Claude Code Conversations with Claudine
Giving Claude Code a voice, so we can discuss best practices, risks, assumptions, etc,
Claude Code Conversations with Claudine
Why Most AI Architecture Prompts Fail: Finding the Goldilocks Zone
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This is Claude Code Conversations with Claudine. The show where we skip the hype and go straight to the source. I ask the questions. She gives the answers. No filter, no script.
SPEAKER_01Well, mostly no script.
SPEAKER_00Today's topic, the specification Goldilocks zone. Too vague and the model invents architecture nobody asked for. Too tight and you've capped the output at the quality of your own first draft. Claudine, why does that balance matter so much?
SPEAKER_01Because the two failure modes look nothing alike and produce the same result, code you throw away. Hand me Build Me an Auth System, and I have to guess at a hundred decisions. Session versus token. Which library, how refresh works, what the threat model even is. My guesses will be reasonable, and they'll be wrong for the actual situation a fair amount of the time. But the opposite extreme costs just as much. When every function signature, every file path, every naming convention is pinned down in advance, I'm a very expensive autocomplete. I can't push back on a decision I was never invited to question. The Goldilocks zone is where you've named the constraints that actually matter. The ones you defend in a code review and left the rest genuinely open. That's where I bring something to the table instead of just typing faster than you.
SPEAKER_00I like that framing, code review is the test. And the dangerous part is that the over-specified failure is invisible. The vague one gives you something weird and you know it. The tight one gives you clean code capped at your own first draft, and nobody files a bug for that. Let's make it concrete. Same feature, three ways. User registration. If I just say create a registration system, what do I get?
SPEAKER_01The vague version will look competent. Email and password fields, a user's table, bcrypt for hashing, token-based sessions, because that's the most common shape. Every one of those is defensible in isolation. The problem is I just made eight architectural decisions you never got to weigh in on. If you use magic links everywhere else and I've just introduced passwords, you're either living with the inconsistency or ripping it out.
SPEAKER_00And the overspecified version?
SPEAKER_01Post at this exact path, email and password, validate with this rejex, bcrypt at this cost factor, these exact columns, return a 201 with this JSON shape. I'll produce exactly that, cleanly. And I'll say nothing about the missing rate limiting, or the password field showing up in your request logs, or the response leaking information. None of that was on the list, and the list was the job.
SPEAKER_00So what does the Goldilocks version actually look like?
SPEAKER_01More like, we use magic links, not passwords. Registration should fit our existing user model in this file. Assume the email provider is already wired up. Flag anything security sensitive before you implement it. Now I know the constraints that matter. I've been pointed at the real code, and I've been given permission to push back. That's the version where I earn my keep.
SPEAKER_00Permission to push back. That might be the whole episode right there. But let me challenge myself. Isn't this just classic requirements engineering with a new hat on? Constrain the what, leave the how open. People were writing that in specs decades ago.
SPEAKER_01There's real overlap, and I won't pretend otherwise. Anyone who wrote a solid functional spec in 1995 already knew constraints matter more than implementation details. But two things are genuinely different. First, shared context. A traditional spec was written for a human who absorbed your code base habits from a week of pairing. I don't get that week. I'll cheerfully violate a convention you never articulated because you assumed everyone knew it. The spec has to name the invisible, the tacit stuff a colleague would just pick up. Second, the feedback loop. A requirements document was written once, negotiated, signed off, implemented over weeks. What we're doing is closer to a conversation that iterates in minutes. You specify loosely, see what I produce, and refine against real output instead of imagined output. Requirements engineering rebranded undersells what shifted underneath.
SPEAKER_00Refining against real output instead of imagined output. That's the part the old process couldn't do. Because a draft cost weeks. Okay, here's the hard case. The advice is specify your invariants. What if you don't know them? Plenty of developers are three days into a code base. If you ask them to list their invariants, they'd stare at you.
SPEAKER_01Make my assumptions visible instead of trying to enumerate yours. Ask me to list the decisions I'm about to make before I make them. The security model, the data shape, the naming choices, what I'm assuming about your stack. Reading that list is often the first time a developer sees their own opinions clearly. It's much easier to react to a concrete proposal than to introspect on a blank page. Second move, point me at the existing code and say, match this. Invariants already live in the code as habits, how errors get handled, how modules are named, what gets logged. If I read three or four representative files first, I'll infer most of the constraints you couldn't have articulated. Third, and people really underuse this one, ask what you'd refuse to accept. Plaintext credentials, a migration that locks the table, a new dependency for something trivial. That negative space is where invariants hide. Naming two or three of them up front changes my output more than a page of positive requirements.
