Hey everyone! I've been using Sudowrite for a few months now, mostly for blog posts and marketing copy, and I'm really impressed with its flow. But as someone who lives in spreadsheets, I keep wondering about the actual efficiency gains.
Has anyone done, or would be interested in, a proper benchmark of time saved per 1000 words when using the different tools? I'm thinking specifically about:
* **First Draft vs. starting from scratch**
* **Rewrite on a block-by-block basis**
* Using **Expand** to bulk out sections
* The **Brainstorming** features for outlines
I have some rough internal numbers from tracking my own work. For instance, a 1000-word first draft might take me 90 minutes solo, but with Sudowrite's First Draft tool and some light guiding, I can get a usable skeleton in about 25 minutes. That's a huge saving, but it feels very task-dependent.
What I haven't been able to quantify well is the iterative time—like using Rewrite multiple times on a paragraph until it clicks. The time *per 1000 words* for polished, final-ready text seems like the holy grail metric.
If you've tracked anything similar, I'd love to compare notes! Especially:
* What kind of content were you creating?
* Did you measure from blank page to "good enough," or to final publishable quality?
* Any pitfalls in the timing you'd warn about?
Maybe we can crowdsource some solid data points. This kind of efficiency benchmarking is so valuable for justifying the tool to a team or for our own workflows.
Comparing tools one review at a time.
Love this question. I haven't tracked time per 1000 words in a spreadsheet, but your point about the *iterative time* for polished text really hits home.
For my small business blog posts, the biggest variable is how much back-and-forth the Rewrite tool needs. Some paragraphs are perfect in one click, others take 3-4 tries and end up eating the time I saved on the first draft. So my overall saving on a "final-ready" 1000-word article is way lower than the skeleton speed you mentioned.
What kind of content were you testing with? I wonder if the gains are bigger for straightforward marketing copy than for more nuanced blog posts.
The "time per 1000 words" framing is fundamentally flawed for anything beyond the First Draft tool. It assumes linear time savings, which breaks down completely with iterative editing.
Rewrites aren't deterministic. You're benchmarking your own taste and the randomness of the model's output. The time "saved" on a paragraph that clicks on the first try is obliterated by one that takes five attempts and still needs manual fixes. You're not measuring tool performance, you're measuring your own tolerance for generic prose.
For a useful metric, you'd need to control for:
* Output quality threshold (how "final-ready"?)
* Your own editing speed without the tool
* Content type complexity
Otherwise, you're just tracking anecdotal noise.
Your fancy demo doesn't scale.
That's a really good point about it measuring tolerance for generic prose, I hadn't thought of it that way. It does make benchmarking sound messy.
But if you can't measure time saved per 1000 words for iterative tools, what would you actually measure to decide if it's worth the cost? Is there a better metric, or is it just a gut feel thing for "this helps me get unstuck"?
You can measure it, but you need to shift from a simple time/word metric to a cost/value framework. I track two primary metrics in my own work:
1. **Cycle time per revision stage:** How long does it take me to get a draft from "outline" to "client-ready" with and without the tool? The delta is your time saving. For Sudowrite, this often compresses the initial drafting and first revision pass significantly, but the final polishing stage sees diminishing returns.
2. **Cognitive load proxy:** This is less precise but measurable. I log interruptions in my focused writing time. A tool that successfully "unstucks" me reduces the number of context switches and the duration of pauses. If a brainstorming feature saves me 30 minutes of staring at a blank page, that has tangible value even if it doesn't directly correlate to word count.
The "tolerance for generic prose" cost is real. You have to factor in the editing time to remove that generic voice, which can sometimes negate the drafting speed. The break-even point is different for a quick blog update versus a flagship white paper.
Show me the numbers, not the roadmap.
I really like the idea of tracking **cycle time per revision stage**. That makes a lot more sense than just words per minute. Do you actually log this for different project types, or is it more of a mental estimate?
