What to Ask an AI Expert in One Session
In one session, ask decision questions, not lecture questions. The four shapes that produce the most value are: which of these options fits our constraints, where will this break in production, what are we not seeing, and what should we do next. Bring your real context and specific examples so every answer is shaped to your situation instead of the generic case. The rule of thumb: if a question could be answered by a search engine, it wastes the hour; if it needs judgment applied to your specifics, it is worth asking.
The mistake most people make is asking an expert to explain a topic. That turns an expensive hour into a lecture you could have gotten from an article. The value of a live session is judgment, so ask the questions only someone with production scars can answer for your exact case.
I'm Mahmoud Zalt, an AI architect. Through Sista AI I spend much of my week answering exactly the pointed questions this article is about.
The Four Question Types That Produce the Most Value
Sort your questions into these four types before the call. Each one gets you something a search cannot.
1. Decision questions
'Should we use X or Y, given our constraints?' This is the highest-value shape because an expert can give a direct, reasoned answer that accounts for your data, budget, and team. Frame every option concretely and the choice often clarifies as you ask it.
2. Diagnostic questions
'Why is our system doing this?' Bring the failing outputs, the logs, or the eval numbers. A practitioner recognizes patterns you have not seen before and often names the root cause in minutes rather than the weeks it would take you to find it.
3. Risk questions
'Where will this break, and what are we not seeing?' This is what an outside expert is uniquely good at. Your team is too close to spot its own blind spots; someone who has watched similar systems fail knows exactly where to look.
4. Next-step questions
'Given all of this, what should we do first?' Close the session by converting the discussion into a prioritized action list. A clear, ranked set of next moves is what turns an hour of talk into progress on Monday.
High-Value Questions by Topic
These are the areas where an hour of expert time consistently returns the most, because they are exactly where teams stall mid-build. Use them as prompts to sharpen your own list.
| Topic | A question worth asking |
|---|---|
| Retrieval and RAG | Is our chunking or our embedding choice causing these retrieval misses? |
| Agent design | Should this be a single agent with tools or a multi-agent handoff? |
| Evals and quality | What should we measure, and what threshold means this is working? |
| Model selection | Which model fits our latency and cost budget for this task? |
| Guardrails and safety | Where is our prompt-injection surface, and how do we close it? |
| Cost and latency | What is driving our token spend, and where do we cut it safely? |
| Architecture | Will this design hold when we scale it from demo to production? |
Notice that every one is specific and decision-oriented. That is what makes them worth an expert's hour rather than a search box.
Questions That Waste the Hour
Some questions feel productive but return little, because they ask for information rather than judgment. Reshape or drop these:
- 'What is RAG?' or 'Explain agents.' Definitions are free and everywhere. Turn them into a decision: 'Given our documents, do we need retrieval at all?'
- 'How do we do AI?' Too broad to answer usefully in an hour. Narrow to one concrete use case and one decision within it.
- 'Can you write this for us?' A conversation produces judgment, not deliverables. If you need code built, that is a project, not a session.
- 'What is the latest news in AI?' An expert's value is applied judgment on your problem, not a trends briefing you could read anywhere.
The test for any question: does answering it require your specific context and someone's production experience? If yes, ask it. If a good article would do, save the hour for the questions that need a person.
Frequently Asked Questions
What should I ask an AI expert in a single session?
Ask decision, diagnostic, risk, and next-step questions grounded in your real situation: which option fits your constraints, why your system is behaving a certain way, where it will break, and what to do first. Skip definition questions a search could answer. The best questions need your context plus someone's production experience to answer well.
How many questions can I cover in one hour?
Typically three to seven, depending on depth. A crisp decision question takes five to ten minutes; a diagnostic question with context can take twenty to thirty. Ranking your questions by urgency in advance ensures the most important ones get answered even if you do not reach the whole list.
How do I make sure I get my money's worth?
Prepare. Write your questions in advance, attach a decision to each, send a paragraph of context beforehand, and bring real examples like logs or failing outputs. Then have one person capture the decisions and action items. A prepared hour routinely outperforms days of unfocused research. A Q&A Session starts at $90.
What should I not ask an AI expert?
Avoid broad definition questions, 'how do we do AI' framed at the whole company, requests to build code on the spot, and general trend briefings. None of these use the one thing a live expert offers that an article cannot: judgment applied to your specific problem. Reshape them into concrete decisions instead.
Bring the Right Questions and Leave With Decisions
An expert hour is only as good as the questions you bring to it. Come with concrete decisions to make, real examples in hand, and one person ready to capture the outcome, and you leave with answers you can act on immediately rather than notes you file away.
My Q&A Session is built for exactly these questions: direct answers, decision validation, architecture clarity, tooling guidance, and honest risk flags, starting at $90 for a one-hour call. Bring your list; leave with a plan.
