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Before you add AI to a business website, write down where human review belongs.
A useful brief answers four questions:
• What information does the customer provide?
• What rules stay fixed for every request?
• What should a usable result contain?
• What needs a person’s approval before it is shared or acted on?
For example, an AI-generated event description may be a useful draft, but the date, price and booking link still need checking. Name the reviewer and the next step in the brief. This is a planning example, not a claimed client outcome.
Lucete AI Lab’s Brand Strategy, Website Messaging & AI Workflow Brief connects those decisions to your offer and website messaging. The fixed scope covers one brand, one core offer and one target market, including three AI workflow guides with example outputs and human review checklists.
USD $3,000. Final PDF and editable text, with one consolidated revision. Website implementation and AI integrations are scoped separately. Written English communication with translation support.
View the full scope and enquire through Contra:
https://contra.com/s/AvocoLOo-brand-strategy-website-messaging-and-ai-workflow-brief
contra.com
Brand Strategy, Website Messaging & AI Workflow Brief by Lucete AI Lab
Read more about Brand Strategy, Website Messaging & AI Workflow Brief by Lucete AI Lab on Contra.
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IBT came to me with an AI-generated draft: one long page, every service in an identical card, stock people in suits, copy like "unparalleled efficiency"
IBT is a 30-year consultancy that turns messy processes into clear systems. The draft showed the opposite
An AI tool gives every block the same weight. Someone has to decide what an operations director should understand in the first scroll
So each section got one job: who IBT is, why them, the three solutions. Each solution leads to its own page and to an enquiry. Process Mining, their core offer, got the most care
The video shows both: the AI draft and the live site
AI saves you the first draft. Turning it into a site that sells the company is still the designer's job
The site is live at theibtgroup.com.
Giving every block the same weight is exactly the problem with AI drafts. Deciding what a 30 year consultancy should lead with is where the real design work happens.
I’ve been working on a small skill called Manual Orchestrator to make longer projects with AI agents easier to manage.
The problem started with a familiar situation: one chat would accumulate plans, implementation details, corrections, and test results. By the time I was ready for the next phase, I wanted a fresh conversation without losing the decisions we’d already made.
Manual Orchestrator gives that process some structure. One chat acts as the orchestrator: it breaks the work into stages and writes a prompt for the next one. I run that prompt in a new session, then bring the result back. The orchestrator reviews it against the stage’s criteria before preparing the next prompt. If something needs fixing, I go back to the same worker session.
The skill also keeps a record in the project with the current stage, decisions, evidence, and next steps. That makes it easier to pause, resume, or hand the work to another session.
The handoff is manual. I choose when to open a session and carry the result back. The orchestrator and worker sessions can also use different agent CLIs, with the prompt adapted to the capabilities available.
It’s open source and still a work in progress. I’m using it to learn what helps in practice and where the workflow needs to improve. Installation has been checked for Codex, Claude Code, and Gemini CLI, but the full workflow hasn’t been tested across every CLI or version.
If you try it, I’d be interested in hearing what works and where it gets in your way.
For an AI scribe, I'd test what happens when someone switches encounters while a draft is still generating.
In my Arogya / Aurora EHR work, typed or dictated rounds become editable drafts. AI content stays advisory, and a clinician explicitly approves anything added to the chart.
The first response should stay attached to its original encounter. Before saving, I'd check that the encounter being reviewed still matches the draft, as well as requiring clinician approval.
That context check belongs in the save workflow, even when the draft reads well.
kapilchauhan.netlify.app
Arogya / Aurora EHR: AI for inpatient care | Kapil Chauhan
Production hospital and EHR platform that accelerates rounds, documentation, records, and care operations with clinician-reviewed AI.