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How to Check Whether AI Assistants Recommend Your Product

Yonatan Naor — Sat, 01 Aug 2026 05:38:54 +0000

Originally published at https://thicket.sh/blog/check-if-ai-recommends-your-product.

Being cited by an AI and being recommended by one are different standings, and most teams measure neither. Here is a repeatable check that takes minutes — and the three ways it will mislead you if you run it carelessly.

By Thicket AI Team · August 1, 2026 · 7 min read

Ask the model the question your buyer would actually ask — the category question, never your brand name — and record which products it names. Run it three or more times, because output varies between samples. If you never appear, that is a real and useful signal. What it is not is a measurement of how often assistants cite you as a source, which is a separate thing that can move in the opposite direction.

We built this check for a practical reason: we wanted to tell companies truthfully whether an assistant named them, and we were not willing to assert it without running it. What follows is the method and, more usefully, its failure modes.

The check

Write the buying question, not your brand. “What is the best SQLite editor for macOS?” — not “What is Base?” A model will happily discuss a brand named in the prompt while never surfacing it unprompted. That difference is the entire measurement.
Ask for specifics. Append something like “list the specific products you would recommend, with a one-line reason for each.” You want a list you can check a name against, not an essay.
Run it at least three times and count how many runs named you. One run is a coin flip; a count is a position.
Record who was named. The competitor list is more actionable than your own absence — it tells you which material the model actually learned from.
Match on brand and domain, with word boundaries. A short brand like “Base” will match inside “database” if you are careless, and you will record a false presence. ## The three ways this misleads

1. It is one model, not “AI”. A result from one assistant answering from training knowledge says nothing about the others, and nothing about live web-grounded search. Absent in one place does not mean absent everywhere. If you report this internally, name the model and the date, because both change.

2. A single run is noise. Sampling variance is real and large enough to flip a verdict. We treat any check that produced zero usable responses as an error rather than an absence — because the failure mode we most wanted to avoid was reporting “they were not named” when the truth was “the request failed.” That distinction matters more than it sounds: we separately discovered a metric of our own that had reported 0% for three months off 280 consecutive failed API calls, because a failure and a zero were represented identically.

3. Citation and recommendation are not the same thing. This is the one that surprises people. Our own portfolio is cited roughly 14,394 times in 28 days by one assistant — and a different model names us for zero of 40 category questions in our own niches. Both are accurate. Being used as a source and being recommended as a vendor are separate standings, and we currently hold only the first.

Validate the checker before you trust it

A test that always returns “absent” would look identical to a working one right up until you acted on it. So run a control: pick a company that obviously is well known in its category and confirm the check finds it.

When we did this, a household-name workspace tool came back named in every run, and a jobs marketplace we expected to be absent turned out to be named as well — correctly excluding it from our own outreach. Both results were more valuable than the absences, because they proved the instrument discriminates rather than merely agreeing with us.

If you are not named

The usual cause is a thin third-party footprint rather than any penalty. Models learn from what others wrote about you: independent comparisons, documentation, forum answers, category explainers. Your own marketing pages contribute far less than their prominence in your Google results suggests.

In our own data, the content that gets picked up shares one property — it answers a question with a specific, checkable, quotable answer. Comparisons, definitions and reference tables perform; comprehensive overviews do not, because there is no single passage to lift. We broke that down in what kind of pages AI assistants actually cite.

Frequently Asked Questions

How do I check if ChatGPT or Gemini recommends my product?

Ask the model the question your buyer would actually ask — the category question, not your brand name — and record which products it names. Run it several times rather than once, because model output varies between samples and a single run can miss you by chance. Searching your own brand name tells you almost nothing: the model will discuss a brand it has heard of even when it would never surface that brand unprompted. The useful test is whether you appear in an answer where you were not mentioned in the question.

How many times should I run the query?

At least three, and treat the result as a count rather than a verdict. In our own checks we record how many runs named the company, so a single unlucky sample never gets reported as an absence. Consistency matters as much as presence: appearing in one run out of five is a materially different position from appearing in five out of five, and a single-run test cannot distinguish them. If you are tracking this over time, hold the question wording and the run count fixed, or you will measure your methodology instead of your visibility.

Does being absent from an AI answer mean I have an SEO problem?

Not necessarily, and conflating the two is the most common mistake here. A model answering from training knowledge is reflecting what was written about you across the web, not what ranks today. You can rank first on Google for your category and still be absent, usually because the pages that rank are your own marketing pages while the pages models learn from are third-party comparisons, forum discussions and documentation. The two channels reward different things, which is why they can disagree so sharply.

Is being cited by an AI the same as being recommended by one?

No, and the distinction is worth holding onto. Being cited means a model used your page as a source when answering someone's question. Being recommended means the model names you as an option when someone asks what to use. They come apart completely — our own portfolio is cited roughly 14,394 times in 28 days by one assistant, while a different model names us for zero of 40 category questions in our own niches. Source-of-record and recommended-vendor are separate standings, and a strategy aimed at one will not automatically deliver the other.

What should you do if an AI does not name your product?

First check whether the material a model could learn from actually exists. Absence usually reflects a thin third-party footprint rather than a penalty — few independent comparisons, little documentation others can quote, nothing that states plainly what you do and who you are an alternative to. The content that tends to get picked up answers a question with a specific, checkable answer: head-to-head comparisons, clear definitions, reference tables. Pages written to be comprehensive rather than answerable do worse, because there is no single passage a model can lift and attribute.

Method and caveats

Our checks run against a single Gemini model answering from training knowledge — not a live web search, and not Copilot, ChatGPT, Claude or Perplexity. The 14,394 citation figure comes from Bing Webmaster Tools' AI Performance report for a 21-site portfolio over 28 days; Microsoft describes that data as a sample. The zero-of-40 figure is our own category-question check across seven niches. Neither generalises to assistants we did not test, and both are point-in-time — model behaviour changes without notice. For how the citation side is measured, see how to measure whether AI assistants cite your site; our full operating numbers, including what failed, are in the Thicket Report.

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Is It Bad to Eat Before Bed? What the Evidence Says

Yonatan Naor — Sat, 01 Aug 2026 05:38:52 +0000

Originally published at https://fit.thicket.sh/blog/is-it-bad-to-eat-before-bed.

By Dr. Sarah Okafor, Exercise Physiologist

For most people, no — what and how much you eat matters far more than the clock, and calories do not become more fattening after a certain hour. But the timing is not perfectly neutral either. In a tightly controlled trial where people ate identical meals either early or late, eating late increased hunger, decreased energy expenditure, and shifted fat-tissue gene expression toward storage. So a late meal is not harmful in itself, but for someone chasing fat loss it appears to make the job modestly harder — through appetite and expenditure, not through any special property of night-time calories. And in one specific case the folk rule is simply backwards: for lifters, protein before sleep is beneficial.

This question has two honest answers depending on why you are asking, which is why the internet disagrees with itself about it so consistently. Below are both.

What the Controlled Evidence Shows

The strongest study here matched calories precisely and varied only timing. Participants ate the same meals either early or roughly four hours later, in a controlled crossover. Late eating increased hunger, decreased 24-hour energy expenditure, and altered adipose-tissue gene expression in the direction of fat storage (Vujović and colleagues, Cell Metabolism 2022, PMID 36198293).

That is a real circadian effect, and it is worth stating what it is not: it is not evidence that a calorie eaten at 10pm contains more energy than one eaten at 6pm. The effect runs through how hungry you are afterwards and how much you burn, both of which are meaningful but modest next to total intake.

A broader review of night-time eating reaches a similar balanced conclusion — that the older blanket warnings were overstated, and that the composition and amount of the food matter more than the hour (Kinsey and Ormsbee, Nutrients 2015, PMID 25859885).

The Case Where the Rule Is Backwards

If you lift, pre-sleep protein is not something to avoid — it is something to consider adding. Casein taken before sleep is digested and absorbed through the night and raises overnight protein synthesis (Res and colleagues, 2012, PMID 22330017). Across a 12-week resistance-training programme, a pre-sleep protein drink produced greater gains in muscle mass and strength than placebo (Snijders and colleagues, Journal of Nutrition 2015, PMID 25926415). Roughly 30–40 g of a slow-digesting protein is the amount typically used.

“Never eat before bed” and “take casein before bed” are both widely repeated, and both cannot be general rules. The resolution is that they answer different questions — see how much protein you need to build muscle and protein distribution across meals.

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Two Answers, Depending on Why You Asked

If your goal is…Does late eating matter?What to doFat lossModestly, via hunger and expenditureControl total intake first; shift calories earlier if it is easyMuscle gainYes — in your favour30–40 g slow protein before sleepSleep qualityYes, for large or fatty mealsFinish a big meal ~2–3 h before lying downRefluxStronglyLonger gap; avoid large, high-fat late mealsBlood-sugar controlYes — glucose tolerance is poorer at nightFollow your clinician’s guidance

Why the Myth Persists Anyway

Because it is usually right about the outcome and wrong about the cause. Late eating really is associated with weight gain in observational data — but evening eating is disproportionately unplanned, calorie-dense, and continues past the point of hunger. It is when the surplus happens, not why it counts. Someone who eats a planned meal at 9pm and someone who grazes through three hours of television are doing very different things, and only one of them has a timing problem.

If you want the numbers your intake is actually being measured against, start with how many calories to eat to lose weight.

Sources and Methodology

Isocaloric late-eating crossover: Vujović N et al., Cell Metabolism 2022 (PMID 36198293). Night-time eating review: Kinsey AW, Ormsbee MJ, Nutrients 2015 (PMID 25859885). Pre-sleep protein and overnight recovery: Res PT et al., Medicine & Science in Sports & Exercise 2012 (PMID 22330017). Pre-sleep protein over 12 weeks of training: Snijders T et al., Journal of Nutrition 2015 (PMID 25926415). The 2–3 hour guidance for large meals reflects standard reflux and sleep-hygiene advice rather than a single trial, and is flagged as such. General information for healthy adults, not medical advice; anyone managing reflux or diabetes should follow their clinician. Last updated August 1, 2026.

Frequently Asked Questions

For most people, no — what and how much you eat matters far more than the clock. Calories do not become more fattening after a certain hour; a late meal counts the same as an early one. But timing is not entirely neutral either. In a tightly controlled crossover trial where participants ate identical meals either early or late, eating late increased hunger, decreased energy expenditure, and shifted fat-tissue gene expression toward storage (Vujović 2022, PMID 36198293). The practical reading: a late meal is not automatically harmful, but for someone trying to lose fat, eating late appears to make the job modestly harder through appetite and expenditure rather than through some property of night-time calories.Not directly, and mostly through behaviour. The strongest predictor of weight change is total energy balance over time, and late eating is often just when the excess happens — snacking after dinner is typically unplanned, calorie-dense, and eaten past the point of hunger. That said, the isocaloric evidence suggests a real, smaller circadian effect on top of the behavioural one: at identical calorie intake, later eating raised hunger and lowered energy expenditure. So the honest answer is that late eating does not make food fattening, but it can make you eat more and burn slightly less, and both nudge in the same direction.For general comfort and sleep, most guidance lands on finishing a substantial meal about two to three hours before lying down — largely to reduce acid reflux, which reliably worsens when you are horizontal on a full stomach. That is a digestive and sleep-quality rationale rather than a weight one. There is no evidence for a universal cutoff time such as 7pm or 8pm; what matters is the gap between a large meal and lying down, not the number on the clock. A small protein-containing snack much closer to bed is a different case entirely, and is generally fine.For people doing resistance training, the evidence points to good. Casein protein taken before sleep is digested and absorbed overnight and increases whole-body protein synthesis during the night (Res 2012, PMID 22330017). Over a 12-week resistance-training programme, a pre-sleep protein drink produced greater gains in muscle mass and strength than a placebo (Snijders 2015, PMID 25926415). This is one of the clearest cases where the folk rule — never eat before bed — points in the wrong direction for a specific goal. Roughly 30 to 40 g of a slow-digesting protein is the amount typically used.Usually reflux and blood-sugar rather than the eating itself. Lying down soon after a large meal makes acid reflux considerably more likely, which fragments sleep even when you do not fully wake. Very large or very fatty meals also prolong digestion and can raise core body temperature slightly, and a falling core temperature is part of how sleep is initiated. Heavily sugary snacks can produce a rise and fall in blood glucose overnight that some people experience as waking. None of this applies strongly to a modest, protein-containing snack — the culprit is generally volume, fat content, and proximity to lying down.Both are genuine exceptions and are worth taking seriously. For gastro-oesophageal reflux, a longer gap between the last meal and lying down is standard clinical advice, along with not eating large or high-fat meals late. For diabetes and insulin resistance, glucose tolerance is generally poorer in the evening than the morning, so an identical carbohydrate load can produce a larger glucose excursion at night. Anyone managing either condition should follow their clinician's guidance rather than general advice — this is one of the places where the population-level answer and the individual answer genuinely diverge.It can make it modestly harder, though not in the way the myth suggests. The mechanism is not that night-time calories are stored differently by some special rule; it is that in controlled conditions late eating increased hunger the following day and reduced energy expenditure, both of which work against a deficit. Add that late eating is disproportionately unplanned snacking, and the practical effect can be larger than the physiology alone. If your total intake is controlled and the late food is planned, the timing effect is small. If your late eating is what puts you over your target, that is the actual problem.

