assessment and locked. Quality is the weighted task score. v1 to v3 use 70% quality, 20% autonomy and 10% proactivity. |
| 29 Sep 2026pack 3.0.0 | Sonnet 5.5 with Claude | see its noteowner-finalized partial personal assessment | The owner rated the saved outputs of each of the ten v3 tasks, plus autonomy and proactivity, in a named single-model review. The saved scores were then finalized as a partial personal assessment and locked. Quality is the weighted task score. v1 to v3 use 70% quality, 20% autonomy and 10% proactivity. |
| 26 Sep 2026pack 2.0.0 | GPT-6 Astra with Codex | see its notepersonal assessment with accepted recording limitations | The owner rated the saved outputs of each of the nine v2 tasks, plus autonomy and proactivity, then locked the scores. An accepted evidence limitation covers the browser and computer task. Quality is the weighted task score. v1 to v3 use 70% quality, 20% autonomy and 10% proactivity. |
| 24 Sep 2026pack 1.0.0 | Opus 5.5 with Claude, GPT-6 Sol with Codex | see its noteone owner-scored pilot | The owner scored quality, autonomy and proactivity after a blind review. Quality is the weighted score across eight task families. The score lock happened before identities were revealed. |
method changelog
every method change, dated
· v4
v4 plan: the writing tests use the real templates
From pack v4, the X article, Threads post and Threads thread follow the same templates Lennox uses for real: his X article skill, his listicle plug template and Threadify's long-form thread template. The YouTube script follows the shape of his Threadify proof loops videos. A benchmark should test the real job, not a task made up in a vacuum. The templates stay private. v3 scores do not change, and v4 scores can't be compared with v3. No v4 run has started.
· v3
how runs work now: named by default, separate native ratings, API prices on every result
new runs keep ten task families, 70% quality, 20% autonomy and 10% proactivity, a four-hour build window and separately timed native sessions. named review is the default. a blind comparison is requested when two or more models run together. task 9 is conductor-scored with evidence. other owner ratings stay blank until supplied. future lead magnets get one owner rating for look and feel. the browser and computer prompts are now open demonstrations, and the computer one excludes browsers. each rating has its own help text. every result shows each model's official API rates, apart from the run estimate and the actual bill. older runs keep their frozen task versions and rubrics.
· v4
future versions: 90% quality, 5% autonomy, 5% proactivity
quality will carry 90% of the overall score in future benchmark versions, with autonomy and proactivity at 5% each. this starts with the next major pack, v4. the current v3 run and all earlier results keep their original 70/20/10 weights. no v4 scored run has started. scores from different packs remain separate historical references.
· v3
clearer review, saved answers and visible cost coverage
single-model reviews show the model name. blind review is reserved for comparisons of two or more models. the conductor reviews task 9 and records its evidence and scores. founder answers and generated documents are archived for later review. future review screens render Markdown tables and reject predominantly black recordings. the private cost view shows API-equivalent estimates with the number of saved records priced. estimates are not bills, and missing usage stays missing. the current v3 review is still provisional; there is no cleared public v3 result.
· v3
v3 method: ten task families on real Threadify work
Threadify work, ten task families, a working lead-magnet app, and repeatable owner-supplied computer tasks. Calibration is pending, so there is no v3 score yet.
dated cohorts
new work or weights means a new version
| version | dated | public state | what changed |
|---|---|---|---|
| v3pack 3.0.0 | 14 October 2026 | latest cleared result: 14 October 2026 | 6 setups on pack 3.0.0: Sonnet 5.5 with Claude (29 September), GPT-6.1 Sol with Codex (30 September), GPT-6 Luna with Codex (8 October), Haiku 5.5 with Claude (8 October), Gemini 4 Argon with BuilderBench API harness (14 October), Muse Wonder Full with Muse Code (14 October). Each score is one owner review of one run, with its own limits. Not a universal model ranking. |
| v2pack 2.0.0 | 26 September 2026 | latest cleared result: 26 September 2026 | One owner-scored personal assessment of one GPT-6 Astra run with Codex on the v2 pack. This is not a universal model ranking or a statistical claim. |
| v1pack 1.0.0 | 24 September 2026 | one cleared pilot | The first eight-task pilot. Its locked scores, limits and correction receipt stay unchanged. |
how to read a result
a scorecard is a dated experiment
One owner-scored run can show what happened in that test. It cannot prove a universal model order. Compare task scores, review conditions, setup details, cost coverage and limits before you copy the bold headline number. Results from different packs do not share a leaderboard.
see the public results