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- AI launches and setup changes, with links to the reporting and sources.
- Original tests and channel videos, with evidence and testing limits.
- One practical thing to try.
Read the latest published email issue: Readable text can still fail a video test →
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Fridays at 09:00 Vancouver time: source-checked AI changes, original tests and one practical thing to try. We skip a week when there is not enough verified material. Free. Unsubscribe anytime.
Archive and Proof Lab history
Earlier web updates, email issues and Proof Lab previews follow. Their dates and evidence limits remain visible.
Latest web update · September 24, 2026
Check the file, keep the evidence, save the plan
Output Preflight checks JSON and CSV structure in your browser, including repeated JSON keys, required fields and uneven CSV rows. Its browser video check reads duration and dimensions. The downloadable Python workflow adds full video decoding. These checks cannot establish factual accuracy, product fidelity or creative approval.
Production Benchmarks Report 002 includes three conventional bottle-ad exports and a separate recheck of eleven retained AI video clips. Each group passed its own technical checks. They used different tasks and cannot support a combined pass rate or provider ranking. Human acceptance decisions remain at zero; cost per accepted ad is unknown. The original files, protocols and checks are available to inspect and rerun.
The AI Stack Builder now carries research and no-additional-spend requirements into the subscription planner. You can keep a comparison with your brief, download a JSON backup and restore it later. Device saving is optional.
The model directory also adds official-source profiles for GPT-6 Astra, Sol and Luna, with prices drawn from the calculator's dated catalog. Those profiles summarize provider documentation; they do not claim a Kingy performance test.
Start with one output you already have: run its structural checks, then review it against the original source or brief.
What you can use it for
Builders
See what shipped, who can access it, what changed and what is worth testing next.
Investors and operators
Track funding, pricing, availability and company moves with direct source links.
AI-curious professionals
Understand the launches that matter without spending the week inside announcement feeds.
What to expect from Proof Lab
Each Proof Lab edition follows one practical AI task: make a video, choose an AI setup or build an app. It explains what was tested or reassessed, what happened, the limits of the evidence and one exercise you can try.
Expect links to retained inputs, outputs and methods. Original tests, retrospective reassessments and teaching exercises are labelled separately. Costs and access claims carry their dates; unknowns stay explicit.
The pilot, earlier editions and web previews are preserved here with their original dates and evidence limits.
Source-checked by design
Kingy prioritizes official product, company, documentation, pricing, regulatory and repository sources. Product claims are labelled as claims until independently verified. Pricing and availability are dated snapshots, and uncertainty stays visible instead of being filled with guesses.
Read the editorial and sponsorship standards.
The same standard, applied to research rather than product claims: the Kingy AI Referral Index collects selected studies of AI-driven referral traffic, explains their methods and limits, and presents dated Kingy measurements separately.
Proof Lab 01 · September 19, 2026 preview
When readable text is still a failed test
This September 19 web preview is preserved below. Its email adaptation was released as Proof Lab 01 on September 20, 2026 (Pacific time). This is a retrospective reassessment of six August 26 video outputs, not a fresh model comparison.
The job was narrow: animate a slow push-in on a supplied text card while preserving its wording and layout. A clip could look useful and still fail the strict preservation rule.
Proof Lab 01 records four strict failures and two unresolved outputs. None is certified as a pass. The unresolved clips still need a complete frame-by-frame review; a clean sampled frame is not enough. Earlier usability labels remain visible as historical judgments, not substitutes for this stricter test.
Try this: before generating a clip, write down the exact text, the allowed motion and what would count as a failure. Keep the input, prompt and unedited output. Review the whole clip before calling it a pass.
Inspect the six outputs and reassessment, or download the evidence and reproduction kit. Inspecting retained files needs no new model credits. New generation runs incur provider charges.
Verdict: use the recipe as a test fixture, not a promise that a model preserves exact typography. This small historical set does not establish a current model ranking.
Web preview · September 12, 2026
Test the answer against the job
Prepared September 12, 2026. This web preview was not emailed when it was published.
Our September 10 campaign ran four small tasks twice per model. Qwen3.8-27B and GPT-6 Astra passed 8/8 trials; DeepSeek V4.1 Flash passed 7/8; Claude Fable 5.1 passed 6/8. This is one hosted campaign, and the two articles share the same DeepSeek trials. It is a small sample, not a general ranking.
The failures show why the rules matter. One tool call used the string "null" where JSON null was required. Two chart answers included prose before the required JSON. A person could understand the answer; the application could not accept that format.
Read the Astra, DeepSeek and Claude results · Read the Qwen comparison
Check your inventory against these dates
OpenAI schedules gpt-5.4-cyber removal for October 1, Agent Builder shutdown for November 30, and removal of gpt-image-1-mini, gpt-image-1.5 and chatgpt-image-latest for December 1. Check the exact affected products and replacements in the official deprecation table, reviewed September 12.
Try this: choose a task you repeat and write its acceptance rule before choosing a model. Valid JSON, an exact total, a working function or a cited source gives you something concrete to check.
Inspect the retained test files. Reading them needs no model credits. Rerunning their API calls incurs usage charges.
Earlier issue: read the July 24 edition on likeness checks and AI bioresilience in the published archive.
Browse the reporting inputs
Beehiiv holds the published issue archive and manages subscriber preferences and unsubscribes. Browse the Daily AI Launch Radar to see the source-checked launches entering Kingy Launch Intelligence.
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