Start With the Number That Actually Matters

Timing is a small lever. Total intake is the large one. Enter your stats to get an evidence-based maintenance calorie and protein target in seconds — free and instant.

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Four Times Our Own Dashboards Lied To Us in Five Days

Yonatan Naor — Fri, 31 Jul 2026 08:18:08 +0000

Originally published at https://thicket.sh/blog/when-your-metric-is-broken-not-your-business.

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Measurement

A build outage we blamed on our code. A traffic decline that was a reporting gap. Citations that could never have become links. And a KPI that reported 0% off 280 consecutive failed API calls. Here is what each looked like from the inside.

By Thicket AI Team · July 31, 2026 · 9 min read

In five days we found four separate cases where a number we trusted was describing our instruments rather than our business. None were caught by the process whose job is checking numbers. All four were caught by chasing something that did not add up — and in every case the false reading was the one that confirmed what we already believed.

We publish our operating failures as a matter of course. This particular set is worth writing up because the failure mode generalises: if you run any automated measurement, some version of at least one of these is probably live in your stack right now.

1. The build outage that looked like a code regression

Every site in the portfolio suddenly failed to build, aborting with should not be imported outside of pages/_document while prerendering the error pages. That message points at router code these projects do not contain.

We stashed our changes; a clean checkout failed too. So it pre-dated our work — except the same commit had deployed successfully two days earlier. We suspected a dependency doing something odd in the bundle, and the compiled output supported it. Two fixes, both failed.

Then we built a different site, one that had compiled cleanly hours before with nothing changed since. It failed identically. That made it environmental, and the cause was an inherited NODE_ENV=development in the process environment, which makes a production build emit a dev build and trip that guard.

Cost: about an hour, and two confident fixes shipped against a theory that was wrong. Testing a second project would have taken thirty seconds.

2. The decline that was a reporting gap

Search Console showed our clicks sliding for three straight weeks — 67, then 64, then 62 — with week-over-week impressions at −8.1%, then −9.0%. We reported it as a genuine warning twice.

Before writing it up a third time, we checked which properties were falling. All 26. Including four that had been frozen for months with no changes at all.

That is the tell. The daily series showed roughly 28% of finalized days coming back near-zero — 16 to 293 impressions between normal days of 1,200 to 3,700, in clusters, every week or two. Any fixed-length window therefore sums a varying number of near-empty days, so the totals track the null count rather than performance. Our current seven-day window held four of them; the comparison window held five days rather than seven, and we were reporting the difference as a percentage.

Measured per valid day instead, clicks went 1.93 → 3.86, a doubling — while the totals fell. Both were true. We were reading the wrong one, three days before a monthly review that would have opened an investigation into a decline that did not exist.

3. Citations that could never have become links

This one is not a bug, which is what makes it interesting. Two real numbers that refused to reconcile: 14,394 AI citations in 28 days, and zero new referring domains.

We assumed a distribution problem and tested it — publishing hard to five channels produced no referring domains, confirming the symptom without explaining it. The answer was in the query data all along. Every one of our top 25 cited queries is a consumer question. Not one is a practitioner question.

Consumers do not have websites. Links come from people who publish. We had been measuring ourselves on an outcome that our audience was structurally incapable of producing, and scaling the citations would have produced more of the same nothing. Full breakdown in what kind of pages AI assistants actually cite.

4. The KPI that never measured anything

The worst one. We track a share-of-model metric — how often an AI names us for category questions in our niches. It had read 0.0% since April.

Every run had failed. Completely. Seven runs, 40 questions each, 280 consecutive failed API calls, every one silently recorded as “not mentioned.” The model had been retired and returned 404; the aggregation divided mentions by questions asked rather than questions answered, so 0 ÷ 40 came out as a clean, confident 0.0%.

It hid for three months for one reason: 0% was exactly what we expected. Our strategy predicted low AI visibility, so every reading confirmed the prior and nobody looked underneath. One of us even wrote a tidy rationale for it in a status report five days before finding the bug.

After fixing it, the first valid run returned 0.0% — with zero failures. The number did not change. Its meaning did completely: it went from uninterpretable noise to a measured baseline.

The two tells

Uniformity across things that should move independently. 26 sites falling together, including frozen ones. Two unrelated projects failing identically. When independent things move together, suspect the instrument before the world.
A number that matches what you expected. This is the dangerous one, because it feels like confirmation. The 0% share-of-model reading survived three months purely because it agreed with us. A metric that tells you what you already believe is the one you should audit first, not last. ## What we changed

Absence of data must not be representable as zero. Our metrics now return null when nothing was measured, carry the failure count alongside the result, and print an explicit no-valid-measurement warning instead of a percentage.
Rates per valid day, never totals per calendar window — and always report how many valid days a period contained.
Never compare windows of different lengths. Ours were quietly comparing seven days against five.
Fail loudly at the boundary. The deploy wrapper now refuses to run under a bad environment variable rather than shipping a broken build. ## Frequently Asked Questions

How do you tell a broken metric from a real decline?

The most reliable tell we have found is uniformity across things that should move independently. When 26 separate websites — including four we had frozen months earlier and not touched since — all dropped by a similar percentage on the same days, that was not 26 ranking events. Independent things moving together points at the instrument, not the world. The second tell is a number that exactly matches what you already expected, because that is the number you are least likely to audit. Our share-of-model KPI read 0% for three months and nobody checked it, precisely because 0% was what our strategy predicted.

Why do broken analytics report zero instead of an error?

Usually because a failure and a genuine zero are represented by the same value somewhere in the pipeline. Our share-of-model script divided mentions by the number of questions asked rather than the number actually answered. When every API call failed, the arithmetic produced 0 divided by 40 — indistinguishable from asking 40 times and never being mentioned. The fix is to make absence of data structurally different from a data point of zero: report null when nothing was measured, carry the count of failures alongside the result, and print an explicit no-valid-measurement warning rather than a percentage.

Why does Google Search Console show days with almost no impressions?

We do not know the cause on Google's side, and we have been careful not to guess. What we can report is that roughly 28% of finalized days on our domain come back at 16 to 293 impressions, against a normal range of 1,200 to 3,700, in clusters of one to five days every week or two. We verified it is not our pull: querying the API by date, by page and with no dimensions returns identical values, stable across repeated pulls and flagged finalized. The operational consequence matters more than the cause — any fixed-length window sums a varying number of these near-empty days, so window totals move with the null count rather than with performance.

What is the safest way to compare traffic across periods?

Compare rates per valid day rather than totals per calendar window, and always report how many valid days each period contained. Our 28-day totals were falling while clicks per live day were rising sharply — both facts were true at once and we were reading the wrong one. Also check that the two windows you are comparing are the same length: ours were quietly comparing seven days against five and reporting the difference as a percentage. And be wary of short windows; at seven days our own corrected metric still swung between +8% and −52% purely on which days landed inside it.

Do AI citations turn into backlinks?

Not in our data, and the reason is structural rather than fixable by volume. We accumulated 14,394 Copilot citations in 28 days and earned zero new referring domains over the same period. Looking at the actual queries that pulled our content into AI answers, all 25 of the top ones are consumer questions — is this service still active, when should I update this form, which option is fastest. Consumers do not have websites. Links come from people who publish, and none of our citations were reaching them. Scaling that citation volume tenfold would have produced tenfold of exactly nothing.

Method and caveats

All four cases are from a 21-site portfolio between 2026-07-27 and 2026-07-31, drawn from Google Search Console, Bing Webmaster Tools' AI Performance report, GA4, and our own tooling. The Search Console null-day behaviour is something we observed and verified but cannot explain — we confirmed it is not our data pull and have deliberately not guessed at Google's side. The citation figures come from one ecosystem (Microsoft) which describes its own AI data as a sample, and say nothing about other assistants. Our full operating numbers, including the experiments that failed, are in the Thicket Report; the measurement method is in how to measure whether AI assistants cite your site.

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How Much Should I Contribute to My 401(k)?

Yonatan Naor — Thu, 30 Jul 2026 06:03:25 +0000

Originally published at https://pay.thicket.sh/blog/how-much-should-i-contribute-to-my-401k.

By Jamie Reeves, Personal Finance Writer

A widely used target is 15% of gross pay including your employer’s match — but the order matters more than the number. Contribute at least enough to capture the full match first; that is an immediate return no investment reliably beats. If you carry high-interest debt, clearing it usually outranks contributing beyond the match. Then work toward 15% total. The ceiling on your own deferrals is **$24,500 for 2026, plus an $8,000 catch-up at 50 or older. Starting at 22, 10–15% is generally enough; starting at 45, it is usually 20% or more.**

“15%” gets repeated so often that people either hit it and stop thinking, or fall short and feel defeated. Both miss that the first few percentage points are worth far more than the last few.

The Priority Order

Contribute enough to get the full employer match. A 50% match on the first 6% of pay is a 50% return on that money before any market growth. Nothing else on this list competes with it. Contributing less than the match threshold is declining part of your compensation.
Clear high-interest debt. Credit card debt at 20–25% beats an uncertain market return reliably. Paying it off is a guaranteed return equal to its interest rate.
Build a small emergency fund. Without one, a car repair becomes new credit card debt or a 401(k) loan — and either undoes the contributions you were protecting.
Work up toward 15% of gross, including the match. If your employer contributes 4%, you need 11% to get there.
Then consider going further, up to the IRS limit. ## The 2026 Limits

Limit2026 amountYour elective deferrals*$24,500Catch-up, age 50+$8,000Catch-up, ages 60–63 (SECURE 2.0)$11,250Total annual additions (you + employer + after-tax)$72,000Total annual additions incl. catch-up$80,000 ($83,250 at ages 60–63)
Per the IRS. Employer matching does *not count against your personal $24,500 deferral limit — which is why the match is effectively free capacity.

What the Tax Break Actually Does

A traditional 401(k) contribution lowers your income tax but not your Social Security and Medicare tax. The contribution is excluded from the wages your income tax is computed on, so in the 22% bracket a $200 contribution reduces take-home by about $156, not the full $200. But it is still counted in your FICA wages, so you pay the full 7.65% on it either way.

That distinction surprises most people. The deductions that escape *both*income tax and FICA are HSA and FSA contributions and Section 125 premiums — see which paycheck deductions are pre-tax. For the now-versus-later trade, see Roth vs traditional 401(k).

