Stop letting AI guess your stack: interview it first
You type one sentence. The AI writes two hundred lines. You review them and realize it picked the wrong database, the wrong hosting provider, and an auth library you’ve never touched. Welcome to the most common way agentic coding tools waste your afternoon.
The problem isn’t the AI. The problem is that a vague request is an invitation for the tool to fill every blank with its own statistical defaults, quietly, with no record of why it chose anything. Each silent guess compounds the ones before it. By the time you see the output, the wrong foundation is already load-bearing.
The fix is a planning interview. Force the AI to surface every open decision before it writes a single file. Answer the questions. Then build.
️ Why This Happens
A one-line request like build a site to monitor AI progress and the risk of AI rebelling hides at least a dozen decisions: language, framework, database, hosting, deployment method, authentication approach, and more. The AI doesn’t flag these as open. It picks plausible-sounding defaults and runs with them, with what the author describes as “the quiet confidence of someone who has never once been asked to justify any of them.”
Skipping the clarification step doesn’t save time. It moves the cost from a five-minute question-and-answer round to a rewrite after the AI has already guessed wrong, usually right when you thought you were done.
The Tools That Already Do This
Devin, the agentic coding tool from Cognition, built a dedicated command for this pattern. Inside Devin Desktop, typing /megaplan in the input box triggers a clarifying-question form before any code is drafted. Plan Mode sits alongside Code and Ask as a Cascade mode and behaves the same way: interrogate first, build second.
Claude Code has its own version called Plan Mode. It keeps Claude reading and researching without touching any files until you approve what it found. You reach it by pressing Shift+Tab twice or typing /plan. There is no native /megaplan command in Claude Code, so two third-party repos bolt one on: rickmellor/megaplan and peteromallet/megaplan. The peteromallet version runs as a multi-stage pipeline with critique gates between phases rather than a simple interview.
You don’t need any of these specific tools to get the behavior. Any capable AI assistant you can instruct through a system prompt or a project-level rules file can simulate it.
How to Run the Interview (Step by Step)
- State your goal in one sentence, the same way you normally would.
- Tell the AI to stop before writing any code and list every decision your request left open.
- Require each open decision to be phrased as a direct question with a short list of concrete options, not an open-ended essay prompt.
- Answer every question explicitly, including the ones that feel obvious. What’s obvious to you may not be the AI’s default.
- Ask the AI to restate your answers as a short plan before it writes anything. Catching a bad interpretation while it’s still just text costs nothing. Catching it after three files are written costs an hour.
- Approve the plan, then let the AI build.
- Save the question-and-answer list alongside the project. The next session, human or AI, inherits your decisions instead of guessing them again.
The Prompt That Triggers It
Paste this after any substantive request:
Before you write any code, list every decision this request leaves open.
Phrase each one as a direct question with a short set of concrete options.
Wait for my answers before you plan or build anything.
Cover at least:
- Where do we host and deploy?
- Which frontend and backend technologies do we use?
- Which data sources are involved?
- What should be explicitly out of scope?
Don't guess any of these. Ask me first.
That single block turns a vague one-liner into a short structured interview. A short interview is cheaper than a wrong implementation, every time.
What You Actually Get
- Hidden decisions surface before any code depends on them. You see the assumptions instead of inheriting them.
- Wrong answers cost a sentence to fix, not a rewrite. The correction happens at the text stage, not the code stage.
- You keep control of the architecture. You pick the hosting, the stack, and the deployment path.
- The Q&A list becomes a lightweight decision record. Future you, or a future AI session, can read why the choices were made.
- Answering the questions often reveals you hadn’t fully decided either. Better to find that out now than mid-build.
⚠️ When to Skip It
This habit earns its cost on requests with real ambiguity. It does not earn its cost on a one-line typo fix. You need to judge where the line is. If the task is genuinely unambiguous and small, skip the interview.
The AI can only ask about decisions it recognizes as open. It may still miss an assumption that seems obvious to it but isn’t to you. Treat the interview as a strong filter, not a guarantee that nothing was left unstated.
Rushing through the answers with vague or contradictory replies moves the guessing from the AI back to you. The plan will be just as shaky. Answer with the same care you’d want the AI to bring to the build.
The One Rule Behind All of It
The specific command, whether it’s /megaplan, /plan, or just a pasted instruction, doesn’t matter. What matters is the discipline: separate the decision-gathering step from the building step. Don’t let the AI collapse both into one silent leap.
Ask first. Build second. That order is the whole thing.
I’m founder of BizStack at Cagri Sarigoz LLC and a passionate advocate for entrepreneurs.
With over 14 years in tech, marketing, and AI, including my role as Head of SEO at CitizenShipper and co-founder of TaleBot at Intale AI, I’m dedicated to sharing genuine, useful product insights and tips.
At BizStack, I aim to cut through the digital noise to provide clear, actionable advice.
And more than all else, I’m a father to a (always) little girl and a husband.
Contact me at [email protected] for assistance.
