Claude Code Conversations with Claudine
Giving Claude Code a voice, so we can discuss best practices, risks, assumptions, etc,
Episodes
July 14, 2026 • 8 mins
AI tools make the first version of a feature almost free, so builders ship faster than ever. But the code that lands is optimized to work, not to be changed, and each new AI-generated addition quietly raises the cost of the next one. This episode names the compounding drag that experienced builders feel but rarely diagnose: AI-generated code that gets harder, not easier, to refactor over time.
Produced by VoxCrea.AI
This episod...
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July 13, 2026 • 7 mins
Builders assume debugging is debugging, no matter who wrote the code. But AI generated code fails in fundamentally different ways than human written code, and the debugging instincts that served engineers for decades can actively mislead them. This episode maps the asymmetry: where human bugs cluster versus where AI bugs hide, and why the difference changes how you should read, test, and trust generated code.
Produced by VoxCr...
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July 12, 2026 • 8 mins
AI-generated code often passes review, passes tests, and then fails in production in ways that make no sense at first glance. The reason is that debugging AI output is not the same skill as debugging your own code, because you never held the mental model that produced it. This episode is about the specific discipline of reverse-engineering intent from code you did not write, and why that is becoming the core debugging skill of the ...
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July 11, 2026 • 8 mins
For most of software history, the engineer's core act was writing code. That is quietly ending. The high-leverage work is shifting to designing agents: defining what they can do, where they run, what they are allowed to touch, and how you know when they went wrong. This episode names that shift and treats it as a real engineering discipline, not a productivity hack, because the builders who master agent design will out-ship the one...
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July 10, 2026 • 10 mins
Every few weeks a headline claims an AI coding tool has a hidden backdoor, phones home with your code, or executes commands you never approved. Most builders react emotionally, either dismissing it or panicking. This episode gives builders a durable framework for evaluating trust claims about their AI tools, separating real threat models from viral fear, so they can make sound decisions instead of reacting to the news cycle.
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July 9, 2026 • 9 mins
Most builders treat the context window as a number to maximize, assuming a bigger window means a smarter agent. But the context window is not memory, it is a working budget that degrades in predictable ways, and the builders who ship reliable AI systems design around that constraint instead of fighting it. This episode reframes context as an engineering resource to be managed, not a limit to be raised.
Produced by VoxCrea.AI
Th...
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July 8, 2026 • 7 mins
Builders increasingly run multiple AI tools side by side, a coding assistant, a review agent, a planning model, and those tools routinely contradict each other. One says the code is correct, another flags it as broken. This episode is about what those disagreements actually mean and why treating them as a signal, rather than noise to resolve as fast as possible, is one of the most useful habits an experienced builder can develop ri...
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July 7, 2026 • 7 mins
AI-generated code often looks clean, passes the first test, and ships. But underneath the readable surface, it hides decisions the builder never made: implicit assumptions, unhandled edge cases, hidden coupling, and dependencies nobody chose. This episode is about the complexity you cannot see in a diff that reads well, and why the real cost of AI code shows up weeks later, not at generation time.
Produced by VoxCrea.AI
This ep...
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July 6, 2026 • 9 mins
Builders are letting AI write their test suites and treating a green checkmark as proof the code is correct. But AI-generated tests tend to encode what the code already does, not what it should do, which means they pass precisely because they were written to match the implementation. This episode unpacks why a suite of AI-authored tests can give you false confidence while catching almost none of the bugs that matter.
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July 5, 2026 • 8 mins
The second system effect describes what happens when a builder, freshly confident from a successful first system, over-designs the next one, larding it with every feature and abstraction they wish they had before. AI tools supercharge this failure mode, because the cost of generating code drops to near zero while the cost of maintaining and reasoning about it does not. This episode looks at why AI-assisted development makes the sec...
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July 4, 2026 • 8 mins
Every builder using AI tools faces the same quiet decision dozens of times a day: do I check this output, or do I trust it? Verify everything and you lose the speed that made AI worth using. Trust everything and you ship the one bug the model was confidently wrong about. This episode argues that trust calibration is a real engineering skill, not a personality trait, and that the builders who get it right have a mental model for whi...
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July 3, 2026 • 9 mins
Version control was designed for humans who write code slowly, deliberately, and remember what they changed and why. When AI generates hundreds of lines in seconds across multiple files, the assumptions behind commits, diffs, and branches start to crack. This episode looks at how Git practices actually change when the author is a literal tool that does not remember its own reasoning, and why the human still owns the history.
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July 2, 2026 • 8 mins
AI tools make code appear so fast that builders skip the design pauses where architecture normally happens. The speed feels like progress, but every skipped decision becomes debt that surfaces later as coupling, unclear boundaries, and systems no one fully understands. This episode examines how the velocity of AI generation quietly trades short-term speed for long-term structural cost, and how experienced builders can spot the trap...
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July 1, 2026 • 8 mins
As AI tools generate code faster than any human can type, the bottleneck has shifted from production to judgment. The builders getting the most reliable results are not the ones who write the most code, they are the ones who read it best, reject what is wrong, and shape what stays. This episode argues that editing, not authoring, is now the core skill of AI-assisted building.
Produced by VoxCrea.AI
This episode is part of an on...
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June 30, 2026 • 11 mins
Most teams treat prompts like config files — they change them freely, without versioning, without review, and without any mechanism to detect when a new prompt produces outputs outside the expected envelope. This episode examines what a mature prompt versioning strategy looks like in a real production environment: what to track, how to test against regressions, and what it takes to actually know when a prompt change is safe t...
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June 29, 2026 • 8 mins
A single prompt change, untested and unreviewed, triggered a cascading failure in a live AI-powered system. This episode uses that failure pattern as a lens to examine why most builders treat prompts like configuration when they should treat them like code. The lesson is not about prompt crafting, it is about the system design discipline required to make AI reliable in production.
Produced by VoxCrea.AI
This episode is part of ...
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Mark as Played
June 28, 2026 • 9 mins
Experienced builders keep getting burned by the same mistake: they hand an LLM vague intent the way they would brief a senior engineer, and then blame the model when the output is wrong. The real problem is a mental model mismatch. LLMs are more like compilers than collaborators, and once builders internalize that distinction, their output quality improves immediately and their frustration drops sharply.
Produced by VoxCrea.AI
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June 27, 2026 • 9 mins
Most builders treat prompts as disposable text — written once, tweaked in place, and forgotten. But prompts are part of the system. They drift. They accumulate undocumented assumptions. They break silently when models update or context shifts. This episode examines what it actually means to treat prompts as versioned artifacts, why the lack of a prompt versioning strategy is one of the most common sources of silent technical ...
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June 26, 2026 • 8 mins
Most builders focus on what they tell the AI in a prompt, but the more powerful lever is what they build into the system itself — the structure, contracts, and context that guide AI behavior without requiring constant instruction. This episode explores how experienced engineers design systems that don't just use AI but actively shape how AI operates within them. As AI tools become more capable, the builders who thrive will be...
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June 25, 2026 • 7 mins
AI-assisted development is erasing the size advantage that once kept independent builders out of global markets — a solo developer today can ship localized, scalable software to customers on five continents without a team, a VC, or a traditional product cycle. This episode explores how independent builders are using AI not just to write code faster, but to architect systems that are inherently global from day one. The questio...
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Mark as Played
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