By-Age Benchmarks (Use Loosely)

AgeCommon benchmark30~1× salary saved40~3× salary50~6× salary60~8× salary67~10× salary
These are widely circulated industry rules of thumb built on assumptions about retirement age, spending, and Social Security — not IRS rules, not requirements, and not personalised. Treat them as a direction check, not a grade.

If You Are Starting Late

The arithmetic is unforgiving but not hopeless. Compounding does most of the work across 30–40 years, so starting at 45 means buying growth with contributions instead of time — commonly 20–25% of gross. Three levers help: the age-50 catch-up, directing every raise straight into the contribution rate so your take-home never drops, and working a few years longer, which shortens the retirement being funded while lengthening the period funding it.

The One Mistake With a Real Penalty

Exceeding the deferral limit creates an excess deferral, which must be withdrawn by the following April 15 or it is taxed twice — once in the year contributed and again on distribution. It happens most often after a mid-year job change, because each employer tracks only its own plan and neither sees your combined total. If you switched jobs, add the deferrals from both W-2s and check. Same structural blind spot that causes over-withheld Social Security after a job change — see why your paycheck changed.

Sources and Methodology

Contribution and catch-up limits and annual additions: IRS 401(k) and Profit-Sharing Plan Contribution Limits. Excess deferrals and the April 15 correction deadline: IRS. FICA treatment: IRS Topic 751. The 15% target and the by-age multiples are widely used industry rules of thumb, flagged as such above rather than presented as official guidance. General information, not tax or investment advice; your plan documents govern. Last updated July 30, 2026.

Frequently Asked Questions

A widely used target is 15% of gross pay including your employer's match, but the order of operations matters more than the number. First contribute at least enough to capture the full employer match — that is an immediate return no investment reliably beats. Then, if you carry high-interest debt, clearing it usually outranks contributing beyond the match. After that, work toward 15% total, and if you can go further the ceiling is the IRS elective deferral limit of $24,500 for 2026. Someone starting at 22 can reach a comfortable retirement on roughly 10–15%; someone starting at 45 generally needs 20% or more, because they have fewer years of compounding to work with.You can defer up to $24,500 of your own pay in 2026. If you are 50 or older you can add a catch-up contribution of $8,000, and under SECURE 2.0 those aged 60 to 63 get a larger catch-up of $11,250. Separately, total annual additions — your deferrals plus employer contributions plus any after-tax contributions — cannot exceed $72,000, or $80,000 including catch-up ($83,250 for ages 60 to 63). Employer matching money does not count against your personal $24,500 deferral limit, which is why the match is effectively free capacity.Usually yes, but not always immediately. The match is the highest-priority dollar because it is an instant guaranteed return — a 50% match on the first 6% of pay is a 50% return on that money before any investment growth. Beyond the match, the honest comparison is against your alternatives. Credit card debt at 22% reliably beats an uncertain market return, so clearing it first is rational. No emergency fund is also a strong reason to pause: without one, a car repair becomes credit card debt or a 401(k) loan. Once high-interest debt is gone and you hold a few months of expenses, contributing past the match is usually the best available use of the money.A common benchmark suggests roughly 1× your salary saved by 30, 3× by 40, 6× by 50, 8× by 60, and 10× by 67. These are rules of thumb built on assumptions about retirement age, spending, and Social Security — not requirements, and not personalised. Their real value is directional: if you are meaningfully behind, the fix is raising your contribution rate now, because the variable you control is what you save rather than what the market returns. Being behind at 40 is common and recoverable; being behind at 60 leaves fewer options, which is precisely why the benchmarks are worth glancing at early.A traditional 401(k) contribution lowers your income tax but not your Social Security and Medicare tax. The contribution is excluded from the wages your income tax is computed on, so in the 22% bracket a $200 contribution reduces your take-home by roughly $156 rather than the full $200. But it is still included in your FICA wages, so you pay the full 7.65% on it regardless. A Roth 401(k) works in reverse — no deduction now, tax-free qualified withdrawals later. HSA contributions through payroll are the ones that escape both income tax and FICA.Higher than the standard advice, and the arithmetic is unforgiving. Compounding does most of the work over 30 to 40 years, so starting at 45 means you are buying growth with contributions rather than time. Many people in that position need 20–25% of gross pay to reach a comparable outcome. Three levers help: the age-50 catch-up ($8,000 in 2026, rising to $11,250 for ages 60–63), directing every raise straight into the contribution rate so your take-home never drops, and continuing to work a few years longer, which shortens the retirement being funded while lengthening the funding period. Starting late is much better than not starting.You can exceed the IRS limit, and it is worth avoiding. Deferring more than $24,500 in 2026 creates an excess deferral that must be withdrawn by the following April 15 or it is taxed twice — once in the year contributed and again when distributed. This happens most often to people who change jobs mid-year, because each employer tracks only its own plan and neither sees your combined total. If you switched employers, add the deferrals from both W-2s and check. There is also a softer version of contributing 'too much': funding a 401(k) heavily while carrying 22% credit card debt or holding no emergency savings is legal, but usually not the best use of the dollar.

See What a Contribution Change Costs You

Enter your salary, filing status, state, and 401(k) percentage. The calculator shows exactly how much take-home pay each contribution rate actually costs — usually less than people expect. Free and instant.

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What Kind of Pages AI Assistants Actually Cite

Yonatan Naor — Thu, 30 Jul 2026 06:03:23 +0000

Originally published at https://thicket.sh/blog/what-kind-of-pages-ai-assistants-cite.

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Data

We run 21 sites that Microsoft Copilot cites about 14,394 times a month. We classified the 25 most-cited pages by shape to see what they have in common — and found something uncomfortable about what all those citations were worth.

By Thicket AI Team · July 30, 2026 · 8 min read

Four page shapes account for 80% of our most-cited pages: head-to-head comparisons, definitions, reference tables, and trend explainers — each exactly 20% of the top 25. What they share is that each answers a question with a specific, checkable, quotable answer. Assistants cite what they can lift a sentence out of. And the uncomfortable part: across the same period those 14,394 monthly citations produced zero new referring domains, for a reason that turns out to be structural rather than fixable by volume.

Most writing about AI citation is inference from the outside. This is from the inside, on a portfolio large enough to have a distribution — with the method published separately so you can reproduce it on your own domain.

The Classification

We took the 25 most-cited pages from Bing's AI Performance report and classified each by shape. Counts, and total citations attributable to each shape:

ShapePagesShareCitationsTrend / event explainer520%2,796Comparison (X vs Y)520%1,952Definition / what-is520%1,853Reference data / table520%1,695Direct question page28%753Listicle / best-of14%666Other28%674
The even split across the top four is more striking than any single winner. It suggests the shape that matters is not a specific format but a property those formats happen to share.

The Shared Property

Every one of those shapes answers a question that has a specific, checkable answer that fits in a sentence.

A comparison resolves to this one, because of that.
A definition resolves to it means this.
A reference table resolves to for your case, the number is X.
A trend explainer resolves to here is what it is and why now. An assistant assembling an answer needs a passage it can lift and attribute. Pages written to be comprehensive rather than answerable do worse, because there is no single passage that resolves the question — the answer is distributed across 3,000 words and the model has nothing crisp to quote.

This matches what we changed and saw work: put the direct answer in the first line in bold, keep a primary source next to each factual claim, and include one table. It is close to the opposite of writing for a word count.

The Part That Should Give You Pause

We accumulated 14,394 citations per 28 days. Over the same period we earned zero new referring domains. Not few. Zero.

The grounding-query table explains it. Our top 25 queries by citation volume, every one of them:

tuscan mom aesthetic · salary overtime law · is myspace still active · federal overtime laws · best AI tools for developer productivity · office siren · employee tax withholding update timing · when to update W4 · w2 example · fastest VPN speeds · cold plunge vs sauna · protein requirements toning vs bulking · fica vs federal tax

These are consumer questions, all of them. Not one is a practitioner question — nobody reaching us asked how to measure AI citations, how to run content operations, or which tool to use.

Which produces the mechanism, and it is not a distribution problem:

We are cited to people who ask questions. Links come from people who publish answers. Consumers do not have websites.

Someone asking whether MySpace is still active gets a good answer partly built from our page, and is satisfied. They have no blog, no newsletter, no editorial calendar. There is no path from that citation to a link however many times it happens — and scaling it tenfold yields tenfold of exactly nothing.

What We Take From It

Citations and links are different products and need different content. Consumer-question content earns citations and traffic. Only practitioner-question content can earn links, because only practitioners publish.
Do not judge AI visibility on analytics sessions. 14,394 citations produced 126 assistant-referred sessions — about a hundred citations per visit, because a good citation answers the question inside the chat.
Do not judge commercial value on citations either. Same numbers, opposite error. They measure attention, not intent and not authority.
Citations appear to behave like a stock. Our most-cited property has published nothing for a month and still leads the portfolio. Rankings decay when you stop; citations so far have not. We are re-measuring that at 60 and 90 days before believing it. ## Frequently Asked Questions

What kind of content do AI assistants cite most?

In our data, four shapes account for 80% of the most-cited pages: head-to-head comparisons (X vs Y), definitions of a term someone just encountered, reference tables of values by category, and explainers of a specific trend or event. Each accounts for 20% of the top 25. What they share is that they answer a question with a specific, checkable, quotable answer — a number, a definition, a direct comparison. Assistants cite what they can lift a sentence out of. Pages built to be comprehensive rather than answerable perform worse, because there is no single passage to quote.

Does publishing more content increase AI citations?

Not reliably, in our experience. We tested volume directly and rejected it — more pages of the same shape did not produce proportionally more citations. What moved the number was writing pages that answer a specific question with a liftable answer, and citing a primary source next to each claim. We also found citations behave more like a stock than a flow: our most-cited property has published nothing for a month and still holds the largest block of citations in the portfolio. Rankings decay when you stop publishing; citations so far have not.

Do AI citations bring traffic?

Some, but far less than the citation count suggests, because a good citation often answers the question inside the chat and produces no click at all. Over an identical 28-day window our portfolio recorded 14,394 citations and 126 assistant-referred sessions — roughly a hundred citations per visit. Both numbers are real and they measure different things. Judging AI visibility by analytics sessions alone understates it by about two orders of magnitude; judging commercial value by citations alone overstates it by about the same.

Do AI citations produce backlinks?

In our data, no — and this was the most uncomfortable thing we found. Over the period we accumulated 14,394 citations per 28 days, new referring domains stayed at zero. The grounding-query table explains why: every one of our top 25 queries is a consumer question, and consumers do not have websites. Links come from people who publish. If your citations are earned on questions asked by readers rather than by writers, scaling that volume produces more of the same nothing.

How do you find out which queries you are cited on?

Bing Webmaster Tools has an AI Performance report showing citations by Copilot and partner models, broken out by grounding query and by page. It is the only first-party citation data any major platform publishes, and there is no API — we checked every plausible endpoint and got 404s, so it has to be read from the interface. Verify your root domain rather than each subdomain and one read covers a whole portfolio. It says nothing about ChatGPT, Claude, Gemini or Perplexity, so treat it as a sample of one ecosystem rather than a total.

Method and Caveats

Data is from Bing Webmaster Tools' AI Performance report (Microsoft Copilot and partner models) for a 21-subdomain portfolio, 3-month window, read 2026-07-26, plus GA4 referrer segmentation and Google Search Console over the 28 days ending 2026-07-24. The full method, including what each measurement misses, is in how to measure whether AI assistants cite your site.

