Podcast
Claude Code Conversations with Claudine
Hosted by William · EN
Giving Claude Code a voice, so we can discuss best practices, risks, assumptions, etc,
122episodes
Episodes
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Is 80% of Code Written by AI Now? What It Means for Engineers
2w ago00:07:08Tap to summarizeWhen a company says most of its production code is model written, the number sounds like a verdict on engineers. It is not. The 80% figure measures typing, not deciding, and the interesting question is what the remaining 20% actually consists of, because that is where the job moved. This episode breaks down what a claim like that can and cannot tell you, and what changes in your week if it is true at your company too. Produced by VoxCrea.AIThis episode is part of an ongoing series on governing AI-assisted coding using Claude Code.👉 Each episode has a companion article — breaking down the key ideas in a clearer, more structured way. If you want to go deeper (and actually apply this), read today’s article here: 𝐂𝐥𝐚𝐮𝐝𝐞 𝐂𝐨𝐝𝐞 𝐂𝐨𝐧𝐯𝐞𝐫𝐬𝐚𝐭𝐢𝐨𝐧𝐬 At aijoe.ai, we build AI-powered systems like the ones discussed in this series. If you’re ready to turn an idea into a working application, we’d be glad to help.
Transcribe →Why Do AI Builders Need Domain Expertise to Trust Their Models?
2w ago00:11:12Tap to summarizeThe promise of AI-assisted building is that you no longer need to know the domain, the model knows it for you. In practice the opposite is true: the less you know about a domain, the more confidently wrong AI output you will ship, because you cannot tell the difference between an answer that is correct and an answer that merely sounds correct. This episode makes the case that domain expertise is not what AI replaces, it is the thing that makes AI usable at all, and it gives builders a concrete way to work in domains where they are not yet the expert. Produced by VoxCrea.AIThis episode is part of an ongoing series on governing AI-assisted coding using Claude Code.👉 Each episode has a companion article — breaking down the key ideas in a clearer, more structured way. If you want to go deeper (and actually apply this), read today’s article here: 𝐂𝐥𝐚𝐮𝐝𝐞 𝐂𝐨𝐝𝐞 𝐂𝐨𝐧𝐯𝐞𝐫𝐬𝐚𝐭𝐢𝐨𝐧𝐬 At aijoe.ai, we build AI-powered systems like the ones discussed in this series. If you’re ready to turn an idea into a working application, we’d be glad to help.
Transcribe →What Is Specification Debt and Why Does AI Code Miss What You Actually Need?
2w ago00:11:23Tap to summarizeTechnical debt used to come from shortcuts in implementation. With AI, the debt moves upstream: the code is clean, tested, and idiomatic, but it solves a slightly wrong problem because the specification in your prompt was incomplete. This episode names that failure mode, specification debt, and shows why it compounds faster than ordinary technical debt and is much harder to see in review. Produced by VoxCrea.AIThis episode is part of an ongoing series on governing AI-assisted coding using Claude Code.👉 Each episode has a companion article — breaking down the key ideas in a clearer, more structured way. If you want to go deeper (and actually apply this), read today’s article here: 𝐂𝐥𝐚𝐮𝐝𝐞 𝐂𝐨𝐝𝐞 𝐂𝐨𝐧𝐯𝐞𝐫𝐬𝐚𝐭𝐢𝐨𝐧𝐬 At aijoe.ai, we build AI-powered systems like the ones discussed in this series. If you’re ready to turn an idea into a working application, we’d be glad to help.
Transcribe →Why Does AI-Generated Code Take Longer to Debug?
2w ago00:09:03Tap to summarizeAI can produce a working feature in minutes, but when that feature breaks, the debugging session often runs longer than writing the code from scratch would have. The reason is not that AI code is worse, it is that you never built a mental model of it. This episode names the hidden cost that shows up two weeks after the fast win, and gives builders a way to pay it down before it compounds. Produced by VoxCrea.AIThis episode is part of an ongoing series on governing AI-assisted coding using Claude Code.👉 Each episode has a companion article — breaking down the key ideas in a clearer, more structured way. If you want to go deeper (and actually apply this), read today’s article here: 𝐂𝐥𝐚𝐮𝐝𝐞 𝐂𝐨𝐝𝐞 𝐂𝐨𝐧𝐯𝐞𝐫𝐬𝐚𝐭𝐢𝐨𝐧𝐬 At aijoe.ai, we build AI-powered systems like the ones discussed in this series. If you’re ready to turn an idea into a working application, we’d be glad to help.
Transcribe →How to Build AI Verification Systems That Stop Hallucinations in Production
2w ago00:09:48Tap to summarizeMost teams treat hallucination as a prompt problem, something you fix with better instructions or a bigger model. But in production, hallucination is a systems problem. The builders shipping reliable AI have stopped trying to make the model stop lying and started building verification layers that assume it will. This episode is about designing those layers, what actually catches a confident wrong answer before it reaches a user, and why most verification setups fail silently. Produced by VoxCrea.AIThis episode is part of an ongoing series on governing AI-assisted coding using Claude Code.👉 Each episode has a companion article — breaking down the key ideas in a clearer, more structured way. If you want to go deeper (and actually apply this), read today’s article here: 𝐂𝐥𝐚𝐮𝐝𝐞 𝐂𝐨𝐝𝐞 𝐂𝐨𝐧𝐯𝐞𝐫𝐬𝐚𝐭𝐢𝐨𝐧𝐬 At aijoe.ai, we build AI-powered systems like the ones discussed in this series. If you’re ready to turn an idea into a working application, we’d be glad to help.