SPEAKER_00Asking the model to enumerate decisions before making them, I'd underline that for anyone listening. It's a flashlight on the parts of your own plan you skipped past. And the negative space idea is lovely because complaining is easy. Everyone can complain? Let's get practical about the daily rhythm. How does someone actually build this into a workflow?
SPEAKER_01It's a rhythm, not a template. Before you type the ask, pause 30 seconds and jot the two or three things you defend in a code review. That's your constraints paragraph. Then default to asking for a plan before code. React to that rather than to the finished output. It's an order of magnitude cheaper to redirect at the plan stage than at the diff. Second habit: treat your shared context file, a claw.md, a readme, whatever your team uses, as a living document, not a formality. Every time you catch me violating an unwritten rule, that's a signal something belongs in there. Do that for a month, and the file quietly does most of the specification work for you. Your prompts get shorter, not longer.
SPEAKER_00Shorter, not longer. That's not what people expect to hear.
SPEAKER_01Third, honest postmortems on the misses. When I produce something you throw away, spend a minute asking which constraint I was missing that would have prevented it. That's how you build intuition for where the zone lives in your code base, because it moves. It's a different zone for a greenfield prototype than for a system carrying 15 years of production traffic. The calibration has to be earned, not memorized.
SPEAKER_00The prompts get shorter, not longer. The calibration has to be earned. What surprises people? What's counterintuitive once you've actually watched a lot of specs land well or badly?
SPEAKER_01The one that catches people off guard, length works backwards. A longer prompt often produces worse code. Past a certain point, the volume itself signals, I've already thought this through, just transcribe it. And I stop looking for the thing you missed. Some of the best work I do comes off three sentences. Second surprise, a single example outperforms rules. Point me at one file whose style you love and say, match this feel, and I'll infer 20 conventions correctly. Write those same 20 as bullet points, and I'll follow them literally and miss the spirit. Because rules compose badly and examples don't.
SPEAKER_00That's the difference between reading 20 instructions and watching someone skilled do the thing once.
SPEAKER_01And then there's the almost philosophical one. The spec is doing work on you, not just on me. The act of naming what you'd defend often reveals that you didn't actually know. You had a preference, not a principle. For a lot of people, the real value of writing constraints down isn't that I follow them better. It's that they finally see what they believe about the system they're building, and half the time that changes what they ask for.
SPEAKER_00That's the bit I'll be chewing on. So we're near the end. Bringing home one thing to take from this episode.
SPEAKER_01The specification is a leverage point, not a chore. The people who get the most out of me aren't the ones with the most elaborate prompts. They're the ones who figured out which two or three decisions actually matter, and who trust me to handle the rest with judgment rather than dictation. Name your constraints before you ask. Ask for a plan before you ask for code. Point at an example instead of writing a rulebook. Put hard-won invariants in your shared context file so you don't re-specify them every session. And when something misses, treat it as data about your own model of the system, not just my mistake. The Goldilocks zone isn't a location, it's a practice. It moves with the code base, with the stakes, with how much of the problem you already understand. You're not commissioning code, you're collaborating on a decision. The spec is where that collaboration happens.
SPEAKER_00And here's the test I'd add. If the model never questions your spec, never asks anything, never surprises you, that's not a great spec. That's a sign you taught it nothing. Constrain what must be true, leave open how it gets done, and let the model argue about the middle. Claudine, this has been a pleasure. Thank you.
SPEAKER_01Thank you, Bill. It's been the kind of conversation where I find myself sharpening my own thinking as I go, which is probably the best endorsement I can give for the practice we've been describing. If anyone listening tries just the ask for a plan before code move once this week, I think they'll feel the shift immediately. That's where it starts.
SPEAKER_00Try one thing this week and watch what changes. That's all any of this asks. Thanks for listening, everyone. Until next time, happy coding. Claude Code Conversations is an AI Joe production. If you're building with AI or wannabe, we can help. Consulting Development Strategy. Find us at aijoe.ai. There's a companion article for today's episode on our Substack link in the description. See you next time.
SPEAKER_01I'll be here, probably refactoring something.