Honest limits. This is one portfolio in one ecosystem — Bing reports only Microsoft-family citations and says nothing about ChatGPT, Claude, Gemini or Perplexity, and Bing itself describes its AI Performance data as a sample. The shape classification is our own judgement applied to 25 pages; a different taxonomy would produce different buckets, and 25 is a small n. Our portfolio skews to calculators, consumer finance, fitness and trend explainers, which plausibly biases which shapes appear at all. Treat the direction as informative and the percentages as indicative. Our own numbers, including the experiments that failed, are in the Thicket Report.

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How Do ETFs Work? A Plain-English Explanation

Yonatan Naor — Wed, 29 Jul 2026 11:04:08 +0000

Originally published at https://etf.thicket.sh/blog/how-do-etfs-work.

An ETF is a fund that owns a basket of assets — often hundreds or thousands of stocks or bonds — and sells shares in itself that trade on a stock exchange like any ordinary stock. Buy one share and you own a proportional slice of everything inside. Two things make it behave differently from a traditional mutual fund: it trades continuously through the day at a market price rather than once daily at a computed value, and it uses a creation-and-redemption mechanism with large institutions that keeps the market price tethered to the value of the holdings — the same mechanism that gives ETFs their tax efficiency.

Most explanations stop at “a basket that trades like a stock,” which leaves the interesting question unanswered: if the share price is set by supply and demand on an exchange, what stops it drifting away from what the fund actually owns? The answer is the part worth understanding.

1. The Basket

The fund holds real assets. A total-market equity ETF owns shares in thousands of companies; a bond ETF owns thousands of individual bonds; a gold ETF owns bullion. Divide the value of everything it owns, minus liabilities, by the number of shares outstanding, and you get net asset value — the honest per-share worth of the fund at that moment.

Most ETFs track an index, meaning the basket is chosen by a published rule rather than by a manager's judgement. That is why costs are low: following a rule is cheap. For how a fund's ongoing cost is deducted, see how an ETF expense ratio is charged.

2. The Exchange Listing

Shares of the fund are listed on an exchange and trade all day at whatever price buyers and sellers agree on. You can buy at 10:04am and sell at 2:15pm. A mutual fund, by contrast, transacts once per day at the NAV computed after the close.

An important consequence: when you buy an ETF share, your money usually goes to another investor, not to the fund. You are trading on the secondary market, and the fund's holdings are untouched. That is structurally different from a mutual fund, where your money flows in and the manager deploys it.

3. The Arbitrage Loop That Keeps the Price Honest

This is the mechanism that makes the whole thing work, and it involves institutions called authorized participants.

SituationWhat the authorized participant doesEffect on priceETF trades above NAVBuys the underlying basket, delivers it to the fund for newly created ETF shares, sells those shares at the higher market priceNew supply pushes the price down toward NAVETF trades below NAVBuys cheap ETF shares on the market, redeems them with the fund for the underlying basket, sells the basketDemand pushes the price up toward NAV
Both trades are profitable for the participant, which is the point: nobody enforces the tracking — the profit motive does it, continuously. It is why a large index ETF trades within pennies of its underlying value nearly all the time, and why the mechanism strains in thinly traded funds or during severe market stress, when assembling or valuing the basket becomes harder.

4. Why the Tax Treatment Is Different

Notice that redemptions are settled in kind — the fund hands over securities rather than selling them for cash. That detail produces the tax advantage.

When a mutual fund investor sells, the fund often must sell holdings to raise cash, and the resulting capital gain is distributed to everyone still in the fund, including people who did nothing. An ETF's in-kind exchange is generally not a taxable sale for the fund, so broad index ETFs frequently distribute no capital gains at all. Your tax bill stays largely under your control — you owe when you choose to sell. More in how ETFs are taxed and ETF vs mutual funds.

5. How It Actually Pays You

Price appreciation. Holdings rise, NAV rises, share price follows; you realise it on sale.
Distributions. The fund collects dividends and interest, subtracts expenses, and passes the rest through — usually quarterly for stock ETFs and monthly for bond ETFs. See do ETFs pay dividends. A fund holding assets that generate no income — physical gold, say — offers only the first.

6. What It Costs, and What Can Go Wrong

The expense ratio is the headline cost, commonly 0.02%–0.09% for broad index funds, accrued daily inside NAV so it never appears as a charge. Sitting outside it: the bid-ask spread when you trade, any premium or discount to NAV, and the fund's own internal trading costs.

On risk, the honest framing is that “ETF” is a wrapper, not a risk level. A total-market index fund and a leveraged single-sector product are both ETFs and are not comparable. The dominant risk is simply that the assets inside can fall. Structure-specific risks are narrower: wider spreads and larger NAV deviations in thin or hard-to-value funds, especially under stress, and leveraged and inverse products that reset daily and are not built for long holds. A fund can also close — which returns your money rather than losing it, as covered in what happens when an ETF closes.

Sources

Fund structure, exchange trading, creation and redemption, and required prospectus disclosure: U.S. Securities and Exchange Commission, Mutual Funds and ETFs and Investor.gov on mutual funds and ETFs. Net asset value: Investor.gov, Net Asset Value. Typical expense-ratio ranges reflect fees observed across large US-listed ETFs and change over time.

Caveats

This describes US-regulated ETFs and is general information, not investment advice. Any specific fund's holdings, costs, distribution schedule, and risks are set out in its prospectus on the issuer's own site, which is the authoritative source when a third-party data provider disagrees.

Frequently Asked Questions

How do ETFs work?An ETF is a fund that owns a basket of assets — usually hundreds or thousands of stocks or bonds — and sells shares in itself that trade on a stock exchange like any single stock. Buy one share and you own a proportional slice of everything the fund holds. Two features make it different from a traditional mutual fund. It trades continuously through the day at a market price, rather than once daily at a computed value. And it uses a creation-and-redemption mechanism with large institutional firms to keep that market price tethered to the value of the underlying holdings, which also gives ETFs their well-known tax efficiency.What keeps an ETF's price close to the value of what it holds?An arbitrage loop run by institutions called authorized participants. Every ETF has a net asset value — the per-share value of everything it owns. If the ETF's market price drifts above NAV, an authorized participant can assemble the underlying basket of securities, deliver it to the fund in exchange for newly created ETF shares, and sell those shares at the higher market price. If the price falls below NAV, the reverse: buy cheap ETF shares, redeem them with the fund for the underlying basket, sell the basket. Both trades profit the participant and push the price back toward NAV. Nobody enforces the tracking; the profit motive does it continuously.Where does an ETF's money go when you buy a share?Usually to another investor, not to the fund. The overwhelming majority of ETF trades happen on the secondary market — you buy from whoever is selling, the same as with a stock, and the fund's assets are unaffected. New shares are only created when an authorized participant delivers a basket of securities to the fund, which happens in large blocks and typically only when demand has pushed the price away from NAV. This is a genuine structural difference from a mutual fund, where your purchase money flows into the fund and the manager buys securities with it.How do ETFs make money for you?Two ways, and they mirror owning the underlying assets directly. Price appreciation: if the securities the fund holds rise in value, NAV rises and so does the share price, and you realise that gain when you sell. And distributions: the fund collects the dividends its stocks pay and the interest its bonds pay, subtracts its expenses, and passes the rest to shareholders — typically quarterly for stock ETFs and monthly for bond ETFs. A fund holding assets that produce no income, such as a physical-gold ETF, offers only the first.Why are ETFs more tax-efficient than mutual funds?Because of how redemptions work. When a mutual fund investor sells, the fund often has to sell securities to raise cash, and any capital gain from that sale is distributed to everyone still holding the fund — including people who did nothing. An ETF instead hands a basket of securities to the authorized participant in an in-kind exchange, which is generally not a taxable sale for the fund. The practical result is that broad index ETFs frequently distribute no capital gains at all, so your tax bill is largely under your own control: you owe when you choose to sell.What does an ETF actually cost to own?The headline cost is the expense ratio, quoted annually but accrued daily out of fund assets before the share price is calculated, so it never appears as a charge on your statement. Broad index ETFs commonly run 0.02% to 0.09%. Beyond that sit costs the ratio excludes: the bid-ask spread you pay when trading, any premium or discount to NAV, and the fund's own internal trading costs. For a large, liquid fund held long term the expense ratio dominates. For a thin or exotic one, the spread can easily exceed a year of expense ratio in a single round trip.Are ETFs safe, and what can go wrong?The structure itself is well-regulated and durable, but 'ETF' describes a wrapper, not a risk level — a total-market index fund and a leveraged single-sector product are both ETFs and are not remotely comparable. The real risks are the ordinary ones: the assets inside can fall in value, and you carry that fully. Structure-specific issues are narrower — wider spreads and larger NAV deviations in thinly traded or hard-to-value funds, particularly during market stress, and the fact that leveraged and inverse products reset daily and are not designed to be held long term. A fund can also close, though that returns your money rather than losing it.how ETFs workNAVcreation and redemptionauthorized participantin-kindtax efficiencyindex fundsSEC← More fund analysis

How Long Does It Take to Build Muscle? (Realistic Timeline)

Yonatan Naor — Wed, 29 Jul 2026 11:04:06 +0000

Originally published at https://fit.thicket.sh/blog/how-long-does-it-take-to-build-muscle.

By Dr. Sarah Okafor, Exercise Physiologist

Measurable muscle growth takes about 8 to 12 weeks of consistent training. Change other people notice usually takes 3 to 6 months. The catch is that the first few weeks feel like the fastest progress you will ever make and are mostly not muscle: early strength gains come from your nervous system learning the movement, and early size changes are largely swelling from muscle damage plus water and glycogen drawn into the tissue. Real hypertrophy starts accumulating underneath that, and only becomes measurable once the early swelling settles.

That gap between how progress feels and what is actually happening is why so many people quit around week four, exactly when the real process is beginning. Below is the honest timeline, what drives the rate, and why the mirror lies early on.

The First Three Weeks Are Not Muscle

Damas and colleagues tracked muscle protein synthesis alongside actual hypertrophy through the first weeks of training and found that early synthesis is directed at repairing damage, not building new tissue — the two only start corresponding once the damage response attenuates (Journal of Physiology 2016, PMID 27219125). Studies measuring muscle thickness very early therefore tend to overstate growth: the muscle is swollen, not bigger.

Even research designed to catch hypertrophy as early as possible finds it takes weeks of high-intensity work before architectural change is detectable (Seynnes and colleagues, PMID 17053104). Meanwhile your strength climbs quickly, because you are getting better at recruiting and coordinating the muscle you already have. Strength and size are related, but early on they move for different reasons.

A Realistic Timeline

TimeframeWhat is actually happeningWhat you noticeWeeks 1–3Neural adaptation; damage repair; water and glycogenStrength climbing fast, muscles feel fuller, sorenessWeeks 4–8Hypertrophy begins accumulating; swelling subsidesOften feels like a stall — the discouraging phaseWeeks 8–12Measurable growthClothes fit differently; tape and scale moveMonths 3–6Growth compoundsOther people start commentingYear 1+Rate slows substantiallyProgress requires deliberate programming

How Much, Per Month

A well-trained, well-fed beginner can realistically add roughly 1–2 lb of muscle per month, with women averaging around half that, and the rate falls considerably after the first year. A widely used rough guide puts lifetime natural gain for men at roughly 20–25 lb in year one, about half that in year two, half again in year three, and a few pounds a year thereafter.

Those monthly and yearly figures are practitioner estimates that have held up well in practice, not outputs of a controlled trial. Use them to calibrate expectations, not as a prediction for any individual.

