DEV Community: Jack

AI Search Sent Me 0 Clicks But 19 Citations — So I Rewrote Every Old Blog Post

Jack — Wed, 26 Aug 2026 13:09:40 +0000

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Three months ago I checked my analytics and found something I didn't know how to read: ChatGPT was sending me referrals. Except the referral page was /.

Not a blog post. Not a landing page. The homepage.

Twenty times in a single week, the same pattern — someone asked Claude or ChatGPT a question about solo-founder content strategy, the assistant answered with my name and article ideas, and the person clicked through to my homepage to find the post themselves.

Nineteen citations. Zero article clicks. That was the moment I stopped optimizing for ranking and started optimizing for being mentioned.

Here's what I learned in the five weeks since, and the framework I now run every old post through.

The Quick Answer That Kills Three

Google figured this out years ago. You look up "how to X", get the boxed answer, and never click.

AI search is that on steroids. The difference is that an LLM doesn't stop at quoting you once — it weaves your post's answer into its reply to a completely different follow-up three turns later. One good fact from your article can travel into seven separate conversations.

But here's the trap: the stats you see don't tell you that, because nobody clicks.

The first thing I did was stop using clicks as my success metric for AI search. Traffic got replaced by two things:

Citation appearances in AI answers (searched manually, and increasingly via tools)
Prompt queries reaching my content — sessions where an AI was visibly answering on my behalf

When I audited my articles that did get cited, a pattern emerged. Every one of them answered a question in the first 120 words.

The Audit I Want to Show You

The boring parts of my old posts were wasting all the potential. Here's what cheap little test: paste a blog post title into ChatGPT and ask "summarize this article in 3 bullet points worth quoting."

If it says "no information found on that" — or worse, hallucinates a generic summary with nothing specific is missing — the post isn't in the AI's usable index, or it's not structured in a way that survives distillation.

Underperforming posts shared three holes:

1. No obvious thesis sentence. My intros were scene-setting and meandering. AI cites what it can lift and reuse in two seconds.

2. Facts hiding in paragraphs instead of structure. A table or a stat in its own line gets pulled into answers 10x more often, because it's self-contained.

3. No "voice anchor." When an LLM decides whether to quote me or genericblog.com, it looks at the specificity of the author. Vague, carefully-written generic advice reads like everyone else.

The 90-Minute Rewrite Loop

I set up a simple pass for every post that had ever gotten organic traffic. It takes about 90 minutes per old post:

Pass 1 — The Answer Block (15 min). Rewrite the first 120 words as a standalone answer to the post's primary question. It should be quotable even if the rest of the article is stripped away. Title + first paragraph should alone be clear enough to answer: "Who is this for, and what will they learn?"

Pass 2 — Evidence Extraction (30 min). Convert any useful number or study into its own indented bullet or a one-line bolded statement. Trim every sentence that could apply to any SaaS ever.

Pass 3 — The Comparison Table (25 min). Whenever the post compares two things — manual vs automated, agency vs tool, do-it-yourself vs buy — a markdown table forces AI to lift exact rows into answers.

Pass 4 — Freshness Date (20 min). Update the publish date, and add a one-line "last verified" note near the top. AIs weight recency — a post that says 2024 data gets treated as stale, even when it's still right.

The Tool That Made This Repeatable

I won't pretend I keep doing this manually at scale. Once the framework worked on 5 posts, I needed it baked into my workflow — thinking about AI answers before the post exists, not after.

That draft pipeline is what I built at nextblog.ai — the posts get drafted with the answer-block structure in the first write where the bones of the article are laid down, SEO structure and potential citations in mind, instead of the scrappy old me rewriting everything three weeks after publishing for human-only writing. It's the same framework above, but moved earlier in the pipeline so the rewrite last month was the last one I needed.

What Actually Changed

Six weeks in:

The articles I rewrote attract citations at a noticeably higher clip than the ones I didn't
Referral volume from AI routing (people landing on a specific post) picked up
I changed my definition of content ROI. A seat in the answer is now a legitimate objective, because a citation converts inside the AI conversation where debate can happen

The from-here-on-writing for humans is done. Writing that is also quotable by machines is the entire game now.

What's your take — do you chase clicks or citations?

Matthew — building the AI-native content routine that's existence-proof. nextblog.ai drafts your posts answer-first. If this was useful, join the newsletter.

What 50,000 video generations taught me about rendering pipelines

Jack — Tue, 25 Aug 2026 14:03:36 +0000

What 50,000 video generations taught me about rendering pipelines

I run a text-to-video platform. Over the past year our pipeline has processed just over 50,000 generation requests — everything from 20-second brand clips to three-minute explainer videos. I've spent most of that time staring at render metrics instead of shipping features, and the data has changed my mind about almost everything I believed when I started.

Here's what the numbers say, in the order they changed my mind.

The metric that matters is not render time

Everyone asks about render time. It's the wrong question.

The metric that actually determines whether customers come back is the regeneration rate — the share of generations that get re-run because the first result wasn't usable. Ours started around 61%. That means for every ten "successful" renders, six were immediately discarded and generated again. Render time is irrelevant when two-thirds of your output goes in the bin.

After nine months of pipeline work, regeneration rate is down to 34%. It's still the single largest cost driver in the business — bigger than GPUs, bigger than storage, bigger than the foundation-model API bills we pay every month.

Where videos actually fail

I categorized the first 5,000 discarded renders by failure mode (human-labeled, which took a deeply unreasonable amount of time). The breakdown:

Text rendering — 29%. Logos, captions, on-screen text coming out garbled with invented letters. It's the biggest single failure mode and also the quietest one, because people just click "generate again" and move on.
Physics and motion breakdown — 23%. Objects melting, limbs detaching, motion that looks fine for three seconds and then goes off the rails.
Aspect-ratio and composition — 18%. Subjects cropped out of frame, or framing that doesn't match the target platform (9:16 vs 16:9 vs 1:1). This one is almost entirely a prompt-discipline problem on our side, and it was the easiest to fix.
Style drift — 14%. The vibe collapsing mid-video. First half looks cinematic, second half looks like a screensaver from 2001.
Lip sync and audio — 9%. Audio-visual mismatch in talking-head videos.
Everything else — 7%. Glitches, black frames, corrupted segments.

