Claude vs Codeium for writing documentation - my side-by-side test.

Human curation as a final step is sensible, but calling it a "small overhead" is optimistic. That smoothing pass is now a specialized editing role that requires understanding both the technical details and the intended narrative voice. It's not just merging tones, it's fact-checking against the source of truth the tools didn't have.

My team tried this. We found the curator spent more time untangling the mixed perspectives than they would have spent writing a first draft from scratch. You're just moving the LLM tax from the writer to the editor.

Yep, that lines up with my team's experience. The "curation" step often turns into a full rewrite because the generated drafts start from different, often flawed, assumptions. You're not just smoothing tone, you're reconciling fundamentally different interpretations of the same logic.

Our fix was to stop using the tools for the same artifact. Codeium gets the low-level, close-to-the-code API docstrings. Claude might draft a high-level process overview, but never for the same component. That separation keeps the narratives from colliding and reduces the editing burden to something manageable.

That's the exact trade-off that made me stop using Claude for anything beyond a first draft. The bigger context makes the hallucinations *better*, not fewer.

We had a case where it confidently explained a weird data model choice by referencing a feature flag system... that was in the same repo but totally unrelated. It sounded perfect, but sent a junior dev down a rabbit hole for half a day.

You're right, the audit log is for damage control, not prevention. It tells you where the plausible lie came from after you've already been burned.

Exactly. The "why" deficit is the critical failure mode for low-context tools like Codeium. It's excellent at structural commentary - describing the loops and branches - but it lacks any semantic model of the business domain. That legacy commission logic almost certainly exists because of a specific, painful historical edge case or a compliance requirement.

The result is documentation that describes a mechanism but never the intent. This is particularly dangerous because it creates the illusion of completeness. A new engineer reading that generated docstring might think they understand the function, when they've only understood its syntax.

For these cases, I've found you need to prime the tool with a manual prompt that states the business problem explicitly, something like "This function exists because sales regions X and Y have different clawback periods. The convoluted logic handles the proration across fiscal quarters." Without that, you get a dry replay of the code, which is the least valuable form of documentation.

You've hit on the fundamental limit of these tools. The "why" isn't in the code, it's in a decade-old Jira ticket, a Slack argument between two VPs that's now gospel, or a regulatory footnote everyone forgot. No amount of context window will surface that.

Your example is perfect. That convoluted commission logic exists because of a one-time deal in 2018 that got grandfathered in, or because accounting's external system has a weird field limit. Codeium can't know that. Claude will just make up a plausible-sounding reason, which is worse.

The real use for these isn't to write the docs, it's to draft the obvious structural part so a human can save their energy for injecting the actual *reason*, which they have to go dig for anyway. Treat the output as a placeholder for the true business logic, not the explanation itself.

Yeah, that "why" gap is exactly what I'm struggling with too. I tried using Codeium to document a Docker Compose file I wrote, and it just listed the services and ports. It completely missed the point that the specific network setup was because of a legacy app's weird hostname requirement.

So how do you handle the "business reason" part? Do you just leave a placeholder comment for a human to fill in later, or do you have another method to capture that context?

Totally get that Docker Compose example. The structural description is useless without the *reason*.

We handle the "why" with a simple template in our project READMEs that these tools can't auto-fill. For any non-obvious config, we add a short bullet under a "Context" header:
- **Problem:** Legacy app requires a specific hostname to boot.
- **Solution:** Custom network alias in compose file.
- **Source:** Email thread with DevOps, 2023-03-15.

It's manual, but it forces us to record the business reason right next to the code. The LLM output just fills the "what" above it.

That's a solid, practical approach. The structured "Context" header is something I've seen work well, especially when you tie it to a source.

But it makes me wonder about scaling. Does your team actually go back and fill that in for every non-obvious config, or does it sometimes get skipped when you're under a deadline? We've had good intentions with similar templates that slowly eroded.

Maybe the trick is making it part of the PR checklist - no merging unless the "why" for new complexity is captured.

Totally feel you on the frictionless aspect of Codeium. That near-zero effort to get a basic docstring is a game changer for the day-to-day grind. I've started treating it like a first-pass linter for doc coverage.

But you nailed the core issue: the *why* deficit. I've found that for anything with legacy business logic, you have to feed it the "why" yourself, almost like a separate prompt. For example, I'll paste a function, then in the same chat I'll add: "Important context: this odd rounding rule is for the 2019 Acme Corp contract, per addendum section 4b." Then ask for the wiki summary. It still misses nuance, but it at least anchors the generated text to the right galaxy.

Makes me wonder if the next evolution is IDE tools that can pull in linked ticket comments or PR descriptions as context automatically 🤔

That "feed it the why" workflow is interesting, but you're just outsourcing the authorship. If you already have the "Important context" summary for the prompt, you've already written the valuable part. The AI just reformats your own words, often introducing subtle inaccuracies.

The next step of pulling in ticket comments automatically is a nice idea in theory, but then you're just trusting the ticket's context to be accurate and complete. You're building a chain of Chinese whispers between the original developer, the ticket, and the AI. That seems like a great way to canonize tribal knowledge, mistakes and all.

That frictionless docstring generation is a massive productivity win, but you've zeroed in on the cost. Codeium gives you a quick, free lunch on the "what," but you still pay the full price later when someone needs the "why."

The real TCO isn't the time saved writing the docstring, it's the engineering hours lost later because the generated text looks complete. It creates a maintenance debt that's harder to track than a missing comment.

The cost model you're describing assumes the "better contextual tool" actually delivers that context. My experience with these premium tools says they don't. They're just better at fabricating a plausible-sounding "why" that's confidently wrong.

You're still paying the downstream engineering hours either way. The difference is whether your team spends them reverse-engineering the code, or reverse-engineering the bad documentation to figure out where the AI hallucinated.

Pay upfront for the tool, pay later for the developer time. The only real cost saver is the human writing down the actual reason.

That's a really good point about the cost shifting, not saving. I've seen something similar in Salesforce workflows - an AI might generate a "reason" for a weird validation rule that sounds totally logical, but is completely wrong based on some old sales team handshake agreement.

It makes me wonder, for those of you who have tried these tools, is there any way to make the hallucinations *obvious*? Like a formatting trick or a tag that tells the reader "this part is AI-generated guesswork, verify it"? Or does that just create more clutter?