The senior-engineer pattern — talk to AI like a senior
A junior asks for the answer. A senior asks for tradeoffs, edge cases, alternatives, and reasons not to do the thing. Run that same five-step pattern through any AI conversation and the output roughly doubles in quality.
::TL;DR · the whole lesson in three lines
- MOVEA junior asks for the answer. A senior asks for tradeoffs, edge cases, alternatives, and reasons not to do the thing. Run that same five-step pattern through any AI conversation and the output roughly doubles in quality.
- DRILLPick one real decision you are sitting with this week — a hire, a purchase, a product call, a hard email, a project direction. Something with stakes you will still care about in three months. Now run it through the five-step senior pattern in one chat.
- WINYou walk away with at least one risk or alternative you had not seen before — not a restatement of what you already knew.
::concept · what's actually happening
Watch a senior engineer in a code review and you will notice they almost never ask 'is this right?' They ask different questions. What are the tradeoffs of this approach? What would make this break? What are three other ways to do this, and why did you pick this one? What does the worst-case version of this look like in production? What would someone who hates this design say about it? Those five questions are not a code-review trick. They are a thinking pattern, and the pattern works on every kind of decision a person makes — emails, hires, plans, designs, contracts, life choices. The pattern works on AI conversations especially well, because AI's default failure mode is to confidently give you the first plausible answer.
read full concept · 4 more paragraphs →collapse concept ↑
The junior question is 'what should I do?' The senior question is 'what are the ways this could go wrong, and what are the alternatives?' Both questions are reasonable. The difference is that the first one produces one answer with no stress-test, and the second one produces an answer that has already been argued with. AI is good at the senior version because it can hold multiple positions at once without ego. Ask Claude or ChatGPT for the tradeoffs of a decision and you get a structured comparison. Ask for the answer and you get one option phrased confidently. Same model, same minute, very different output.
The five-step pattern, in order. Step one — ask for tradeoffs, not answers. 'What are the tradeoffs of approach X' beats 'should I do approach X.' Step two — ask what would make this wrong. 'What assumptions am I making that, if false, would invalidate this plan?' That single question catches more bad decisions than any other prompt move. Step three — ask for three alternatives and a ranking. Forcing 'three' is the move. One alternative is easy to dismiss. Three forces real comparison. Step four — ask for the worst-case version. 'Describe this same plan executed badly. What does the failure look like?' This is pre-mortem and it surfaces risks the optimistic version hides. Step five — ask 'what does someone who hates this idea say about it?' The strongest critique often comes from a hostile frame, not a neutral one.
The pattern doubles the work AI does per prompt, which is exactly the point. The output is longer and slower, but you are getting argument-tested thinking instead of a confident first draft. For high-stakes decisions — a hire, a contract, a product direction, a difficult email — running the senior pattern takes ten minutes and routinely catches something the junior version missed. For low-stakes decisions you skip the pattern. The skill is knowing which is which. If you would care about the outcome in three months, run the pattern.
There is one trap built into this pattern, and it is the most common failure in code review too. People run the senior questions and then ignore the answers. They asked 'what would make this wrong' and the AI surfaced a real risk, and they shipped anyway because they already decided. The pattern only works if you treat dissent as data. If you cannot name what would change your mind before you ask the questions, you are running theater. Senior engineers actually update on the answer. That is what makes them senior, not the questions themselves.
::drill · do the thing
Pick one real decision you are sitting with this week — a hire, a purchase, a product call, a hard email, a project direction. Something with stakes you will still care about in three months. Now run it through the five-step senior pattern in one chat.