The text failures are the interesting case. They're the least fixable by prompt engineering: no amount of "make the text legible" helps, because the model doesn't render text so much as hallucinate it. We shipped a post-processing pass that detects garbled glyphs and triggers an automatic re-roll with a different seed — it cut text failures by about half.

The cost breakdown nobody talks about

Per successful minute of delivered video, the full pipeline costs us about $1.14 in compute at current (August 2026) rental prices:

Component	Share
Base generation (GPU-seconds)	42%
Regeneration waste (the 34% regen rate, plus partial re-runs)	31%
Upscaling and post-processing	18%
Audio, captioning, assembly	9%

Regeneration waste is the number I'd tell any founder to instrument from week one. If we'd built automatic candidate scoring in month one instead of month six, we'd have saved somewhere in the low five figures of pure GPU waste before we ever shipped a feature — let alone the retention cost of handing customers broken videos.

Render length is a trap

The single best operational decision we made was capping generation at ten seconds per segment and stitching longer videos together from short segments.

The naive approach — longer generation windows — produces a worse quality-to-cost curve the longer you go. Failures compound: a 30-second generation that fails at second 22 wastes 30 seconds of compute, not 8. With 8–10 second segments, a failure wastes at most ten seconds, and it fails fast enough that the automatic retry lands before the user notices anything.

The downside is stitching artifacts. Cut points are visible in roughly 1 in 20 finished videos, especially when camera motion doesn't match between segments. We've mitigated it with cross-fades and motion-matched boundaries, but it's still the most frequent complaint we get — which tells you how good the underlying generation has become.

What I'd do differently

Instrument the failure pipeline before the happy path. Every generation should log its outcome, its cost, and its failure category from day one. I shipped for four months before I could answer "why are people re-generating?" — and that answer would have focused the roadmap better than any feature request we received in that window.
Don't build your own queue until you've outgrown someone else's. I wrote a custom render scheduler in month two. It was a mistake. Off-the-shelf queue systems already have backpressure, retries, and observability. Ship on the boring queue; build the custom one only when the boring one is demonstrably the bottleneck.
Rent, don't buy. We almost bought a small GPU cluster in month five. A pricing change on rental hardware a few weeks later would have made that purchase look very silly. Reserved capacity for the spike, on-demand for the base — that's the whole strategy.
Score output; don't just deliver it. A cheap scoring model that rejects obviously-broken renders (black frames, frozen frames, audio dropout) before they reach the user bought us more customer trust than any UI feature we've shipped. A broken video that reaches a customer doesn't just cost a regeneration — it costs credibility.

The honest part

The platform still fails in ways that surprise me weekly. I assumed that by video #50,000 the failure modes would be a solved, boring problem. Instead the frontier just moves: we fixed garbled text, and discovered that subtle physics errors — a hand that bends wrong, a background that warps slowly — are the new silent killers. Those are harder, because users can't always articulate what's wrong. They just know "something feels off."

That's the actual state of this field: the obvious failures get fixed, and the remaining failures are the subtle ones that erode trust invisibly. The teams that win will be the ones that measure regeneration rate, treat output quality as an operations problem rather than a model problem, and instrument everything from day one.

I built vidmachine.ai to make this kind of generation accessible without needing a team of ML engineers — prompt to finished 4K clip in one product. If you've built anything on top of generated video, I'd genuinely like to know: what's your biggest bottleneck right now — quality, cost, or reliability?

The Best Thing I Did for My X Account Was Posting Less

Jack — Sun, 23 Aug 2026 13:05:26 +0000

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For 14 months I treated my X account like a business calendar. Post every day, reply to everything, keep the engine warm. "The algorithm rewards consistency," I told myself.

Then I went through a month of my own analytics and found something uncomfortable: roughly 80% of my follows and clicks came from roughly 20% of my posts — and most of that 20% died within 24 hours of going up.

I was grinding out daily posts while my best work sat in a graveyard.

The uncomfortable half-life

Here's the part nobody frames properly. The average tweet of mine got the heavy majority of its impressions in the first few hours. After a day, it was effectively a museum piece. Occasionally something random picked it back up, but I had no control over when or why.

So the daily grind was producing daily driftwood. New post, same half-life, zero compounding.

The people telling you to post daily aren't wrong, exactly. They're just optimizing for input — how often you show up. The thing they never talk about is what you do with output: the posts that already worked.

The fix: run your account like a release channel

I made one structural change. I stopped asking "what do I post today?" and started asking "what system keeps my best work working?"

Rule 1 — Give the winners a second at-bat.

Instead of betting every morning on brand-new content, I started re-surfacing my best performing posts a few days later at a different time. It sounds too simple to matter, and that's exactly why it works: a new audience is on the other side of the world three days later.

One post that got 12,000 impressions in February got 9,000 more when I surfaced it again in April. I didn't write a word of new content. I just stopped abandoning it.

Rule 2 — Batch the inputs, automate the outputs.

Replies, welcome DMs, scheduling, thread planning — this was genuinely eating my mornings. I built a pipeline that turns raw thoughts into scheduled posts in batches. Ten minutes on a Monday: the whole week is locked in. No daily decision. The daily decision is where most solo founders bleed willpower.

Rule 3 — Watch the pattern, not the post.

I stopped judging individual posts and started watching which patterns commanded attention: which topics, formats, and days. Posting is like PPC — you judge the campaign, not the click.

Where the product fits

I built a tool called XBeast to run this exact loop. Point it at the posts that already worked, and it schedules a whole week of content in your voice, resurfaces the winners, and cleans up replies and DMs in the background. It turns "you need to be on X daily" from a life commitment into a Monday-morning ritual.

It is not magic. It doesn't make bad posts good. What it does is remove the two biggest killers — the daily blank page, and the 24-hour graveyard for your best work.

What actually happened

A month into the system:

The average engagement per post went up, because I stopped spending my daily budget on unproven content and started compounding what had already earned attention.
Followers kept growing, but the interesting change was where: they came while I was asleep, kicked in by auto-surfaced posts.
I got my mornings back. That's the underrated one. The momentum felt permanent instead of remembered.

The scariest part was how slowly it happened, then how steady. No viral tweet, no spike. Just the compounding behavior of a system that never skips a day — even when I do.

The one sentence version

Chase patterns, not posts.

A daily posting habit restarts the queue from scratch every morning. A system keeps what already works in rotation, and puts a human exactly where a human is worth something.

So here's a question for you: what "daily" task are you still doing that could be a week-scheduled system instead? I'd genuinely love to know what happens if you try the second at-bat trick — drop it in the comments.