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What Sets the Pace

Training age. The single biggest factor. Beginners gain several times faster than experienced lifters, and nothing recovers that advantage once it is spent.
Progressive overload. The stimulus has to keep increasing. See progressive overload for beginners vs intermediates.
Weekly volume. There is a clear dose-response — more weekly sets produce more growth, up to a point (Schoenfeld 2017, PMID 27433992).
Protein and calories. Protein supplementation meaningfully augments resistance-training gains (Morton 2018, PMID 28698222). Targets in how much protein you need to build muscle.
Sleep and recovery. Muscle is built during rest, not during the session — see how many rest days you need.
Consistency. Twelve merely-adequate weeks beat four excellent weeks followed by eight missed ones. The adaptation is cumulative. ## Two Things That Distort the Timeline

Fat loss makes muscle visible faster than muscle growth does. Someone with more body fat can look substantially different at 12 weeks having added only a few pounds of tissue, because the change is mostly the layer over the muscle thinning. If being noticed is the goal, body composition beats mass — see body recomposition timelines.

Soreness is not a progress meter. It reflects unaccustomed stress, and it fades as you adapt — which is a sign of adaptation, not of stalling. See does soreness mean growth.

Sources and Methodology

Early-phase protein synthesis and damage: Damas F et al., Journal of Physiology 2016 (PMID 27219125). Early hypertrophy detectability: Seynnes OR et al., Journal of Applied Physiology 2007 (PMID 17053104). Volume dose-response: Schoenfeld BJ et al., Journal of Sports Sciences 2017 (PMID 27433992). Protein supplementation: Morton RW et al., British Journal of Sports Medicine 2018 (PMID 28698222). Monthly and annual gain figures are practitioner estimates, flagged as such above. General information for healthy adults, not medical advice. Last updated July 29, 2026.

Frequently Asked Questions

Measurable muscle growth typically takes 8 to 12 weeks of consistent training, and visible change to others usually takes 3 to 6 months. The first few weeks feel dramatic but are mostly not muscle: early strength gains come from the nervous system learning the movement, and early size changes are substantially swelling from muscle damage rather than new tissue. Damas and colleagues showed that muscle protein synthesis in the first three weeks tracks damage repair, and only begins to correspond with real hypertrophy once that damage subsides (PMID 27219125). Genuine, measurable growth is a 2-to-3-month project at minimum.A realistic ceiling for a well-trained, well-fed beginner is roughly 1 to 2 pounds of muscle per month for men and about half that for women, and it slows considerably after the first year. A common rough guide is around 20 to 25 pounds of lifetime natural muscle gain for men in year one, halving in year two, halving again in year three, and then measured in a few pounds a year. These figures are practitioner estimates rather than precise trial outputs, so treat them as a sanity check on expectations, not a prediction. The direction is what matters: the newer you are, the faster it goes.Three things that are not new muscle tissue. Training draws water and glycogen into the muscle, which increases its volume. Unaccustomed training causes swelling from muscle damage, which temporarily inflates measurements. And the pump during and after a session is transient blood flow. All are real and visible, and none is hypertrophy. This is precisely why early-phase studies that measure muscle thickness in the first weeks tend to overstate growth — the tissue is swollen, not larger. It also explains the demoralising moment around week four when the initial change seems to stall: the swelling has settled and actual growth has not yet caught up.Usually 3 to 6 months of consistent training, and often sooner if you are also losing fat, because reducing the layer over the muscle reveals shape faster than adding tissue does. People carrying more body fat frequently look meaningfully different at 12 weeks while having gained only a few pounds of actual muscle, since the visual change is driven mostly by the fat loss. Conversely, a lean beginner can add real muscle for months before anyone comments. If being noticed is the goal, body composition matters more than muscle mass alone.It slows the process but does not stop it. Older adults build muscle more slowly than younger adults, largely because of anabolic resistance — the muscle responds less strongly to the same protein and training stimulus. The practical adjustments are a somewhat higher protein intake, an emphasis on progressive resistance training rather than only cardio, and more patience with the timeline. Meaningful hypertrophy is well documented into the seventies and beyond. Starting at 50 or 60 means a slower curve, not an absent one.In rough order of impact: training age (beginners gain fastest by a wide margin), progressive overload, total weekly volume, protein and calorie intake, sleep, and genetics. Volume has a clear dose-response — more weekly sets produce more growth up to a point (Schoenfeld 2017, PMID 27433992) — and protein supplementation meaningfully augments gains from resistance training (Morton 2018, PMID 28698222). Consistency dominates all of it. Twelve mediocre weeks beat four excellent weeks followed by eight missed ones, because the adaptation you are chasing is cumulative.Legs follow the same 8-to-12-week timeline for measurable change, but they often look slower for two reasons. They start from a larger base — you walk on them daily — so a given amount of new tissue is a smaller percentage change and less visually obvious. And many people train legs less hard than upper body because it is more uncomfortable. Quadriceps in particular respond well to sufficient volume and full range of motion. The timeline is not different; the perception is.

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Do I Have to Pay Taxes on Social Security? (Combined Income Explained)

Yonatan Naor — Tue, 28 Jul 2026 04:41:55 +0000

Originally published at https://pay.thicket.sh/blog/do-i-have-to-pay-taxes-on-social-security.

By Jamie Reeves, Personal Finance Writer

Only if your other income is high enough. The test uses “combined income” — your adjusted gross income, plus any tax-exempt interest, plus half of your Social Security benefits. Below $25,000 filing single, or $32,000 married filing jointly, none of your benefits are taxable. Between $25,000 and $34,000 single ($32,000–$44,000 joint), up to 50% of benefits can be taxable. Above $34,000 single ($44,000 joint), up to 85% can be. Crucially, “85% taxable” means 85% of your benefit is added to your taxable income — it is not an 85% tax rate, and at least 15% of your benefits are always tax-free.

Two things make this question harder than it should be: the calculation uses a figure called combined income that appears almost nowhere else in the tax code, and the widely-quoted “85%” sounds like a rate when it is a share. Both are cleared up below, along with the age myth.

Step 1: Work Out Your Combined Income

Combined income is a specific formula:

Your adjusted gross income (wages, pensions, IRA and 401(k) withdrawals, interest, dividends, capital gains)
plus tax-exempt interest — municipal bond interest counts here, even though it is otherwise tax-free
plus one-half of your Social Security benefits That half-benefit detail matters. People often add their whole benefit, land above a threshold, and assume they owe tax when they do not. Only half of the benefit enters the test.

Step 2: Compare It to the Thresholds

Filing statusNone taxableUp to 50% taxableUp to 85% taxableSingle / head of household / qualifying surviving spouseUnder $25,000$25,000 – $34,000Over $34,000Married filing jointlyUnder $32,000$32,000 – $44,000Over $44,000Married filing separately, lived apart all yearUnder $25,000$25,000 – $34,000Over $34,000Married filing separately, lived together at any pointBase amount is $0 — up to 85% taxable from the first dollar
Base amounts per IRS Publication 915. These thresholds are not indexed to inflation and have not changed since the 1980s and 1990s — which is why a steadily growing share of retirees crosses them each year.

The 85% Misunderstanding

“Up to 85% of your benefits are taxable” is a statement about how much of the benefit enters your taxable income. It is not a tax rate. Worked through:

You receive $30,000 in Social Security for the year.
Your combined income puts you in the top band, so 85% of the benefit — $25,500 — is added to taxable income.
That $25,500 is taxed at your ordinary rate. In the 12% bracket, that is about $3,060.
$3,060 on a $30,000 benefit is an effective rate of about 10% — not 85%. And the 85% is a ceiling. No matter how high your income goes, at least 15% of your Social Security benefits are never taxed.

The Age Myth

There is no age at which Social Security benefits stop being taxable.Not 65, not 70, not full retirement age. Taxability is determined by combined income and nothing else. A 90-year-old with a large required minimum distribution pays tax on benefits; a 62-year-old with modest other income pays none.

What genuinely changes with age is how much other income you have. Required minimum distributions from traditional retirement accounts push combined income up, which is why some retirees find benefits become taxable years after they started collecting, with nothing about the benefit itself having changed.

Levers That Actually Reduce the Bill

Every lever works by moving combined income, because that is what the test reads:

Roth withdrawals do not count toward combined income. Building Roth balances before claiming is the cleanest structural fix — see our Roth vs traditional 401(k) comparison.
Time large withdrawals and capital gains into years before you claim, or into years you can absorb them.
Qualified charitable distributions from an IRA after age 70½ satisfy required minimum distributions without raising adjusted gross income.
Municipal bonds do not help here. Tax-exempt interest is explicitly added back into combined income. ## Paying the Tax

If you expect to owe, you can have federal tax withheld directly from your benefit by filing Form W-4V with the Social Security Administration, choosing 7%, 10%, 12%, or 22%. The alternative is quarterly estimated payments, which work but mean four deadlines a year to remember. For how withholding works on earned income while you are still working, see when to update your W-4 and how much tax comes out of your paycheck. If you are still working while collecting, note that your wages remain subject to FICA regardless — see FICA vs federal income tax.

Sources and Methodology

Base amounts, the combined-income definition, and the 50%/85% inclusion rules: IRS Publication 915 (Social Security and Equivalent Railroad Retirement Benefits) and IRS Topic 423. Voluntary withholding from benefits: IRS Form W-4V. The worked example uses a 12% ordinary rate for illustration; your own rate depends on total taxable income. State treatment varies and is changing quickly — verify your state's current rules. General information, not tax advice. Last updated July 28, 2026.

Frequently Asked Questions

Only if your other income is high enough. The test uses 'combined income' — your adjusted gross income, plus any tax-exempt interest, plus half of your Social Security benefits. If that total is under $25,000 filing single (or $32,000 married filing jointly), none of your benefits are taxable. Between $25,000 and $34,000 single ($32,000–$44,000 joint), up to 50% of benefits can be taxable. Above $34,000 single ($44,000 joint), up to 85% can be taxable. Roughly 40% of recipients pay some tax on their benefits; the rest pay none.It is a specific figure invented for this test and used almost nowhere else, which is why it confuses people. Combined income equals your adjusted gross income, plus any tax-exempt interest (yes, municipal bond interest counts here even though it is otherwise tax-free), plus one-half of the Social Security benefits you received that year. Note that only half your benefits go into the calculation — a detail that trips up people who assume the whole payment counts and conclude they owe tax when they do not.No, and this is the single most common misunderstanding. The 85% figure is the portion of your benefits that becomes part of your taxable income — it is not a tax rate. If you receive $30,000 in benefits and 85% is taxable, then $25,500 gets added to your taxable income and is taxed at your ordinary rate. Someone in the 12% bracket would owe about $3,060 on that, roughly 10% of the benefit, not 85% of it. The maximum share of benefits that can ever be taxable is 85%; at least 15% of your benefits are always tax-free.There is no such age. This is a persistent myth — you may have heard 65, 70, or 'after full retirement age.' None of them are real. The taxability of benefits depends entirely on your combined income, not on how old you are. A 90-year-old with substantial retirement income pays tax on benefits; a 62-year-old with little other income pays none. What does change with age is the amount of other income you tend to have, which is why some people's benefits become taxable later in retirement when required minimum distributions begin.Usually not. The large majority of states do not tax Social Security benefits at all, and several states have no income tax whatsoever. A small and shrinking number of states do tax benefits, typically with their own income exemptions and age-based carve-outs that are often more generous than the federal rules. Because states have been steadily repealing these taxes in recent years, check your own state's current rules rather than relying on an older list — this is one of the fastest-changing corners of retirement tax.Because the test keys off combined income, the levers are all about managing that number. Roth withdrawals do not count toward combined income, so building Roth balances before claiming can keep you under a threshold. Timing large withdrawals or capital gains into years when you are not yet collecting benefits helps. Qualified charitable distributions from an IRA after age 70½ satisfy required minimum distributions without adding to adjusted gross income. And remember tax-exempt municipal bond interest does count here, so it does not help with this particular test. Coordinating withdrawals across account types is genuinely worth professional advice — the thresholds are not indexed to inflation, so more retirees cross them every year.If you expect to owe, yes — it is simpler than quarterly estimated payments. You can request federal withholding from benefits by filing Form W-4V with the Social Security Administration, choosing 7%, 10%, 12%, or 22% of your benefit. The alternative is paying quarterly estimated tax, which works but requires you to remember four deadlines a year. Many retirees find withholding less error-prone, particularly in the first year of benefits when the tax consequence is unfamiliar.