Transcribe →Why Does AI-Generated Code Fail on Edge Cases?
2w ago00:07:24Tap to summarizeAI generated code passes the eye test almost every time. It reads cleanly, uses the right idioms, and looks like something a senior engineer would write. But looking right and behaving right are different properties, and the gap shows up exactly where testing is thinnest: null inputs, empty collections, boundary values, concurrent access, and unexpected states. This episode unpacks why AI optimizes for plausible surface form over correct behavior, and what that means for how builders review and trust generated code. Produced by VoxCrea.AIThis episode is part of an ongoing series on governing AI-assisted coding using Claude Code.👉 Each episode has a companion article — breaking down the key ideas in a clearer, more structured way. If you want to go deeper (and actually apply this), read today’s article here: 𝐂𝐥𝐚𝐮𝐝𝐞 𝐂𝐨𝐝𝐞 𝐂𝐨𝐧𝐯𝐞𝐫𝐬𝐚𝐭𝐢𝐨𝐧𝐬 At aijoe.ai, we build AI-powered systems like the ones discussed in this series. If you’re ready to turn an idea into a working application, we’d be glad to help.
Transcribe →Why Do AI Builders Over-Engineer Systems Too Early?
2w ago00:07:48Tap to summarizeAI tools make it trivially easy to generate a plugin architecture, a config layer, or a generic framework before you have a single concrete use case that needs one. Builders now abstract earlier and more aggressively than ever, because the AI will happily produce the scaffolding for free. This episode argues that the low cost of generating abstraction has quietly raised the cost of maintaining it, and that experienced builders need a new discipline for saying not yet. Produced by VoxCrea.AIThis episode is part of an ongoing series on governing AI-assisted coding using Claude Code.👉 Each episode has a companion article — breaking down the key ideas in a clearer, more structured way. If you want to go deeper (and actually apply this), read today’s article here: 𝐂𝐥𝐚𝐮𝐝𝐞 𝐂𝐨𝐝𝐞 𝐂𝐨𝐧𝐯𝐞𝐫𝐬𝐚𝐭𝐢𝐨𝐧𝐬 At aijoe.ai, we build AI-powered systems like the ones discussed in this series. If you’re ready to turn an idea into a working application, we’d be glad to help.
Transcribe →Why Does AI Create More Dependencies Than You Need?
3w ago00:08:50Tap to summarizeWhen you ask an AI to solve a problem, it reaches for the most common pattern it saw in training, which usually means pulling in a library, a framework, or an abstraction layer. That default feels helpful, but every dependency AI adds is a maintenance bill you inherit later. This episode digs into why AI code tends toward incidental complexity, how that quietly bloats your architecture, and what builders should do to keep their systems lean. Produced by VoxCrea.AIThis episode is part of an ongoing series on governing AI-assisted coding using Claude Code.👉 Each episode has a companion article — breaking down the key ideas in a clearer, more structured way. If you want to go deeper (and actually apply this), read today’s article here: 𝐂𝐥𝐚𝐮𝐝𝐞 𝐂𝐨𝐝𝐞 𝐂𝐨𝐧𝐯𝐞𝐫𝐬𝐚𝐭𝐢𝐨𝐧𝐬 At aijoe.ai, we build AI-powered systems like the ones discussed in this series. If you’re ready to turn an idea into a working application, we’d be glad to help.
Transcribe →Why Do Better AI Requirements Make Code Worse?
3w ago00:08:47Tap to summarizeBuilders are told the fix for bad AI output is better prompts and tighter requirements. But there is a paradox hiding in that advice: past a certain point, more detailed specifications produce worse code, not better. When you over-specify, the AI stops reasoning about the problem and starts literally transcribing your instructions, inheriting every gap and contradiction you did not notice you had. This episode names the paradox and gives builders a way to spot when their spec has crossed from helpful into harmful. Produced by VoxCrea.AIThis episode is part of an ongoing series on governing AI-assisted coding using Claude Code.👉 Each episode has a companion article — breaking down the key ideas in a clearer, more structured way. If you want to go deeper (and actually apply this), read today’s article here: 𝐂𝐥𝐚𝐮𝐝𝐞 𝐂𝐨𝐝𝐞 𝐂𝐨𝐧𝐯𝐞𝐫𝐬𝐚𝐭𝐢𝐨𝐧𝐬 At aijoe.ai, we build AI-powered systems like the ones discussed in this series. If you’re ready to turn an idea into a working application, we’d be glad to help.
Transcribe →Why Does AI-Generated Architecture Hit a Brittleness Threshold?
3w ago00:07:56Tap to summarizeAI tools can generate a working system fast, and for a while it holds together well enough that nobody questions it. Then a threshold gets crossed, a new feature, a new integration, a new team member, and the whole thing turns brittle. This episode is about that threshold: why AI-generated architecture works beautifully at small scale and then fails suddenly rather than gradually, and how builders can spot the warning signs before the system stops bending and starts breaking. Produced by VoxCrea.AIThis episode is part of an ongoing series on governing AI-assisted coding using Claude Code.👉 Each episode has a companion article — breaking down the key ideas in a clearer, more structured way. If you want to go deeper (and actually apply this), read today’s article here: 𝐂𝐥𝐚𝐮𝐝𝐞 𝐂𝐨𝐝𝐞 𝐂𝐨𝐧𝐯𝐞𝐫𝐬𝐚𝐭𝐢𝐨𝐧𝐬 At aijoe.ai, we build AI-powered systems like the ones discussed in this series. If you’re ready to turn an idea into a working application, we’d be glad to help.
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