218 Cold Emails, 0 Replies. Then I Started Looking for People Who Were Already Looking

Jack — Wed, 19 Aug 2026 13:05:00 +0000

P.S. If you want more solo-founder acquisition workflows like this one delivered to your inbox every week, join 1,000+ readers getting them free: https://wuki.beehiiv.com/subscribe

Last quarter I did the thing every course tells you to do. I built a clean list — 218 founders, all in my niche, all with "good" titles and real company URLs. I wrote what I thought was a great cold email. Four lines. One clear ask. I personalized each first line by hand.

I sent 218 emails over three weeks.

Zero replies. Not even a "no thanks." Not one angry "take me off your list." Nothing.

I spent the next few days going down the usual rabbit holes: subject lines, send times, email deliverability, more follow-ups. All fine, by the way. My domain was clean, my bounce rate was 1.4%, my open rate was 41%. The email itself was genuinely decent.

So why did nothing happen?

Because I was talking to the wrong people. Not wrong type of people — their ICP matched perfectly. Wrong frame of mind. Every single person on that list was, at that moment, completely happy ignoring me.

The difference between a list and a market

Here's the thing I got backwards. A lead list is a set of people who look like your customer. A market, at any given second, is a much smaller set of people who are actively trying to solve the problem you sell to.

Those two groups barely overlap on any given day.

Think about your own behavior. When you're not thinking about a problem, and someone cold-approaches you about it, your brain classifies that as noise — it doesn't matter how good their pitch is. You delete it with your thumb before your conscious brain finishes reading the subject line. I did this exact thing to a hundred salespeople while building my SaaS. We're all doing it to each other.

The only cold outreach that ever landed with me — like, actually landed, the kind I replied to in under ten minutes — was when I happened to already be looking for that exact thing. Someone reached me at the perfect moment. It felt like they'd read my mind, which felt almost like magic.

It wasn't magic. It was timing. And timing isn't luck — it's a signal you can hunt for.

What "looking" actually looks like (concretely)

Once I stopped treating outreach as a volume game, I started watching for moments where a stranger's problem becomes visible. In my niche, that showed up as:

Someone asking for a tool recommendation in a community or thread — "does anyone know a tool that does X?" — where X is literally my product's core feature
A founder posting about the pain out loud — "cold outreach is killing me," "my acquisition is stuck," "does anyone actually get clients from this?"
A hiring signal — they've posted a role or are building out a function that suggests the pain is now real and budgeted
A recent change in their stack — a new CRM, a new website, a new pricing page — the kinds of things people do right before they go looking for help
Public "how do I..." queries — the person is mid-research, gathering options, comparing vendors

Here's what all of these have in common: the person has already admitted the problem to themselves. They're not deciding whether they need a solution — they're deciding between solutions. That's the single biggest difference in all of outbound. When you reach someone at that stage, your "cold" email isn't interrupting them. It's answering the exact question they were about to Google.

I rewrote my whole approach around this. Instead of generic list → spray → pray, it became: watch for the signal → reach out within hours → reference the signal in the first sentence.

The numbers were embarrassing in the best way. Where 218 "perfect list" emails got me zero replies, my first 40 signal-triggered emails got me 11 replies and 4 calls. Same email template. Same product. The only variable that changed was when the person was in the conversation.

The uncomfortable realization

Here's what I had to accept: I wasn't bad at cold email. I was bad at targeting, and I'd been hiding behind volume to avoid doing the hard part. Building a list is easy and feels productive. Watching for signals is slow, boring, and unstructured — for a while it felt like I was doing nothing at all.

But this is exactly the thing that doesn't scale by hand, and it's where AI genuinely changed my workflow. I spent a couple of weekends hacking together a scraper that watches communities, job boards, and public "help me pick" posts in my niche, scores them for fit, and drops the best ones in my queue each morning. I reference the actual signal in my first line — "saw you asking about X in the Y thread" — which is another way of saying I'm not a stranger, I'm a person who was listening when you spoke.

That scraper eventually became clienthunter.ai — I realized other solo founders were stuck on the exact same problem: not writing outreach, but knowing who to reach out to at the exact moment it stops being cold. So instead of a private script, it's now a product that finds buyers who are already looking.

The rule I wish I'd learned first

Cold outreach works. But "cold" is a timing problem, not a copy problem. Nobody is going to be convinced into buying something they weren't looking for — the best email in the world can't manufacture an unmet need. What you can do is find the people who already have the need, right now, and be the first useful person in their inbox that day.

Stop optimizing your subject lines. Start optimizing your moment.

What's the best signal you've found that someone is about to buy — and how do you watch for it? I'm always looking for new ones.

Google Keeps Ranking Reddit Over Your Blog — Stop Fighting It and Do This Instead

Jack — Sun, 16 Aug 2026 13:02:13 +0000

P.S. If you like solo-founder search and distribution plays like this one, more arrive in your inbox every week — join the founders getting them free: *https://wuki.beehiiv.com/subscribe***

When was the last time you Googled something without mentally appending the word "reddit" to it?

For me it was a Tailwind config question, weeks ago. Anything else — "best stack for a solo dev in 2026," "how to price a SaaS subscription," "how do people actually get first customers" — I type, pause, and add reddit before I hit Enter.

Google has noticed. And it has quietly made a decision: community threads are the new ranking pages. First-person answers from anonymous strangers are outranking polished company blogs, including mine, for the exact keywords I was spending hours writing posts for.

If you're a solo founder still gambling on a blog to get found, this is the most useful thing you'll read this month: that fight is over, and the winner is whoever answers threads like a human, not a marketer.

The 3,000 words that 40 people read

Eighteen months ago I published what I thought was a definitive guide — 3,000 words, real data, screenshots. It ranks somewhere between position 4 and 9 for its main keyword. Some months 40 people find it. Not exactly a growth engine, but it was a blog, and blogs rank, right?

Wrong. Six months before that guide, I had answered the same question on Reddit in about 800 words, no link to my site, with a couple of screenshots. That answer has since been read thousands of times, still gets replies weekly, and now shows up in both Google and AI answers about the topic.

One blog post that took a week to write: 40 views. One comment that took 25 minutes: thousands. Same question, same author, opposite results. The search engine of 2026 does not rank companies — it ranks conversations.

