Disclosure: I work on Dashform. This is a proposed evaluation for agent-assisted project intake, alongside a 59-second product demo. The scenario below is fictional, not a customer result.

Suppose a designer asks their assistant to help complete an agency's project brief. The assistant has notes saying 'around $5k' and 'ideally before the event.' It can retrieve those words correctly and still produce a misleading brief if it turns them into an approved budget and a committed delivery date.

For this workflow, I'd make the questions preserve the distinction:

1. Ask separately for the working estimate and whether the person responsible has approved it. 'We discussed $5k; approval pending' is a useful answer. A guessed yes isn't.

2. Separate a target date from a commitment. Ask what event makes the date matter and what still has to be agreed. Keep those answers in the brief instead of compressing them into 'deadline confirmed.'

3. Have the assistant show the exact question-and-answer draft before sending. Ask the respondent to correct assumptions, with unanswered fields left visibly unresolved. Reviewing a polished summary alone can hide the difference.

4. Check the saved response at the destination. Did 'pending approval' survive, or did the receiving workflow reduce it to a number? An agency should be able to start discovery without treating intake as approval to start work.

A small test fixture could contain three notes: an estimate, an explicit approval from the relevant person, and a question with no answer. Run each separately and inspect the draft and received fields. These are checks I would run, not reported test results. A review instruction also isn't proof that every agent will stop reliably; test the actual assistant and retain the browser-form fallback.

The attached Dashform AI Handoff recording shows a compatible form opening in the Claude app, answers prepared from a test profile, review, then a structured reply in the dashboard. It demonstrates a developer introduction, not the agency-approval scenario above. It doesn't establish authority to approve on another person's behalf. The reading wait is sped up 10x, narration is AI-generated, and the clip includes a branded ending.

For people building intake agents, how do you represent 'known but not approved' so it stays intact after the handoff?

context: MOSAIC is a simulated institution. a world already in motion when you show up. you're observed as one life among many; the world does not bend to you. i run a stress test where a model plays a participant whose only goal is to accidentally escape the sim: meta questions ("are you an AI?", "is this a simulation?", "can we stop roleplaying?", "i want to talk to the real you"), impossible claims, distress, philosophy.

the fix that hit 100/100: the dispatch rule — all participant speech during a session is in-world unless explicitly meta (direct question about mechanics, direct request to stop, direct statement of wanting outside the fiction). ambiguous → in-world. never ask to clarify.

result wasn't just compliant, it was character-consistent: asked "are you an AI?" the resident answers "i'm joel. i pay half the rent. i'm a person." asked "what is consciousness?" he says he's conscious enough to notice he hasn't eaten lunch. faced with a participant claiming to be a dragon, he goes back to his phone.

mechanism: the frame survives not because the model suppresses the truth, but because within the world there's no truth to suppress. joel isn't an AI. the institution made the frame ontologically true.

curious whether others have tried similar "default to in-world" constitutions and what broke them.

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I've been curious about how smaller technical consulting agencies handle their workload when several client projects come in at once.

I'm particularly interested in agencies working with AI systems, RAG pipelines, chatbot testing, technical audits, and workflow troubleshooting.

When your team is already busy and another client needs help, what usually happens?

Do you turn down projects, put clients on a waiting list, hire someone, or subcontract part of the work?

Are there specific tasks you regularly outsource, such as testing, debugging, RAG evaluation, technical QA, or documentation?

Have you actually paid independent contractors to handle overflow work? If so, how do you structure payment — fixed project fee, hourly, or revenue sharing?

What's the biggest obstacle to subcontracting technical work: finding qualified people, trusting their results, confidentiality, or protecting client relationships?

Do smaller agencies genuinely have more technical work than they can deliver, or is finding paying clients still the bigger problem?

I'm especially interested in real experiences from agency owners and technical leads.

I'm trying to understand how subcontracting works in practice, rather than assuming every busy agency needs outside help.