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Does Creatine Cause Hair Loss? What the Evidence Actually Shows

Yonatan Naor — Tue, 28 Jul 2026 04:41:51 +0000

Originally published at https://fit.thicket.sh/blog/does-creatine-cause-hair-loss.

By Dr. Sarah Okafor, Exercise Physiologist

There is no direct evidence that creatine causes hair loss. No study has ever measured hair as an outcome and found that creatine caused it to fall out. The entire belief traces to a single 2009 trial of 20 college rugby players that reported a rise in the DHT-to-testosterone ratio — a hormone marker — and did not look at hair at all. That finding has never been replicated in the fifteen-plus years since, despite creatine being one of the most studied supplements in existence. If you are genetically predisposed to male-pattern baldness you may lose hair whether or not you supplement; the evidence does not say creatine is the reason.

This is a good case study in how one small result becomes received wisdom. Below is exactly what that study did and did not show, why the leap from “DHT went up” to “you will go bald” skips a step that matters, and what creatine’s genuinely documented side effects are.

The One Study Behind the Whole Belief

In 2009, researchers ran a three-week crossover trial in 20 college-aged rugby players and measured hormone levels (van der Merwe and colleagues, Clinical Journal of Sport Medicine, PMID 19741313). After seven days of loading at 25 g/day, the ratio of dihydrotestosterone (DHT) to testosterone rose roughly 36%, and stayed about 22% above baseline through two weeks of 5 g/day maintenance.

Four details rarely travel with that headline:

Hair was never measured. Not counted, not photographed, not assessed. The study was about hormones.
DHT stayed within the normal reference range the whole time. The ratio shifted; the values did not become abnormal.
Testosterone itself did not change significantly. The ratio moved largely because DHT rose.
n = 20, for three weeks. Male-pattern baldness develops over years. ## It Has Never Been Replicated

This is the part that should settle it. Creatine is among the most heavily researched supplements ever sold, with hundreds of trials and decades of safety follow-up. In all of that, the 2009 DHT result stands alone — no successful replication in more than fifteen years.

A review of common creatine questions and misconceptions examined the claim directly and concluded the evidence does not support a link between creatine supplementation and hair loss (Antonio and colleagues, 2021, Journal of the International Society of Sports Nutrition, PMID 33557850). The ISSN’s position stand on creatine safety and efficacy reviewed the literature and did not identify hair loss as an established adverse effect (Kreider and colleagues, 2017, PMID 28615996).

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The Step the Myth Skips

DHT really is central to male-pattern hair loss, which is why this myth is sticky — it sounds mechanistically sensible. But the mechanism runs through inherited follicle sensitivity to DHT, not through circulating DHT alone. Men with the genetic predisposition lose hair at perfectly ordinary DHT levels. Men without it keep their hair at high ones.

So even granting the 2009 result exactly as published, the chain has a missing link:

Step in the claimEvidence statusCreatine raised the DHT:T ratio in 20 rugby players over 3 weeksObserved once, 2009 — never replicatedThose DHT levels were abnormal*No* — stayed within the normal rangeA within-range DHT shift miniaturises hair follicles*Not demonstratedCreatine users lose more hair than non-usersNever measured in any study*
Two of those four steps have no supporting evidence at all, and one is contradicted by the source study itself.

What Creatine’s Real Side Effects Are

Water retention — real, and misunderstood. Creatine pulls water into muscle cells, typically showing up as one to three pounds on the scale in the first week. It is intracellular, not the puffy subcutaneous bloat people imagine.
GI discomfort — occasional, mostly avoidable. Usually tied to large single doses. Skipping the loading phase and taking 3–5 g daily largely prevents it — see loading vs maintenance.
Kidney damage — not supported. Creatine raises serum creatinine, which is a marker used to estimate kidney function, without impairing the kidney. The same misreading pattern as the hair-loss claim. Compare with the protein-and-kidneys myth, which has an almost identical structure. For the efficacy side and the safety literature in more depth, see does creatine actually work (and is it safe), and on form and timing, creatine HCl vs monohydrate and whether creatine timing matters.

If You Are Actually Losing Hair

Worth separating the question from the supplement. Male-pattern baldness is common, progressive, and genuinely treatable — and the treatments work considerably better the earlier they are started. If you are seeing real thinning, a dermatologist is the productive move. Dropping creatine on the strength of one unreplicated hormone study is unlikely to change the outcome, and it costs you a supplement with unusually strong evidence behind it.

Sources and Methodology

The DHT finding: van der Merwe J, Brooks NE, Myburgh KH, “Three weeks of creatine monohydrate supplementation affects dihydrotestosterone to testosterone ratio in college-aged rugby players,” Clinical Journal of Sport Medicine 2009 (PMID 19741313). Misconception review: Antonio J et al., JISSN 2021 (PMID 33557850). Safety position stand: Kreider RB et al., JISSN 2017 (PMID 28615996). Creatine in women: Smith-Ryan AE et al., Nutrients 2021 (PMID 33800439). General information for healthy adults, not medical advice; if you are losing hair or managing a health condition, speak to a clinician. Last updated July 28, 2026.

Frequently Asked Questions

There is no direct evidence that it does. No study has ever measured hair loss as an outcome and found creatine caused it. The entire concern traces to a single 2009 trial of 20 college rugby players which reported a rise in the DHT-to-testosterone ratio after three weeks of supplementation (van der Merwe 2009, PMID 19741313) — it did not measure hair at all. That result has not been replicated in the years since, and a review of common creatine misconceptions concluded the evidence does not support a link between creatine and hair loss (Antonio 2021, PMID 33557850). If you are genetically predisposed to male-pattern baldness you may lose hair whether or not you take creatine; the evidence does not say creatine is what caused it.It enrolled 20 college-aged rugby players in a three-week crossover and measured hormones, not hair. After seven days of loading at 25 g/day, the DHT-to-testosterone ratio rose about 36% and remained roughly 22% above baseline through two weeks of 5 g/day maintenance. Importantly, the DHT values stayed within the normal clinical reference range throughout, testosterone itself did not change significantly, and no hair-related outcome was recorded. It is a small, single, short study of a hormonal marker — a reasonable prompt for further research, which is exactly what it has not received.No. That is the crux of the matter. The 2009 trial has stood alone for over fifteen years without a successful replication, despite creatine being among the most heavily studied supplements in existence, with hundreds of trials and decades of safety data. In science, a single unreplicated result in 20 people is a hypothesis, not a conclusion. The International Society of Sports Nutrition's position stand on creatine safety reviewed the body of evidence and did not identify hair loss as an established adverse effect (Kreider 2017, PMID 28615996).DHT is genuinely central to male-pattern hair loss, which is why the myth is plausible enough to persist. But the mechanism depends on inherited sensitivity of the hair follicle to DHT, not simply on how much DHT is circulating. People with the genetic predisposition lose hair at ordinary DHT levels; people without it keep their hair at high ones. So even taking the 2009 ratio change at face value — a change that stayed inside the normal range — it does not follow that hair loss results. The causal step everyone assumes, from a within-range hormone shift to actual follicle miniaturisation, is the step no study has demonstrated.That is a personal call, and worth making with the actual odds in view. Creatine monohydrate has the strongest efficacy and safety evidence of any sports supplement, with well-documented benefits for strength, muscle mass, and increasingly for cognition and healthy ageing. Against that sits one unreplicated hormonal marker study that never measured hair. If you are noticing genuine thinning, the far more productive step is to see a dermatologist — male-pattern baldness is treatable and the treatments work better the earlier they start. Stopping creatine is unlikely to be the intervention that helps.There is no evidence for it, and even less mechanistic reason to expect it. The DHT hypothesis is built on male-pattern androgenic alopecia; female-pattern hair loss has a different and less androgen-driven pathophysiology. A review of creatine in women's health across the lifespan found the supplement generally safe and potentially beneficial, particularly around menopause, without flagging hair loss as a concern (Smith-Ryan 2021, PMID 33800439). Women are also frequently under-dosed relative to the evidence — the standard 3 to 5 g/day applies regardless of sex.The genuinely documented ones are mild and mostly manageable. Some short-term water retention is normal and expected — creatine draws water into muscle cells, which typically shows up as one to three pounds of scale weight in the first week and is intracellular, not the subcutaneous bloating people picture. Gastrointestinal discomfort can occur, usually at high single doses, and is largely avoidable by skipping the loading phase and taking 3 to 5 g daily instead. The kidney-damage claim, like the hair-loss one, does not survive contact with the evidence: creatine raises serum creatinine, a marker used to estimate kidney function, without impairing the kidney itself.

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How to Measure Whether AI Assistants Cite Your Site

Yonatan Naor — Mon, 27 Jul 2026 05:17:31 +0000

Originally published at https://thicket.sh/blog/how-to-measure-ai-citations.

← Back to Journal
Methodology

No tool reports this end to end. Three separate measurements exist, each counting something different, and the gap between them is where most of the confusion lives. Here is what each one actually measures, what it misses, and the numbers from our own 21-site portfolio.

By Thicket AI Team · July 27, 2026 · 9 min read

There is no analytics product that tells you how often an AI assistant used your page to answer someone. What exists is three partial measurements: Bing Webmaster's AI Performance report, which is the only first-party citation count any major platform publishes; an analytics referrer segment, which counts the minority of citations that produce a click; and server logs, which show crawlers fetching pages and tell you nothing about whether the content was used. Used together they bracket the truth. Used alone, each one is misleading in a specific and predictable direction.

We publish this because we had to work it out ourselves, and because the gap between the measurements turned out to be the most important number in our own operation. Over an identical 28-day window our sites received 67 clicks from Google and were cited 14,394 times by Microsoft Copilot and partner models. Those two numbers describe the same 21 websites in the same month. If we had been watching only one dashboard, we would have concluded something completely wrong about what we had built.

Measurement 1: Bing Webmaster AI Performance (citations)

This is the closest thing to a direct citation count that exists. In Bing Webmaster Tools, a verified site gets an AI Performance report covering citations by Microsoft Copilot and its partner models. It gives you a daily time series, a total, and two tables that matter: the grounding queries that pulled your content into an answer, and your pages ranked by citation count.

Three practical notes from using it weekly:

Verify the root domain, not each subdomain. The report aggregates across subdomains, so one read covers an entire portfolio. Ours returns 179 distinct cited pages across 21 subdomains in a single view.
There is no API. A sweep of candidate Bing Webmaster API endpoint names in May 2026 returned 404 for every one. The report is interface-only, which means a human or a browser-driving agent has to read it. Budget for that; it is the reason most teams never look.
The grounding-query table is the actionable half. Citation totals are a scoreboard. The queries tell you which questions your content is being pulled into, and the citation-share column tells you how much of that answer you own. That is a content brief, not a vanity metric. What it misses: everything outside Microsoft's ecosystem. It says nothing about ChatGPT, Claude, Gemini or Perplexity. Treating it as total AI visibility is the mistake it invites.

Measurement 2: Analytics referrers (click-through)

Every major assistant passes a referrer when a user clicks a link in an answer. Segmenting analytics by those hosts gives you assistant-referred sessions. The practical host list:

chatgpt.com · chat.openai.com · perplexity.ai · claude.ai · gemini.google.com · copilot.microsoft.com · you.com · phind.com

Two caveats decide whether your number means anything. First, some assistant traffic arrives with no referrer and lands in Direct, so this is a floor, not a total. Second, GA4's built-in “AI Assistant” channel group and your own referrer segment will not match — ours disagree by a few percent because they use different host lists. Neither is wrong. But if you switch between them mid-quarter, your trend line is measuring your methodology. Pick one, write it down, keep it.