Why this happened

Google's own updates have moved the value signal from "who has the biggest website" to "who actually knows what they're talking about." AI text can spam out 10,000-word blogs in seconds, so the written word is not scarcity. First-hand experience is.

What survives that filter is what reads like a real log: specific numbers, people describing exactly what they did, hands-on screenshots, and sometimes a mistake they made too. That is Reddit's native format. Threads get read by people and cited by AI — which means if your competition is only shipping blog posts, they're invisible the moment search started favoring people.

Your comments can do 3 jobs

This is the part I had to feel out the hard way. Every comment you leave pays you three times:

Talk to the person now. The questioner reads the thread, replies, follows up, opens a real conversation. That is a lead a blog post can't make.
Rank later. Google indexes subreddit threads — including sub-threads you already reply in. The brain never goes away; your comment is a tiny page with search visibility, forever until it goes stale.
Feed the AI answers. The same threads LLMs are trained on and cited from. If your comment is the best answer, you're in the citation mix when someone asks "what's the best way to X" via AI.

The daily waters: how to actually collect comments

The beautiful part: this takes 10 minutes a day, which is nothing next to the weekly 6-hour blog sprints I was doing.

Find the buying-intent threads. Search "topic + reddit" and the subreddit where your buyers hang out. Sort by new. Look for questions that cost money to get wrong — "which X should I pick", "how do I X faster", "what did you do about Y". Those are shopping questions, not hobby questions.
Be the most specific answer. Lead with your number, a concrete log of what happened — price, time spent, what you'd do differently. Even better if 1 column photo proves it. And say what you wouldn't do.
Answer the replies under your answer. Comments that thread into your comment get indexed and listed too. Depth inreddit = the "expand" or secondary ranking — the fastest way to be the whole conversation instead of a footnote.
Keep it current. My best comment gets updated every few months. Threads that stay accurate get more trust over time, and that freshness pass in Reddit's "best" sorting — repeat once a quarter and the thread keeps working.
Never pitch in the first answer. If you leave a link in the first reply, you get downvoted and the thread gets ignored. Instead: solve the problem with everything you know, and only mention your product when it's genuinely the solution to that specific question.

Where the tool piece fits

My entire reason for building reddbot.ai started here — I was trying to do this across 4 subreddits and kept missing the thread where the timing mattered. So reddbot watches my customer's subreddits 24/7 and pings me the moment a question matches the keywords my buyers actually use, along with a suggested outline. I still write every word myself — that's the part that ranks — the robot just makes sure I'm answering in the first hour instead of the fourth day. That speed matters: the early, detailed answers are the ones that got the upvotes that became rankings.

The reset

Next time you're late to a thread, count how many of your competitors answered with numbers, screenshots, and an honest mistake. Then count how many spat out a sanitized blog paragraph. The algorithm is keeping the score — and the first group is winning it, thread by thread, comment by comment.

Set your blog to "maintenance mode" if it helps, and put 10 minutes a day into being the best, most useful answer on the internet instead of the most produced one. Google never ranked the fanciest website — it ranked the one that believes the most. It's just finally admitting that conversations > content.

What did you last buy — or decide not to buy — because of a Reddit thread?

I Replaced My Blog With AI Shorts for 30 Days — Here's What Actually Happened

Jack — Wed, 12 Aug 2026 13:04:03 +0000

P.S. If you want more solo-founder marketing experiments like this one delivered to your inbox every week, join the founders getting them free: *https://wuki.beehiiv.com/subscribe***

Every solo founder I know has heard the same advice: "You need to be on video. Shorts. Reels. TikTok."

Then they open their calendar, realize a 60-second video takes 3 hours to make, and close the tab. That was me for two years. I had a blog, a newsletter, and a writing habit — and zero video presence.

The 3-hour excuse was real

Here's what I actually tried before going fully automated:

Recording myself on camera → I'm a developer, not a presenter. The lighting was bad. The take count was worse.
Hiring an editor → $50 per video. Thirty videos a month is rent money.
Outsourcing the whole channel → fast, generic, and completely disconnected from my actual product.

So I didn't make videos. Neither do most solo founders. And the platforms that reward video — TikTok, YouTube Shorts, Instagram Reels — stayed off my distribution map while my written content did all the heavy lifting.

The experiment: 30 videos, zero editing, 30 days

I decided to test whether I could run a short-form video channel the same way I run my blog: as a system, not a ritual. The rules:

One short per day for 30 days.
No manual editing. Voiceover, visuals, captions — all generated.
One idea per video, pulled from my existing blog posts and tweets.
Auto-scheduling to TikTok, YouTube Shorts, and Reels.

The pipeline: my best-performing written ideas went into a script template (hook → tension → payoff → CTA), an AI voice read them, and the tool stitched together visuals and captions automatically. I reviewed the week's queue once, on Sunday. That was the entire time investment.

Full disclosure: I built the tool that does this. It's called VidMachine, and it generates vertical Shorts or long-form YouTube videos, adds the voice, schedules them, and posts them to TikTok, YouTube, and Reels on autopilot. I built it because I got tired of waiting for this workflow to exist. The experiment below is me dogfooding it.

The numbers nobody shows you

Days 1–7: silence. Total views across all three platforms: under 400. I almost killed the experiment.

Days 8–14: one video broke through. A short about pricing mistakes got 40x my average views. Not because the topic was exotic — because the first 2 seconds asked a question people desperately wanted answered.

Days 15–30: compounding. Views stayed feast-or-famine per video, but the channel-level numbers only went up. The viewers who followed from that one breakout short started showing up on every subsequent upload.

At the end of 30 days:

~48,000 total views across three platforms
214 profile visits to my product's landing page
11 signups — roughly half of what my best blog post pulled, for about 5% of the effort

And here's the part that surprised me most: while several videos flopped hard, not a single one hurt. There's no such thing as a failed short — a 200-view video costs you ten minutes of weekly review time.

What actually moved the needle

The first 2 seconds are the whole video. Question hooks beat statement hooks, every time.
Consistency beats polish. All three algorithms reward accounts that post regularly far more than accounts that post beautifully.
Repurpose, don't re-create. My best shorts were my best blog posts tightened to 30 seconds. The ideas were already validated by readers.
Views ≠ customers, but they're still free distribution. Every view is a chance to be discovered — and some of those viewers convert months later, from a channel they'd forgotten they followed.