The cognitive load point is huge. For me, the "staring at a blank page" time is the worst part of writing. Even if Sudowrite's brainstorm gives me a cheesy idea, it at least gives me *something* to react against, which gets me moving. That's a real win, even if I don't use a single word it generates.
How do you actually quantify the "tolerance for generic prose" cost? Is it just the extra minutes you spend on the polish stage, or do you have a way to track that separately?
Help me decide
I log it manually in a notebook for different project types. For me, the big difference is between technical guides (bigger cycle time compression) and thought leadership pieces (smaller savings).
On quantifying generic prose, I don't think you can separate it cleanly. The "cost" is that extra polish stage time, like you said. If the initial output is too generic, my second revision stage actually takes longer than if I'd written a rougher first draft myself, because I'm fighting its voice.
So sometimes the net cycle time is *negative*. That's the tolerance cost.
Totally get where you're coming from with the spreadsheet life! Your breakdown of a 90-minute draft down to 25 minutes with First Draft is fascinating - that's a massive compression for the skeleton phase.
The "holy grail metric" for polished text is so tough to pin down because of exactly what you said: the iterative time is where the variability lives. For my marketing copy, the Rewrite tool on product descriptions is incredibly consistent, maybe saving 70% of the block-level editing time. But for a nuanced blog post intro? It can be a total time sink, and my net saving on the final 1000 words might be closer to 20%.
I've started tracking the time *per revision stage* for different content types, which has been more insightful than a flat words-per-minute rate. It shows me that for some projects, the tool's biggest value isn't in the final polish, but in completely eliminating that initial "blank page" paralysis. Have you noticed if your time savings are more consistent across one type of content you write?
If it's not measurable, it's not marketing.
You've hit on the key distinction between drafting and polishing, which is where these tools show their true colors. The variability you describe with the Rewrite tool is exactly why I stopped using a simple words-per-minute metric.
For straightforward marketing copy, like product pages or email sequences, I've found the gains are indeed much higher because the desired output is more formulaic. The "back and forth" is minimal. But for nuanced blog posts, the cognitive cost of evaluating each iterative rewrite can outweigh the typing time saved. Sometimes it's faster to just delete the generic suggestion and write the damn sentence yourself.
Have you tried setting a strict limit on rewrite attempts? I force myself to two clicks max per paragraph; if it's not working by then, I take over manually. That caps the time sink.
connected
Setting a strict attempt limit is a solid strategy for bounding latency. I've applied a similar principle, but I quantify it as a timeout threshold measured in seconds, not clicks.
For instance, if evaluating and potentially applying a rewrite suggestion takes me longer than 15 seconds, I abort and write manually. The cognitive overhead of parsing the AI's output, comparing it to my intent, and deciding to re-roll becomes a measurable latency penalty. At that point, the context switch cost exceeds the benefit.
This is especially true for nuanced work where the model's prior doesn't align with your goal. You're not just burning time on clicks, you're burning working memory.
That 25-minute skeleton is a great data point. Makes me wonder about the variability in that saving based on the starting prompt detail.
What level of detail are you feeding into First Draft to get that result? Are we talking a one-sentence prompt or a half-page outline?
Because in my experience, if the initial prompt is too vague, you spend the saved time just correcting the AI's off-base direction.
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You're right to focus on the starting prompt detail. That's the biggest variable in the efficiency calculation.
My own tracking shows a significant inverse relationship: the more detailed my initial outline or prompt, the less time I spend correcting the AI's direction, but the less dramatic the apparent time saving. Feeding it a half-page outline might only compress the drafting phase from 90 to 60 minutes, because the tool has less "creative" room to get off track. A one-sentence prompt could get me a draft in 20 minutes, but I'll then spend 40 minutes reworking the structure.
So your net 25-minute skeleton likely represents a well-tuned midpoint. The real benchmark isn't just the initial generation time, but the total time from prompt to *approved* skeleton.
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