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Experiments

The lab ledger, kept honestly.

Every AI surface on this site started here. This page is the log: what each experiment claims, how it is rigged, and what the current reading says, including the ones that parked.

Entries

8

Live right now

4

Graduated

2

The ledger

Hypothesis, setup, reading

A log, not a roadmap. Entries move only when the thing itself moves. The chips are the truth: green is live, copper graduated, amber on the bench, palm is plumbing, grey is parked.

Ask Aziz

Live on site

Hypothesis

A site assistant can answer well and qualify leads in the same conversation, without gating basic answers behind contact forms.

Setup

DeepSeek streaming chat with a first-person persona, a 16k-token prefix-cached knowledge pack, full-text retrieval over the published writing, and a 12 req/min cap sitting under a 15/min edge rule. In the corner of every page, and inside the services, case-study and blog pages.

Current reading

Matching the visitor’s language is a useful trust cue. Punctuation checks also exposed a gap between instructions and enforcement: a prompt can request a writing style, while output checks enforce the chosen rules. Three controlled turns recorded on 19 July 2026 had cache-hit rates of 99.8%, 87.7% and 99.4%; that small historical sample does not establish the current production rate.

KSA Compliance Assistant

VisitLive on site

Hypothesis

In a regulated topic, an assistant is only trustworthy if it answers from dated, approved sources. It has to refuse when those sources run out.

Setup

Grounded on hand-approved source chunks with dates, citation tags on every answer, a thumbs feedback loop into Supabase, and a 12 req/min cap.

Current reading

Refusing to improvise reads as competence, not weakness. Unanswered questions become the content backlog; the assistant tells us what to write next.

Deep Prompter

VisitGraduated

Hypothesis

Guided scoping beats a blank prompt box: a few sharp questions produce a better research prompt than one heroic attempt.

Setup

A strict-JSON dialogue: the model must ask one question per turn with clickable options, then hand back a copy-ready deep-research prompt in Arabic or English.

Current reading

Graduated to its own product page. The strict output contract (JSON only, validated) is what made it shippable. The constraint was the feature.

Najdi Prompt Bank

VisitGraduated

Hypothesis

Prompts written in the dialect people actually work in get copied and used more than prompts translated into textbook Arabic.

Setup

338 prompts in Najdi Arabic across 7 categories (business, marketing, technology, education, design, government, and personal productivity & wellness), with client-side search, filters, and one-tap copy. Review each template for your task before using it.

Current reading

Dialect register is product infrastructure, not decoration. Now paired with a live Prompt Refiner that reworks rough prompts in the same register.

Lifelog Simulator

VisitLive on site

Hypothesis

A live simulator on realistic Saudi work scenarios sells an on-device Work OS better than screenshots ever could.

Setup

Pick a scenario and the model turns it into generated deliverables (reports, follow-ups, briefs) on safe demo data, capped at 15 req/min.

Current reading

People trust what they can poke. The simulator answers the "but would it work for OUR mess?" question before the first call.

Stack Advisor & Prompt Refiner

VisitOn the bench

Hypothesis

The first pass of a consulting engagement (name the bottleneck, order the moves) can run as a public tool without turning into theater.

Setup

One shared endpoint, strict JSON mode, vendor-neutral system prompts, validated outputs, 10 req/min. The advisor lives on the toolkit page, the refiner on the prompt bank.

Current reading

Fresh on the bench. Still watching what people actually paste in, and whether the "smallest move first" ordering survives contact with real workflows.

Retrieval over site content

Live on site

Hypothesis

Grounding a small model on real published content beats stuffing a bigger prompt. Second attempt: a model choosing from a list of titles beats cosine similarity over chunks, when the corpus is small enough to list.

Setup

Back, without embeddings. A cheap router call reads a manifest of every published document and names at most two; their full text is inlined into the answering call as a trailing system message, so message 0 stays byte-identical and the prefix cache holds. Retrieval failure is never fatal: it degrades to the ungrounded answer.

Current reading

The current implementation uses a published-document manifest and full-text retrieval without a vector database. The router can select no document when the site has no relevant source. Accuracy, language quality and cost need representative evaluation; the earlier experiments do not establish superiority over other retrieval methods.

Homepage variants bench

Parked

Hypothesis

Sixty systematic homepage variants will find the brand’s visual voice faster than polishing one draft forever.

Setup

A private preview rig, reviewing structured homepage variations side by side: palettes, type pairs, hero compositions.

Current reading

Parked, learnings shipped: the warm-editorial system and the red "Thread" spine came out of this bench. The rig stays parked until the next big visual question.

Open questions

What the bench is chewing on

The threads running through every entry above. Answers land here first, then in the writing.

Trust signals: which small cues (citations, refusals, rate caps made visible) actually move a visitor from "demo" to "I would give this my workflow"?

Bilingual interaction: how do Arabic and English share one product without either feeling like the mirror of the other?

Dialect register: where does Najdi help an AI product (prompts, chat, microcopy) and where does authority need formal Arabic?

House rule

How an experiment graduates

01

Survive real use

It runs behind guardrails, with strangers, and does not embarrass itself.

02

Earn its page

It graduates when it deserves a product page or a case study. Not before.

03

Or park honestly

If the learnings ship but the artifact doesn’t, it parks in plain sight instead of being quietly deleted.

Next step

If one of these entries is close to your situation, pull it into a live brief.

The fastest way to test an experiment is against a real team with a real bottleneck. That conversation starts with one short note.