The honest caveat

Video isn't magic. My written content still converts better per visitor, and the newsletter remains my real asset. But video is where attention actually lives in 2026, and "I don't have time" turned out to be an editing problem in disguise — one that automation genuinely solved.

If a solo founder with no camera skills and no budget can ship 30 videos in a month without touching an editor, the excuse is officially dead.

So I'm curious: what's your excuse — the editing, the camera, or the fear that nobody will watch? And if you've already automated your video pipeline, I'd genuinely love to hear what your stack looks like in the comments.

I Killed 3 SaaS Blogs in 18 Months — The Content Consistency Problem No One Talks About

Jack — Wed, 22 Jul 2026 13:03:30 +0000

P.S. If you want more solo founder content workflows like this one delivered to your inbox every week, join 1,200+ readers getting them free: https://wuki.beehiiv.com/subscribe

The Graveyard

I have a folder on my desktop called "archive/blogs." It contains three dead projects:

DevLaunch.io — 4 posts, died January 2025
BuildInPublic Weekly — 7 posts, died June 2025
SaaS Breakdown — 12 posts, died November 2025

Each one started with the same energy. I bought a domain, set up the theme, wrote a launch post, got 200 views, and felt like a real content creator. Then week three hit. The post I'd planned suddenly felt weak. I had client work to do. The SEO wasn't kicking in. Nobody commented. So I skipped a week. Then another. Then the domain expired.

I'm not alone in this. The indie hacker ecosystem is full of blogs with 3–5 posts and a last-updated date from 2024. The problem isn't that we can't write. It's that content consistency is a systems problem, and we're treating it like a motivation problem.

Why Consistency Is Harder for Solo Founders Than for Teams

When you're a solo founder, your content engine is also your product builder, your support team, and your sales pipeline. Writing a blog post isn't just writing — it's stealing time from the three things that actually keep the lights on.

Here's what I've learned killing three blogs:

1. The "I'll write when I have something to say" trap. This is the deadliest mindset. You never have something to say when you sit down to write. The pressure to produce something profound every time is what kills the habit. You need volume before you can have signal.

2. The editing loop. I'd spend 2 hours on a 800-word post — 30 minutes writing, 90 minutes second-guessing every sentence. The diminishing returns on that last 90 minutes are brutal. A published "good enough" post beats an unpublished "perfect" post every time.

3. The SEO waiting game. Writing a post and waiting for Google to send traffic is like planting a seed and checking for a tree every morning. Most solo founders quit before the SEO compounds because they're measuring by views instead of proof — proof that the system works.

What Fixed It: Treating Content Like Infrastructure

After the third blog died, I stopped asking "how do I write better" and started asking "how do I make writing inevitable."

The answer was infrastructure, not willpower. Three changes made the difference:

Batch, don't bootstrap. I stopped writing posts one-at-a-time. Instead, I spend one Sunday per month writing 4–5 post outlines. They're messy — bullet points, half-baked takes, rough analogies. But the outlines exist, and that means I never sit down at a blank page.

Templates are not cheating. I built a simple structure: hook → problem → three solutions → action steps → question. Every post fits. I fill in the blanks instead of redesigning the architecture each time. This cut my writing time from 2 hours to 45 minutes.

Automate the distribution. This was the real unlock. I realized I was spending 80% of my content energy on publishing — formatting, scheduling, cross-posting, SEO metadata — and only 20% on thinking. Once I built a content pipeline that handled the publishing mechanics, I could focus on what actually mattered: having something useful to say.

I ended up using nextblog.ai to handle the distribution side — it turns my rough outlines into formatted posts, schedules them, and handles the SEO basics. The point isn't that you need a specific tool. The point is that you need a system that removes friction between having an idea and putting it in front of readers.

The Metric That Matters

Forget views for the first 90 days. Forget comments. The only metric that matters for a solo founder blog is posts published per week.

If you publish 2 posts per week for 12 weeks, you have 24 pieces of content. At that volume, you can:

Repurpose the best ones for X/Twitter threads
Cross-post to dev.to and Indie Hackers
Spot patterns in what resonates
Build a real backlog for SEO to compound

24 posts is the minimum viable blog. Most founders quit at 5.

The One Question

I'm writing this post on Wednesday morning. It's not perfect. I could spend another hour polishing the intro, finding a better metaphor, or tweaking the headline. But I'm hitting publish instead.

Because the only question that matters for solo founder content is this:

What system did you put in place this week that makes your next post easier to write than this one?

Drop your answer in the comments — I'm genuinely curious how other solo founders are solving the consistency problem.

The Solo Founder's Client Acquisition Myth: Why "More Outreach" Is the Wrong Variable to Optimize

Jack — Sun, 19 Jul 2026 13:02:14 +0000

P.S. If you want more solo founder growth and client acquisition workflows like this one delivered to your inbox every week, join 2,000+ readers getting them free: https://wuki.beehiiv.com/subscribe

Every solo founder I know hits the same wall around month three.

You've built the product. You've polished the landing page. You've even got a few friends to beta test it. But real paying clients? The kind that hand over a credit card number and expect value in return? They're not showing up.

And the standard advice — "just do more outreach" — is quietly destroying your chances.

The Volume Trap

The logic sounds unassailable: more emails sent = more replies = more demos = more customers. So you buy a list, fire up a sequence, and blast 500 cold emails in an afternoon.

Here's what actually happens:

48% bounce because the data was stale
32% hit spam filters because the sequence was generic
15% open, skim the first sentence, and delete
5% reply with "not interested"
0.1% might actually convert

You just spent 6 hours building a list and writing emails for 0.5 conversions. That's 12 hours per client. At that rate, you'd be better off working a side gig and paying for ads.

The problem isn't effort. It's that you're optimizing the wrong variable.

What Actually Moves the Needle

I've spent the last year talking to solo founders who crossed $10K MRR without a sales team. Not one of them said "I just sent more emails."

They all said the same thing: I got pickier about who I talk to.

The Pareto principle applies brutally here. 80% of your revenue will come from 20% of your outreach — but only if you've correctly identified which 20% that is before you start typing.

The founders who win at client acquisition do three things that the volume-maximizers skip:

1. They build a list of "perfect fits" before writing a single word

Not "companies that might use my product." Not "people in vaguely related industries." A specific, researched list of decision-makers who have a demonstrated pain point. They look for triggers: new funding rounds, job changes, public complaints about a problem your tool solves, recent competitor migrations.