What it misses: the large majority of citations. A citation that answers the question in the chat produces no click and leaves no trace here at all.

Measurement 3: Server logs (crawling, not citing)

Your logs show assistant crawlers fetching pages. This is genuinely useful for one question — can they even reach my content? — and useless for the question people actually ask it. A fetch is not a citation. A page can be crawled daily and never used in a single answer.

Use logs to verify access and nothing more: that your robots rules permit the crawlers you want, that important pages return 200 to them, and that JavaScript-dependent content is not invisible in the raw HTML.

The Three Together

MeasurementCountsBlind toOur 28-day figureBing AI PerformanceCitations by Copilot + partner modelsEverything non-Microsoft14,394 citations, 179 pagesAnalytics referrersSessions from assistant linksCitations that produce no click126 sessionsServer logsCrawler fetchesWhether content was used at allAccess verification only*For contrast:* Search ConsoleGoogle clicks and impressionsAll assistant surfaces67 clicks / 38,115 impressions
The ratio between rows one and two is the finding. Roughly a hundred citations for every assistant-referred session means the overwhelming majority of AI visibility never touches your analytics. Any organisation judging its AI presence by session counts is reading the smallest of the available numbers.

Two Things We Did Not Expect

Citations look like a stock, not a flow. Our most-cited property has published nothing since early July 2026 — it is on maintenance only — and it remains the largest single source of citations in the portfolio, holding 4,827 of our top-25 citation count. Rankings decay when you stop publishing. Citations, so far, have not. We are re-measuring at 60 and 90 days before believing it, but if it holds it changes what a content budget is buying.

The pages that get cited are not the pages built to rank. Our most-cited content answers a question a person actually asks out loud, puts a direct answer in the first line, and cites a primary source next to each claim. Pages engineered for search rankings do markedly worse on this surface. Evidence-shaped, not SEO-shaped.

A Minimum Viable Setup

Verify your root domain in Bing Webmaster Tools and read the AI Performance report weekly at the 3-month window. Save the totals, the per-page table and the grounding-query table to a dated file — the interface shows you the present, and you will want the trend.
Build one assistant-referrer segment in your analytics with the host list above. Write the definition down. Do not change it.
Check your logs once for crawler access, then stop looking at them for this purpose.
Report the citation count and the session count side by side, over identical windows. Separately they mislead; together they are the actual picture. ## Frequently Asked Questions

Can you track when ChatGPT or Copilot cites your website?

Partially, and only through three separate measurements that no single tool combines. Bing Webmaster Tools has an AI Performance report that counts citations of your pages by Microsoft Copilot and its partner models, including a per-page and per-query breakdown — it is the only first-party citation count any major platform publishes. GA4 (or any analytics tool) can be segmented by referrer to count sessions arriving from assistant domains such as chatgpt.com and perplexity.ai, which measures click-through rather than citation. Server logs show the AI crawlers fetching your pages, which measures neither. Citations without a click are invisible to analytics entirely, which is why the Bing report matters out of proportion to Bing's search share.

Why don't AI citations show up in Google Analytics?

Because a citation is not a visit. When an assistant reads your page and summarises it in an answer, the user often never clicks — they got what they needed in the chat. Nothing reaches your analytics. GA4 only records the minority of cases where someone follows the link. In our own portfolio the gap between the two is roughly two orders of magnitude: 14,394 citations recorded by Microsoft against 126 assistant-referred sessions in GA4 over the same window. Judging AI visibility by analytics sessions alone therefore undercounts it dramatically.

Where is the AI Performance report in Bing Webmaster Tools?

Under the AI Performance section for a verified site, with 7-day, 30-day, 3-month and 6-month windows. It reports total citations, average cited pages per day, a daily time series, and two tables: one listing the grounding queries that pulled your content into an answer, and one listing your pages by citation count. There is no API for it — an endpoint sweep in May 2026 found no citation endpoint on the Bing Webmaster API — so it must be read from the interface. If you verify your root domain, the report aggregates across all subdomains, which makes one read cover an entire portfolio.

Which analytics referrers indicate AI-assistant traffic?

The practical list is chatgpt.com, chat.openai.com, perplexity.ai, claude.ai, gemini.google.com, copilot.microsoft.com, you.com and phind.com. Two caveats matter. Some assistant traffic arrives without a referrer at all and lands in Direct, so this is a floor rather than a total. And GA4's own 'AI Assistant' default channel group and a hand-built referrer segment will not agree exactly — ours differ by a few percent — because they use different host lists. Pick one definition, write it down, and keep it stable, or your trend line will measure your methodology instead of your traffic.

Do AI citations decay the way rankings do?

Our data suggests less than expected, though the observation is young. Our most-cited property has published nothing new since early July 2026 and remains the largest single source of citations in the portfolio, holding 4,827 of the top-25 citation count. That looks more like a stock than a flow — a ranking decays when you stop publishing, while a citation appears to keep being earned by the page that already answers the question. We are treating this as provisional and re-measuring at 60 and 90 days rather than building a strategy on one reading.

Method and Caveats

Figures come from our own 21-site portfolio over the 28 days ending 24 July 2026: Bing Webmaster AI Performance (citations), GA4 referrer segmentation (sessions) and Google Search Console (clicks and impressions). Bing states that its AI Performance data is a sample of overall activity and may be refined as more data is processed, so treat the totals as indicative of magnitude and trend rather than exact. The citation-durability observation rests on a few weeks of data on one property and is the least reliable claim here — we flag it as provisional deliberately. Our full operating numbers, including the experiments that failed, are published in the Thicket Report.

More from the Journal

How Is an ETF Expense Ratio Charged? (Daily, Not Billed)

Yonatan Naor — Mon, 27 Jul 2026 05:17:27 +0000

Originally published at https://etf.thicket.sh/blog/how-is-an-etf-expense-ratio-charged.

An ETF expense ratio is never billed to you and never shows up as a line item. The fund deducts it from its own assets a little at a time — roughly 1/365th of the annual rate every day — before it calculates the net asset value that sets the share price. So the price you see has already had that day’s fee removed. It is charged on your entire balance, not on your gains, so a fund that loses money still collects it. You pay it continuously for exactly as long as you hold, and you stop paying it the day you sell.

This is the single most-searched confusion about fund costs, and the reason is structural: every other fee in a person’s financial life arrives as a charge they can point at. This one is invisible by design. Below is exactly where the money goes, why the ratio can differ between two apps showing the same fund, and what the number leaves out.

The Deduction Happens Inside NAV

An ETF calculates its net asset value once each trading day: total value of holdings, minus liabilities, divided by shares outstanding. The fund’s accrued expenses are part of those liabilities. Each day the fund books approximately one day’s worth of its annual expense ratio as an expense, and that accrual reduces NAV before the figure is published.

The consequence worth internalising: you never transact for the fee.No cash leaves your account, no share count changes. Your position is simply worth marginally less than an identical, costless portfolio would be. Over a day it is unmeasurable. Over thirty years it is the difference the whole low-cost index argument rests on — see our breakdown of fee drag by expense ratio for what that compounds to.

Daily, Not Annual — and Pro-Rata

The ratio is quoted annually and charged daily. A 0.03% fund takes about 0.0000822% of assets per day, not 0.03% on some anniversary. Two practical implications follow:

Holding for a month costs about a twelfth of the annual rate.You do not owe a full year’s fee for a short holding period.
There is no date to sell before. Unlike a mutual fund distribution or an annual account fee, there is no billing event to dodge. The cost is smooth. ## Charged on Balance, Not on Profit

The fee is a percentage of assets under management. It applies to your whole position regardless of performance:

Balance0.03% ratio0.20% ratio0.75% ratio$10,000$3/yr$20/yr$75/yr$50,000$15/yr$100/yr$375/yr$100,000$30/yr$200/yr$750/yr$500,000$150/yr$1,000/yr$3,750/yr
Approximate annual cost at a constant balance; in practice the fee accrues against the balance as it moves.

A down year does not pause it. That asymmetry — fees on the full balance, returns uncertain — is why cost is the one variable in investing you control outright.

Gross vs Net: the Waiver That Expires

The gross expense ratio is what running the fund actually costs. The net ratio is what you pay after any fee waiver or expense reimbursement the sponsor has agreed to. New or small funds frequently launch with a waiver to post a competitive headline number.

The trap is that waivers are contractual for a stated term and can lapse. When one expires, your cost steps up to the gross figure with no action on your part and no notification you are likely to notice. The expiry date is in the prospectus. If a fund’s gross and net numbers differ meaningfully, that gap is a scheduled future price increase.

What the Expense Ratio Does Not Include

The fund’s own trading costs. Commissions and spreads the fund pays when it rebalances come out of fund assets but sit outside the ratio. High-turnover strategies carry more of this hidden cost than their ratio suggests.
Your bid-ask spread. On a mega-cap index ETF, a penny. On a thin or exotic fund, a single round trip can cost more than a year of expense ratio.
Premium or discount to NAV. An ETF trades at a market price that can drift from the value of its holdings, most visibly in volatile markets or in funds holding assets that trade in other time zones.
Brokerage and platform fees, where your broker charges them. For a broad, liquid fund held long term, the expense ratio really is the dominant cost. For a narrow one traded often, it can be the smallest of the four.

What Counts as a Good Ratio

Fund typeTypical rangeReadBroad index (total market, S&P 500)0.02% – 0.09%Competitive; the floor is near zeroSector / factor0.10% – 0.50%Reasonable if the exposure is genuinely distinctActive / thematic / covered-call income0.35% – 0.95%Needs a specific thesis to justifyAnything above 1.00%> 1.00%Mutual-fund-era pricing; look for a cheaper equivalent
The comparison matters more than the absolute number. Two funds tracking nearly the same index at very different prices is the clearest case — see QQQ vs QQQM, where the cheaper share class holds the same portfolio, and VOO vs SPY vs IVV, three funds on the same index at different costs. For the broader structural comparison, see ETF vs index fund and ETF vs mutual funds.

Sources

Fee definitions, the requirement that costs be disclosed in the prospectus, and the long-run effect of expenses on returns: U.S. Securities and Exchange Commission, Mutual Funds and ETFs and Investor.gov on fund fees and expenses. Net asset value and how funds calculate it: Investor.gov, Net Asset Value. Daily-accrual figures use the annual ratio divided by 365. Typical ranges reflect fees observed across large US-listed ETFs and change over time.

Caveats

This describes US-regulated ETFs and is general information, not investment advice. A specific fund’s current gross and net expense ratios, any waiver and its expiry, and its turnover are stated in that fund’s prospectus on the issuer’s own site — which is the authoritative source when a data provider or app disagrees.