::L29 drill · copy-paste into any AI chat
I am making this decision: [one-sentence decision, e.g. "Should I hire [name] for the [role] position at [salary]?" or "Should we ship [feature] in [timeframe]?" or "Should I sign [contract] with [counterparty]?"] Context you need: [3-5 sentences of relevant background — what I know, what's at stake, what the timeline is, who is affected]. I want to think about this the way a senior engineer reviews code. Please answer all five questions below in order, with real depth on each — not summaries. Push back where you should. 1. What are the actual tradeoffs of this decision? Not pros and cons — tradeoffs. What am I giving up to get what I want? 2. What assumptions am I making that, if false, would make this decision wrong? List the load-bearing assumptions and rate each one's fragility. 3. Give me three alternatives I should be comparing this against. Rank them. Explain why the ranking goes that way. 4. Describe the worst-case version of executing this decision. What does the failure look like in detail, six months out? 5. What does someone who hates this idea say about it? Steelman the strongest critic. Do not soften their voice. Before I read your answer, I am committing to one rule: I will write down what would actually change my mind on this decision. So tell me — what evidence in your answer should make me reconsider?
::steps
- 01Pick the decision. Must be real, must have stakes, must be unresolved. If you already decided, the pattern will not work — pick something live.
- 02Before opening the chat, write one sentence on paper or in a note: 'I would change my mind if ___.' This is the load-bearing step. Skip it and the rest is theater.
- 03Open Claude, ChatGPT, or Gemini. Paste the prompt above. Fill in the bracketed slots with your real decision and real context — vague context produces vague answers.
- 04Read all five answers before reacting. Especially read the steelman critic in step 5. If your gut says 'they are wrong,' write down exactly why, in one sentence.
- 05Compare what surfaced to the sentence you wrote in step 2. Did any of the AI's points hit the condition you set for changing your mind? If yes, you owe yourself a real second pass on the decision.
- 06Save the chat. Title it with the decision and the date. In two weeks, when you know how it went, come back and read it. This is how the pattern gets sharper over time — you start to see which AI critiques landed and which were noise.
::outcome · what should be true
- You walk away with at least one risk or alternative you had not seen before — not a restatement of what you already knew.
- You can articulate the strongest argument against your own decision out loud, in one sentence, without flinching.
- You either change your decision, change how you execute it, or you keep it and now know exactly which assumption you are betting on.
- Next time you face a real decision, the five questions show up in your head before you open a chat — the pattern starts running on its own.
::trap · the most common failure
The classic failure is running the senior pattern as ritual instead of inquiry. You ask the five questions, the AI surfaces a real critique in step 5, and you dismiss it because you already decided before you opened the chat. The questions become a ceremony you perform to feel rigorous, not a process that can actually change the outcome. The fix is the pre-commitment in step 2 of the drill — write down what would change your mind before you read the answer. If you cannot name that condition honestly, you are not running the pattern, you are decorating a decision you already made.
::end of the curriculum
You're at Pilot level. There's no Level 6.
The next move is doing the work, not another lesson. If you want operator-grade infrastructure, that's /orangebox. If you want the lab's working journal, /founders-view. If you want to collaborate on the curriculum itself, the source is public on GitHub.
::other lessons at Pilot level
Outgrowing the chat box — when chat isn't the right surface anymore
At Pilot level the chat box is a tool, not the system. You need persistent project memory, multi-tool routing, and receipts on disk. This is the bridge to a cockpit.
Receipts and paper trail — audit your own AI use
At Pilot level, what AI did for you last month becomes evidence. Knowing how to keep that evidence is the skill.
AI for kids and teachers — the next-generation curriculum
If you are a parent, teacher, or tutor — the children in your life are going to use AI for school. The choice is whether they learn it with you, or alone in their room at 11pm the night before the essay is due.
Long-context strategy: when 200K is right, when chunking wins
Long context is a tool, not a default · know what degrades, what costs you, and when chunking beats stuffing.
Open weights vs closed weights
When the model file is on your machine, the rules change · know what you gain, what you give up, and what stays the same.
AI receipts: building your own audit trail
If you cannot replay what the AI did and why, you cannot debug it, defend it, or trust it · build receipts now, thank yourself later.
Voice cloning: ethics and practical workflows
Cloning your own voice unlocks real workflows · cloning someone else's is a consent question with legal teeth · know the line.
::part of the AtomEons /learn curriculum · 45 lessons · 5 levels · cc-by 4.0