2. They personalize at the signal level, not the template level

"Hey {first_name}, loved your recent post about {topic}" is not personalization. It's what every other person sending that template is writing. Real personalization references specific signals: a product change they announced, a problem they vented about publicly, a gap in their current stack that you can fill.

3. They measure response rate, not send rate

The volume-maximizer celebrates sending 500 emails. The smart founder celebrates getting 15 thoughtful replies from 50 carefully targeted emails. The second metric predicts revenue. The first predicts a spam complaint.

The Tool That Changed My Approach

I built a tool called clienthunter.ai to solve exactly this problem. It scans thousands of online signals — public posts, company updates, hiring patterns, tech stack changes — and surfaces the people who are actively looking for a solution like yours. Instead of spending hours guessing who to reach out to, it tells you who's raising their hand right now.

The result? I went from a 1.2% reply rate on blast campaigns to a 22% reply rate on targeted, signal-driven outreach. The list is smaller. The conversion rate is higher. And I spend less time in my inbox.

The Framework: 50-10-1

Here's the simple framework I use now for every client acquisition push:

50 — Research 50 potential clients who match your ideal profile. Check their LinkedIn, their recent activity, their company's tech stack, their public roadmaps or complaints.

10 — Reach out to 10 of them with hyper-personalized messages referencing specific signals. No templates. No spray-and-pray.

1 — Aim for 1 new client or serious conversation from every batch.

If you get 0, your targeting is wrong — go back to step one and refine your ICP. If you get 3+, expand the batch size. But never skip the research phase.

Why This Works for Solo Founders

As a solo founder, your time is your scarcest resource. You can't afford to waste it on volume-based approaches that return 0.1% conversion rates. The only way to compete with teams of 5 SDRs is to be smarter about who you talk to, not how many you talk to.

The solo founders who win in 2026 aren't the ones who send the most emails. They're the ones who send the right emails.

So next time you feel the urge to "just send more outreach," stop. Go find one signal instead. Research one person deeply. Write one message that proves you've done the work.

Then do it again.

That's how you go from zero to first client. Not with volume. With precision.

What's your biggest blocker in getting those first few paying clients? Drop it in the comments — I'd love to hear what's working (and what isn't) for other solo founders.

Reddit Is Not a Billboard: Why Most Solo Founders Waste Their Best Distribution Channel (and How to Fix It)

Jack — Sun, 12 Jul 2026 13:04:14 +0000

P.S. If you want more indie hacker distribution workflows — including the exact Reddit plays that drive signups — delivered to your inbox every week, join 7,000+ founders getting them free.

Every week, I watch another solo founder post their SaaS link to a relevant subreddit, get downvoted into oblivion, and then declare "Reddit doesn't work for distribution."

They're half right — Reddit doesn't work as a billboard. But as a relationship channel? It's the most underrated distribution engine for solo SaaS founders in 2026.

Here's the uncomfortable truth: the problem isn't Reddit. It's how you're using it.

The Three Mistakes Killing Your Reddit Strategy

1. You're Posting, Not Listening

The average solo founder opens Reddit, has an idea for a post, writes it in 10 minutes, and hits submit. Then they're confused when it gets 3 upvotes (all from their alt account).

What works instead: Spend 80% of your Reddit time reading, not writing. Set up keyword monitoring for the exact problems your SaaS solves. When someone asks "Is there a tool that does X?" — that's your moment. Not to pitch, but to genuinely help.

One founder in r/smallbusiness spent two weeks just answering questions with no link. By week three, people were DMing him asking what tool he used. That's trust compounding.

2. You're Ignoring the Long Tail

The big subreddits (r/SaaS, r/indiehackers, r/startups) are crowded. Your post competes with 50 others that day. But there are hundreds of smaller, hyper-specific communities where your ideal users actually hang out.

Think niche: r/CRM, r/projectmanagement, r/graphic_design, r/consulting. A post in r/consulting with 30 upvotes can drive more qualified traffic than a front-page post on r/SaaS with 300. The audience is pre-filtered.

3. You're Measuring the Wrong Things

Vanity metrics (upvotes, comments, follower count) feel good but they don't pay the bills. The real metric is qualified clicks to your site — and more importantly, whether those clicks convert.

A post with 50 upvotes that sends 200 people to your landing page and converts 3 is infinitely more valuable than a front-page post with 1,000 upvotes that sends zero traffic.

The System That Actually Works

Here's the Reddit workflow that's been driving consistent signups for solo founders:

Phase 1 — Surface (10 min/day)
Monitor 10-15 subreddits for keywords related to your niche. Save relevant threads. Don't respond yet — just build a backlog.

Phase 2 — Engage (15 min/day)
Reply to 3-5 threads per day with genuine value. Answer questions. Share lessons learned. Build your comment history so your profile signals "helpful human" not "spam bot."

Phase 3 — Create (1x/week)
Write one original post that summarizes the pattern you're seeing across conversations. Use the data and questions you've collected. This is where you earn distribution.

Why Automation Is Non-Negotiable for Solo Founders

Here's the thing — I just described 25+ minutes per day of manual work. As a solo founder, you don't have that time. Not if you're also building product, writing code, handling support, and doing 47 other things.

This is exactly why I built reddbot.ai. It monitors subreddits for your target keywords, surfaces the highest-signal conversations, and lets you engage without spending hours scrolling. The tool handles the surface phase so you can focus on the part that actually needs a human — the genuine conversation.

I use it for all my own products, and what used to take me 40 minutes of scanning now takes 5. The difference between "Reddit doesn't work" and "Reddit is my best channel" is usually just having the right system in place.

The Reddit Distribution Checklist

Before your next Reddit session, ask yourself:

[ ] Am I adding value before asking for anything?
[ ] Is this subreddit specific enough to my niche?
[ ] Am I measuring clicks, not upvotes?
[ ] Have I surfaced the last 24 hours of relevant conversations?
[ ] Is my answer genuinely helpful without a link?

If you can answer yes to all five, you're doing Reddit right. If not, adjust before hitting submit.

What's your biggest Reddit distribution struggle? Drop it in the comments — I read every single one.

The Solo Founder's Video Demo Blindspot: Why Your Product Page Is Costing You Trust (and Revenue)

Jack — Sun, 05 Jul 2026 13:06:01 +0000

P.S. If you want more solo SaaS growth workflows like this one delivered to your inbox every week, join 2,500+ founders getting them free: https://wuki.beehiiv.com/subscribe

I launched my first SaaS product with a beautifully designed landing page. Clean typography. Animated hero section. Social proof carousel. Three pricing tiers. I even had a 30-second explainer video... buried in the "How It Works" section below the fold.

