An independent reference on approximation, Fermi estimates, and the more–less–go frame for everyday choices.
Most decisions in life are made on approximate numbers, whether people admit it or not. MoreLessGo is an independent reference about the craft of being roughly right: how to estimate quantities you cannot measure, how to know when 'close enough' really is enough, and how a simple three-word frame — more, less, go — can cut through deliberation. Nothing here is sold, tracked, or optimized for conversion; it is a reading resource, nothing more.
The phrase 'more or less' is one of the most common qualifiers in English, and it does quiet but important work: it marks a number as a working figure rather than a measurement. When someone says a trip takes more or less an hour, they are communicating both an estimate and an honest tolerance around it. That tolerance is not sloppiness — it is information. A figure stated with its uncertainty is often more useful than a precise figure stated with false confidence.
Estimation is a trainable skill with a small set of core habits: thinking in orders of magnitude, anchoring to quantities you already know, and checking a result against a second, independent path. People who estimate well are not better guessers; they are better decomposers. They break an intimidating question into pieces small enough that each piece can be guessed within a factor of two or three, and they let the errors partially cancel.
The physicist Enrico Fermi was famous for asking students questions that sounded unanswerable — the classic being 'How many piano tuners are there in Chicago?' The point was never the answer. The point was the method: decompose the unknown into a chain of factors (population, households, pianos per household, tunings per year, jobs per tuner), estimate each factor roughly, and multiply. Individually the factors may each be off by a factor of two, but the errors tend to cancel, and the final product usually lands within an order of magnitude of the truth.
Fermi demonstrated the power of the approach at the Trinity nuclear test in July 1945. As the blast wave passed, he dropped small pieces of paper and watched how far the shock wave carried them, then produced an estimate of the yield on the spot. His rough figure came within about a factor of two of the value later computed from instrument data — a remarkable result for a handful of falling paper and a mental model of explosions.
Read as three imperatives, the name MoreLessGo describes a compact decision frame that applies to almost any recurring demand on time, money, or attention. Faced with an activity that is not working, there are only three honest moves: do more of it (invest seriously, because the bottleneck is effort), do less of it (cut back, because the returns do not justify the cost), or go — commit to the current course and stop re-deciding it every week.
The frame earns its keep by eliminating the fourth option, which is the one most people actually choose: indefinite low-grade deliberation. Re-opening the same decision consumes the same attention as deciding, without producing a decision. Forcing the question into three buckets — more, less, or go — converts a vague dissatisfaction into a concrete resource question with a concrete answer.
In 1956 the economist and psychologist Herbert Simon gave a name to the strategy of accepting the first option that meets your criteria: 'satisficing', a blend of satisfy and suffice. Simon's argument was that perfectly rational optimization is usually impossible — the information costs too much and the time costs more — so real decision-makers set an aspiration level and stop searching once it is met. This is not a failure of rationality; it is rationality priced correctly.
Later research sharpened the point. Work by Barry Schwartz and colleagues, popularized in the 2004 book The Paradox of Choice, distinguished 'maximizers', who try to find the single best option, from 'satisficers', who look for good enough. Maximizers tended to make objectively marginally better choices and to feel subjectively worse about them — more regret, more second-guessing, less satisfaction. The lesson generalizes: beyond a modest search effort, additional optimization buys little outcome and costs real wellbeing.
Approximation has hard boundaries. Drug dosing, structural load calculations, tax filings, and aviation fuel planning are domains where 'more or less' is not an acceptable answer, because the tolerance around the correct value is narrow and the cost of crossing it is high. The skill is not estimating everything; it is knowing which questions admit rough answers and which demand exact ones.
Even in friendly territory, estimates fail in predictable ways. The 1999 loss of NASA's Mars Climate Orbiter is the canonical cautionary tale: one team worked in pound-force seconds, another in newton-seconds, and the mismatch went undetected until the spacecraft burned up in the Martian atmosphere. The numbers were precise; the units were wrong. Most estimation disasters share that shape — not wild guessing, but a quiet structural error underneath confident arithmetic.
The practical payoff of more-or-less thinking shows up in ordinary places. Household budgets work better rounded to the nearest ten or hundred than tracked to the cent, because the purpose of a budget is to steer behavior, not to produce an audit. Travel planning improves when estimates carry buffers — leaving 'more or less an hour' for a forty-minute trip converts a fragile plan into a robust one.
Project planning is the classic workplace case: experienced planners take a careful estimate and multiply it by a factor, because tasks systematically overrun. Fitness and diet changes follow the same logic — an approximate but sustained calorie deficit beats a precisely calculated plan that is abandoned in week three. In each case the pattern is identical: a rough number, honestly held and consistently applied, outperforms a precise number that nobody can maintain.