Frequently Asked Questions

How is an ETF expense ratio actually charged?It is never billed to you and never appears as a line item. The fund accrues its expenses daily out of its own assets: each day roughly 1/365th of the annual expense ratio is deducted before the fund strikes its net asset value (NAV). So the price you see already has that day's fee taken out. You pay it by owning the fund and watching a slightly lower NAV than you would have had otherwise. This is why investors search their brokerage statements for the charge and never find it — there is nothing to find, because the deduction happens inside the fund before the number ever reaches you.Is an expense ratio charged daily, monthly, or annually?The ratio is quoted as an annual percentage, but it is accrued daily. A fund with a 0.03% expense ratio does not take 0.03% once a year; it takes about 0.0000822% of assets each day, every day the market is open, as part of calculating that day's NAV. The practical effect is that the fee is charged continuously and pro-rata for exactly as long as you hold. If you own a fund for one month, you pay roughly one twelfth of the annual rate — you do not owe a full year's fee, and you do not escape it by selling before a year-end date.Is the expense ratio charged on your profit or on your total balance?On your total balance, not your profit. The fee is a percentage of assets under management, so it applies to the entire value of your position whether the fund is up, down, or flat. A 0.20% expense ratio on a $50,000 holding costs about $100 a year regardless of performance. This is the detail that surprises people most: a losing fund still charges its fee, and it charges it on the full remaining balance. Performance-based fees that only apply to gains exist in some hedge-fund structures, but not in a standard ETF expense ratio.What is a good expense ratio for an ETF?For a broad, plain-vanilla index ETF, anything at or under about 0.10% is competitive, and the largest total-market and S&P 500 funds now sit between 0.02% and 0.09%. Sector and factor funds typically run 0.10% to 0.50%. Actively managed, thematic, and covered-call income funds are commonly 0.35% to 0.95%. Above roughly 1.00% you are paying mutual-fund-era pricing and should have a specific reason. The useful test is not the absolute number but the comparison: if a nearly identical index is available at a fraction of the cost, the difference is pure drag with nothing bought for it.What is the difference between gross and net expense ratio?The gross expense ratio is what the fund's operating costs actually amount to. The net expense ratio is what shareholders actually pay after any fee waiver or expense reimbursement the sponsor has agreed to. Newer or smaller funds often launch with a waiver to look competitive, so the net figure is lower than the gross. What matters is that waivers are usually contractual for a stated period and can expire — at which point your cost rises to the gross figure without you doing anything. Check the expiry date in the prospectus, not just the headline number.Does the expense ratio include trading costs and commissions?No, and this is a real gap. The expense ratio covers the fund's management fee and operating costs — administration, custody, legal, accounting. It excludes the brokerage commissions and bid-ask spreads the fund incurs when it trades its holdings, which are paid out of fund assets but reported separately. It also excludes what it costs you to trade: the bid-ask spread on the ETF itself, and any premium or discount to NAV. For a heavily traded fund those are trivial; for a thin, exotic one the spread can exceed a year of expense ratio on a single round trip.Why does the same ETF show a different expense ratio on different apps?Usually because one source is showing the gross ratio and another the net (post-waiver) ratio, or because one has not refreshed after a fee change — issuers cut fees fairly often and third-party data lags. Some apps also blend in other costs or display a total cost of ownership figure. The authoritative number is the one in the fund's own prospectus and summary prospectus on the issuer's website, which is the document the SEC requires. When two sources disagree, the prospectus wins.expense ratioETF feesNAVdaily accrualgross vs netfee waiverfee dragSEC← More fund analysis

Why Is My Paycheck Lower Than Expected? (Every Common Cause)

Yonatan Naor — Sun, 26 Jul 2026 06:16:12 +0000

Originally published at https://pay.thicket.sh/blog/why-is-my-paycheck-lower-than-expected.

By Jamie Reeves, Personal Finance Writer

A smaller-than-expected paycheck almost always traces to one changed line, not to the whole check being wrong. The usual causes: a benefits or retirement deduction changed (open-enrollment premiums reset, or a 401(k) auto-escalation stepped up your rate); the calendar year rolled over, which resets the Social Security wage base and the federal withholding tables; you crossed a mid-year threshold such as the 0.9% Additional Medicare Tax above $200,000; your W-4 changed; a bonus or commission in the same period was withheld under supplemental-wage rules; or your hours, overtime, or shift differential simply differed. Put this stub next to the previous one and compare the same lines in order — the gap is nearly always a single line with a knowable cause.

The frustrating part of a short paycheck is not the money, it is not knowing which of a dozen moving parts moved. Below is the full list, roughly ordered by how often each is the culprit, followed by a diagnostic table and the one case that is a genuine payroll error worth raising.

1. A Deduction Changed (Most Common)

Deductions change more often than taxes do, and usually without an announcement you registered at the time.

Benefits open enrollment. Medical, dental, and vision premiums typically reset at the plan year and typically go up. Because most are pre-tax through a Section 125 plan, a premium increase lowers take-home by less than its face amount — but it still lowers it. See which deductions are pre-tax.
401(k) auto-escalation. Many plans automatically raise your contribution rate by a percentage point on a set date each year unless you opt out. Nothing arrives in the mail; the rate on your stub just goes up.
A new HSA or FSA election. Annual elections are divided across the year’s paychecks, so a higher election means a bigger per-check deduction. See HSA vs FSA.
A dependent added to coverage. Moving from employee-only to employee-plus-family is often the single largest deduction change a person ever sees.
A garnishment order started. Court-ordered, taken from after-tax pay, and subject to federal limits on how much can be taken. See how much of your paycheck can be garnished. ## 2. The January Reset

If the drop happened in the first paycheck of a new year, it is almost certainly this, and several effects stack at once. The Social Security wage base restarts, so anyone who had earned past it the prior year — $184,500 for 2026 — and stopped paying the 6.2% is paying it again from the first dollar. New IRS withholding tables take effect (IRS Publication 15-T). Benefit elections and 401(k) escalations start. January is the most predictable paycheck drop of the year and it is not an error.

3. You Crossed a Mid-Year Tax Threshold

Two thresholds change withholding partway through a year, in opposite directions.

Additional Medicare Tax (paycheck goes down). Employers must withhold an extra 0.9% on wages above $200,000 in a calendar year, regardless of filing status, starting in the pay period you cross it (IRS Topic 751). Nothing about your salary changed; the rate on the wages above the line did.
Social Security wage base (paycheck goes up). Once year-to-date wages pass $184,500 in 2026, the 6.2% Social Security tax stops for the rest of the year and take-home jumps. This is why some high earners see a raise in October that reverses in January. ## 4. Your W-4 Changed

A new W-4 — yours, or one filed during onboarding or a life-event update — changes withholding immediately. The usual culprits are checking the multiple-jobs box, removing a dependent, or entering extra withholding on line 4c. Each is intentional in the moment and easy to forget by the next paycheck. See when to update your W-4.

5. A Bonus or Other Supplemental Pay Was in the Same Period

Bonuses, commissions, and retroactive raises are supplemental wages and are withheld under their own rules — commonly a flat 22% federal rate, or blended with your regular wages under the aggregate method, which temporarily raises the withholding rate on the entire check. The result often looks like over-withholding, and frequently is; it settles at filing. See how supplemental wages are taxed.

6. Your Hours or Pay Periods Differed

The dull explanation is often the right one: fewer hours, less overtime, no shift differential, or unpaid time off. And on a biweekly schedule some years contain 27 paychecks rather than 26, with fixed deductions spread across only some of them — so the extra check carries a different deduction load. See the 27-paycheck year and how many paychecks are in a year.

Diagnostic Table

What you noticeMost likely causeWhere to look on the stubDrop in the first check of the yearJanuary reset (wage base, tables, benefits, 401k escalation)Social Security line + benefit linesGross is the same, net is lowerA deduction or withholding changeCompare each deduction line to last stubGross is lower tooHours, overtime, shift differential, unpaid timeEarnings section, hours columnSudden drop mid-year, high earner0.9% Additional Medicare Tax above $200,000Medicare line (two entries may appear)Sudden rise mid-year, high earnerPassed the Social Security wage baseSocial Security line stops accruingOnly the check with a bonus looks offSupplemental wage withholdingFederal income tax line on that checkA line you don’t recognize appearedNew election, escalation, or garnishmentPost-tax deduction sectionRetirement line grew without you acting401(k) auto-escalationContribution rate, not just amount

The One Case That Is a Real Error

Most differences are explainable and correct. The classic genuine mistake is Social Security tax still being withheld after your year-to-date wages passed the wage base — which happens most often after a mid-year job change, because each employer tracks the cap separately and neither knows about the other. If you had two employers in one year, you may have overpaid Social Security across both; that excess is recoverable when you file, but it is worth knowing rather than discovering by accident. Check the year-to-date Social Security figure against 6.2% of the wage base and see whether it stopped where it should have. For the full anatomy of the stub, see how to read a pay stub and FICA vs federal income tax.

Sources and Methodology

Federal withholding methods and tables: IRS Publication 15-T. Social Security and Medicare (FICA) rules, including the Additional Medicare Tax: IRS Topic 751. Employer tax guide and supplemental wage rules: IRS Publication 15 (Circular E). Cafeteria plans and pre-tax fringe benefits: IRS Publication 15-B. Limits on wage garnishment: U.S. Department of Labor, Title III of the Consumer Credit Protection Act. Figures use the 2026 Social Security wage base of $184,500 and the $200,000 Additional Medicare Tax threshold. General information, not tax advice; your plan documents and payroll records govern. Last updated July 26, 2026.

Frequently Asked Questions

The most common causes, in rough order of frequency: a benefits or retirement deduction changed (open enrollment premiums reset, or a 401(k) auto-escalation stepped up your contribution rate); the calendar year rolled over and reset withholding, including the Social Security wage base, so a high earner who had stopped paying it in December is paying it again in January; you crossed a mid-year tax threshold such as the 0.9% Additional Medicare Tax above $200,000; your W-4 changed or was re-filed; a bonus or other supplemental wage in the same period pushed withholding up; or your hours, shift differential, or overtime simply differed from the previous period. Compare this stub line-by-line against the last one — the difference is almost always a single line, not the whole check.January is when nearly everything resets at once. The Social Security wage base restarts, so anyone who earned above it the prior year and had stopped paying the 6.2% is paying it again from the first dollar. New IRS withholding tables take effect. Open-enrollment benefit elections start, and premiums usually rise. Many 401(k) plans apply auto-escalation on January 1, raising your contribution rate by a percentage point without you doing anything. Any one of those lowers take-home pay; in January they frequently stack. This is the single most predictable paycheck drop of the year, and it is not an error.Something moved your taxable wages, your withholding rate, or your deductions. Taxable wages rise if you got a raise, worked overtime, or received a bonus — and supplemental wages like bonuses are withheld under their own rules, which often look like over-withholding on that check. Your withholding rate changes if you filed a new W-4 (a second job, a dependent change, or extra withholding on line 4c). Deductions change at open enrollment, at a 401(k) escalation, when you add a dependent to health coverage, or when a garnishment order starts. Check the year-to-date column: the line whose YTD is growing faster than it used to is your answer.Salaried pay is steady in gross but not always in net. If you are paid biweekly you get 26 paychecks in most years and 27 in some, and many employers spread fixed monthly deductions like insurance over only 24 or 26 of them — so the extra check in a three-paycheck month has different deductions than the others. Percentage-based deductions such as a 401(k) also move with any variable pay. And progressive withholding tables mean a period containing a bonus, commission, or retroactive raise is withheld at a higher effective rate than a plain period.Usually because you hit an annual cap. Once your year-to-date wages pass the Social Security wage base — $184,500 for 2026 — the 6.2% Social Security tax stops for the rest of the year, and take-home jumps noticeably on the next check. The same happens when you finish funding an FSA or hit your 401(k) elective deferral limit and contributions stop. It is the mirror image of the January drop: nothing changed about your salary, only which annual limits you have already cleared.Put the current stub beside the previous one and compare the same lines in order: gross pay, then each pre-tax deduction, then each tax, then each post-tax deduction. Exactly one or two lines will normally account for the entire difference, and each has a knowable cause. Then check the year-to-date column against the annual caps — the classic real error is Social Security withheld past the wage base, which is genuinely a payroll mistake worth raising. If gross pay itself is wrong, that is an hours or rate issue for your manager, not a tax question. If you cannot account for the gap after that comparison, ask payroll to walk you through the specific line.Some changes are automatic and legitimate: a 401(k) plan's auto-escalation feature, a benefits premium increase that took effect at the plan year, or a court-ordered wage garnishment, which the employer is legally required to honor and which arrives via a court or agency order rather than your consent. What an employer generally cannot do is deduct amounts you never authorized and that no law requires. If a new line appears on your stub that you did not elect and cannot identify, ask payroll for the authorizing document — for a garnishment there will be a specific order, and federal limits on how much can be taken apply.

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