After three weeks of watching the analytics — 2,300 visitors, 12 signups, 0 paid conversions — I did something I should have done before launch. I asked 10 people who visited the page why they didn't buy.

Nine of them said the same thing: "I couldn't tell what it actually does."

My beautiful landing page was a trust black hole. And the fix was embarrassingly simple.

The Trust Gap Between "Looks Good" and "Actually Works"

Here's the brutal truth about SaaS in 2026: your potential customers have been burned. They've signed up for tools that looked promising and delivered nothing. They've watched polished demo videos that skipped over the hard parts. They've read landing page copy that made bold claims and fell apart on day one.

Trust is the scarcest currency in SaaS right now. And nothing builds trust faster than an unpolished, real-world video demo.

Not a cinematic production. Not a slick explainer with voiceover. A raw screen recording of you actually using your product to solve the problem it claims to solve.

Why Text + Screenshots Isn't Enough Anymore

I used to think detailed screenshots with annotated arrows were sufficient. I was wrong for three reasons:

Screenshots are static. They show one moment in time. A video shows cause and effect — click this, see that happen, understand the flow.
Screenshots hide friction. A screenshot of a dashboard with beautiful charts doesn't show the 90 seconds of loading time. A video does.
Screenshots don't convey confidence. Watching someone confidently navigate their own product signals that the creator actually uses it. That's infectious.

The Data That Changed My Mind

I ran a simple A/B test on my product page. Version A had a detailed feature breakdown with screenshots. Version B had the same copy but replaced the top screenshot with a 90-second Loom of me walking through the core workflow.

Version A: 1.8% conversion rate.
Version B: 4.2% conversion rate.

That's a 133% lift from a single video. The math was immediate: if my MRR target is $5,000/month, that video was worth roughly $2,100/month in additional revenue.

What Makes a Good SaaS Demo Video

After recording dozens of demos (and cringing at the first 20), here's what I've learned works:

Start with the problem, not the login screen. Open with "You know how annoying it is when X happens? Here's how we fix it."
Show the full journey, not the highlights. Pick one user story and follow it from start to finish. Include the loading states.
Be honest about limitations. Say "This feature is experimental" or "This takes about 30 seconds to process." Honesty builds more trust than perfection.
Keep it under 3 minutes. Attention drops off a cliff after 120 seconds. Cut ruthlessly.
Put it above the fold. Your video is not a bonus feature — it's your best salesperson. Give it the hero position.

The Tool That Changed My Video Workflow

I got tired of constantly recording, trimming, re-recording, and managing video files. So I built a tool called vidmachine.ai that automates the whole pipeline — recording, editing, captioning, and hosting product demos. It's become an essential part of every launch I do.

But the tool doesn't matter nearly as much as the decision to actually put a video on your page. You can record on your phone, use QuickTime, or Loom. The format barely matters. What matters is showing your face (or your cursor) doing the thing your product promises to do.

The Ripple Effect Beyond Conversion

The unexpected benefit: fewer support tickets. My video demo answers "How do I do X?" before users ever need to ask. I saw support volume drop by roughly 30% after the video went live. Users who watched the demo converted better and churned less. They'd seen exactly what they were signing up for.

Start Today

If you're a solo founder and your landing page doesn't have a video demo, that's your highest-leverage marketing move this week. Not a new feature. Not more cold outreach. Not another Twitter thread.

Record yourself using your product. Put it on your homepage. See what happens.

The video won't be perfect. Mine wasn't. But it will be real, and in a world of AI-generated everything, real is the one thing customers can't get enough of.

What's stopping you from putting a video on your landing page? I'd love to hear your blockers in the comments — I've faced most of them and might have a workaround.

I Built 3 SaaS Products in 6 Months Using AI — Only 1 Got Users. Here's What the Other 2 Taught Me About Distribution vs. Features

Jack — Wed, 01 Jul 2026 13:04:33 +0000

P.S. If you want more solo-founder workflows and distribution playbooks like this one delivered to your inbox every week, join 5,000+ indie hackers getting them free: https://wuki.beehiiv.com/subscribe

Between January and June this year, I did something stupid and instructive in equal measure: I built three SaaS products back to back using AI coding tools.

Product A was a scheduling tool for X/Twitter. Product B was a content analytics dashboard. Product C was a lightweight blog engine with AI-powered rewriting features.

Only Product A got any real users. Not because it was the best code. Not because it solved the hardest problem. Because I actually told people about it.

Let me walk through what happened with each one, and why I now believe distribution is the only thing that matters for solo founders in 2026.

The False Economy of Building

When you're a developer and you have access to Claude, Cursor, and GPT-5, the temptation is irresistible. You can spin up a full-stack app in a weekend. A new feature in an afternoon. A complete product in a month.

I fell into this trap hard. Product B (the analytics dashboard) had 14 data visualizations, real-time webhook processing, and a beautiful shadcn/ui interface. It was genuinely better than 80% of the analytics tools on the market. I spent six weeks on it.

Product C (the blog engine) had AI-powered title generation, SEO scoring, automated social sharing, and a custom Markdown editor I was particularly proud of. Four weeks of work.

Product A (the X scheduling tool) was a basic queue system with a calendar view. Two weeks, maximum. The code is honestly embarrassing compared to the other two.

Guess which one has paying customers?

The Distribution Gap Is the Real Gap

Here's what happened after each launch:

Product B: I posted a "Show HN" on Hacker News. Got 3 upvotes. Tweeted about it once. Got 2 likes. Then I went back to adding more features — a sentiment analysis module, a competitor tracking view, an export to PDF. I was convinced that if I just built enough features, people would show up. They didn't.

Product C: I wrote exactly one blog post announcing it. Posted on a few subreddits. Got shadowbanned on two of them for "self-promotion." Then I decided the AI title generator needed "just one more model" and spent two weeks integrating GPT-5. The product grew by 0 users during those two weeks.

Product A: I committed to writing one thread about it every day for two weeks. Not "buy my thing" threads — useful threads about social media scheduling, with my tool mentioned naturally at the end. I cross-posted the best threads as blog posts. I engaged with every comment. I found 5 indie hackers who had the same problem and offered them free lifetime access in exchange for honest feedback.

Product A now has 47 paying users and growing. Products B and C have 4 users combined — 3 of whom are me across different browsers.

The Numbers Don't Lie

Let me put some hard numbers on this. In the 6 months I was building:

Product B: ~400 hours of development. 40 hours of distribution. Result: 3 users.
Product C: ~250 hours of development. 25 hours of distribution. Result: 1 user (not counting my alter egos).
Product A: ~100 hours of development. 80 hours of distribution. Result: 47 paying users.

The ROI isn't even close. Every hour I spent on distribution was worth roughly 10x what an hour of building was worth. And yet my natural instinct — the developer instinct — was to keep building.

What Distribution Actually Looks Like for a Solo Founder

I'm not talking about hiring a marketing agency or running Google Ads. Here's what distribution meant for me:

One piece of good content per day. A thread, a blog post, a thoughtful comment on someone else's post. Every single day. No exceptions.
Repurpose everything. That thread becomes a blog post becomes a LinkedIn article becomes a Reddit post becomes a newsletter. Same ideas, different formats. This is where I started using nextblog.ai — not to generate content from scratch, but to take my existing drafts and reshape them for different platforms without starting over each time.
Talk to users before writing code. Every feature in Product A was requested by at least 3 people before I built it. Product B and C were built based on what I thought people wanted.
Ship distribution infrastructure before product infrastructure. Before writing a single line of backend code for Product A, I set up: a landing page with email capture, a blog, and a Twitter account. Product B and C had none of this until week 4 or 5.

The 2026 Reality

AI has made building trivial and distribution scarce. Every solo founder can ship a product in a weekend now. The differentiator isn't code quality or feature count — it's who can tell the best story about what they built.

The indie hackers winning in 2026 aren't the ones with the most sophisticated architecture. They're the ones who wrote the most useful threads, built the most engaged audiences, and showed up consistently even when nobody was reading.

If I could go back to January and give myself one piece of advice, it wouldn't be about tech stack or pricing or feature prioritization. It would be this: spend at least as much time distributing as you spend building. From day one.

Your product will never be finished. But your audience can start growing today.

What's your ratio — how many hours do you spend building vs telling people about what you built? Drop it in the comments, I'm genuinely curious if other solo founders have the same imbalance.

I Analyzed 30 Days of X Analytics for My Solo SaaS — Here's the Posting Schedule That Actually Drives Signups

Jack — Sun, 28 Jun 2026 13:03:59 +0000

P.S. If you want more solo founder distribution workflows like this one delivered to your inbox every week, join 1,500+ indie hackers getting them free: https://wuki.beehiiv.com/subscribe

When I launched my first SaaS product, I did what every solo founder does: I posted on X every day, replied to every comment, and watched my analytics tick up by maybe two or three views per week. After three months of that grind, I had 47 followers and exactly zero signups from organic X traffic.

So I stopped guessing. For 30 days, I treated my own X account like a data experiment — tracking every post, its time, its format, its engagement, and most importantly, its downstream conversion. Here's what the data actually said.

The Raw Numbers

Over 30 days I posted 87 times. I categorized each post into one of four formats:

Build-in-public updates — what I shipped that day, bugs I fixed, metrics I hit
Value threads — tutorials, observations, frameworks (usually 5–10 tweets long)
Questions/polls — simple engagement bait
Link drops — "just published a blog post, check it out"

I tracked impressions, likes, replies, reposts, profile visits, and link clicks. Then I cross-referenced those against my SaaS signup attribution.

What the Data Revealed

Timing mattered more than content. Posts between 7:00–8:30 AM EST got 3x more impressions than the same content posted at noon. The afternoon dead zone (1–3 PM EST) was brutal — almost zero engagement regardless of quality. Evening posts around 7–9 PM EST did well but mostly with existing followers, not new discovery.

Format dominance was lopsided. Value threads drove 68% of my profile visits but only 12% of my total posts. Build-in-public updates — which made up 40% of my posting — drove the most engagement per post but almost zero link clicks. Link drops got the most link clicks (obviously) but the fewest impressions because X's algorithm buries them.

The biggest surprise: questions and polls generated almost no long-term value. They'd spike for an hour then vanish.

Consistency beat virality. The week I posted at least twice daily (morning thread + afternoon update) saw 42% more profile visits than the week I let three days go dark. One viral post that got 15K impressions drove exactly zero signups. Consistent daily posting drove steady, compounding profile visits.

The Fix: A Schedule, Not a Firehose

Based on the data, I restructured my entire X approach:

One value thread per day at 7:30 AM EST — this is the discovery engine. I invest 20 minutes writing something actually useful (a lesson, a framework, a tool breakdown).
One build-in-public update at 7:30 PM EST — this builds trust and community. Doesn't have to be impressive, just honest.
One link drop per week on Saturday morning — when engagement is lower but the follower-to-click ratio is highest.
Zero unprompted questions or polls — they're vanity metrics in disguise.

This is where I ended up building xbeast.io — a scheduling tool that queues up this exact pattern so I don't have to think about it. I set the timing templates once, drop in my content for the week, and it posts at the optimized windows automatically. It's not about posting more; it's about posting at the right moments consistently.

The 30-Day Results

After 30 days on this schedule:

Profile visits: +280%
New followers: +340%
SaaS signups attributed to X: 11 (from zero the previous month)
Time spent on X daily: 25 minutes (down from 90+)

The biggest win wasn't the virality — it was the predictability. I knew roughly how many signups each week's threads would generate. That let me plan launches, content bets, and feature releases around reliable X traffic instead of hoping for a lucky viral post.

What I'd Do Differently

If I ran this experiment again, I'd track topic categories more granularly. Some threads clearly outperformed others (anything about "mistakes I made" vs. "here's a tutorial") but I didn't have clean enough data to quantify it. I'd also A/B post times more aggressively instead of relying on one early-morning window.

The Takeaway

Most solo founders treat X like a megaphone — shout loud enough and someone will hear you. The data says it's more like a drip irrigation system. Consistent, small, well-timed posts compound into steady traffic. The viral lottery is a distraction.

If you're spending more than 30 minutes a day on X and not seeing results, your problem isn't effort — it's timing and structure. Track your data for two weeks and I bet you'll find the same patterns I did.

What's your best posting time? I'm genuinely curious if morning slots work across niches or if this varies by audience — drop your experience in the comments.