Maximizing

A simple explanation

Maximising is the strategy of searching for the best available option across the entire field rather than stopping at one that is good enough. Schwartz, building on Simon, named the disposition and traced its costs. The Reward System's default mode is mild maximising — it is, after all, evolved to optimise — and in small option sets the default works fine. In modern abundant environments, the default becomes structurally corrosive: the search never closes, the chosen option arrives undermined by counterfactuals, and the residue accumulates as a steady low-grade dissatisfaction with choices that, on paper, look excellent.

Maximising is not the same as having high standards. Standards calibrate what good-enough means; maximising rejects the concept of good-enough in favour of best. The first integrates; the second, in abundance, does not.

An everyday example

You are buying a backpack for a trip. You read seventeen reviews, watch four YouTube comparisons, and create a small mental scorecard across nine dimensions. You order the one that scores highest. The backpack arrives. It is excellent. Within a week you find a forum thread mentioning a brand you did not consider, and you spend three evenings convinced you bought the wrong backpack. The trip is fine. The backpack works. You carry it for two years. Years later, you cannot remember what it actually felt like to use the backpack without doubting it.

The satisficer next door bought a different backpack in twenty minutes, decided it met their three criteria, and used it for two years without ever opening another forum thread. Both backpacks performed identically. The satisficer's two years included less residue.

Why does this happen?

Because maximising is the Reward System's optimisation reflex applied without bound. In ancestral environments — small option sets, scarce resources — searching the whole field was both feasible and adaptive. In modern environments, the field is unbounded. The search cannot complete, but the System, having not received an off-signal, keeps the search active even after the verdict. Every forum thread that surfaces a new contender re-opens the loop. Every new release of a competing product re-triggers the simulator.

The structural problem is not the wanting-the-best; it is that best is not deliverable when the option set is not closeable. The System, asked for a category it cannot deliver, runs without converging — first during the decision, then after it.

The behavioral loop

How maximising runs:

1. Decision arrives — a real choice. The maximiser's frame: find the best one.
2. Search expansion — the option set is taken as approximately exhaustive. Reviews, comparisons, forums, expert opinions, all are consumed as potentially decisive.
3. Weighing across many dimensions — each candidate is scored across criteria; the criteria themselves often grow as the search proceeds.
4. Choice — a verdict lands, sometimes after considerable delay. The choice is often objectively good.
5. Post-decision counterfactual sweep — the simulator runs on the unchosen options. New information surfaces. Doubt arrives.
6. Re-engagement with the option set — forums are re-checked. The chosen option's flaws are highlighted by comparison.
7. Residue accumulation — the chosen option's deposit is hollowed by the persistent simulation of unchosen alternatives. Satisfaction is structurally diminished.
8. Carry into next decision — the maximiser arrives at the next choice with reinforced expectations that exhaustive search is the responsible move.

Emotional drivers

Three motives interact under chronic maximising:

• A wish to choose responsibly, often rooted in an honest care about decisions mattering.
• A fear of regret — I do not want to discover later that I missed the better option — often the louder of the three.
• A faint identity-load: being the kind of person who chooses well — partly performed for self-image rather than outcome.

What your nervous system does

Sustained maximising produces a recognisable somatic pattern: prolonged sympathetic engagement during deliberation, an incomplete parasympathetic recovery after the verdict, and intermittent re-activation across the weeks that follow as new option information surfaces. The body holds the loop. Sleep often degrades in the post-decision window when the simulator runs the counterfactuals. The maximiser frequently reports a baseline tension that they attribute to being detail-oriented but which the body knows is a chronic unclosed loop.

The DojoWell interpretation

Maximising is a Reward System loop where the substitute is exhaustive-search-as-care. The System's original ask was a satisfying preference. The substitute it accepts is the act of comprehensive search — which it registers as responsible, as careful, as the right way to handle a choice that matters. The substitution is convincing because exhaustive search has the outer shape of competence and conscientiousness. The loop is hard to see because it looks like a virtue.

The deposit, however, is structurally diminished. A real preference integrates when the chosen option closes the option set. Maximising deliberately leaves the option set open — that is the strategy — and the unchosen alternatives remain accessible as ongoing simulations. The chosen option, however excellent, is felt relative to the persistent unchosen field. The deposit hollows out before it lands.

This is false_progress density signature in clean form. The maximiser's days are full of decisions that were objectively well-made; the maximiser's evenings are full of small doubts about decisions that were objectively well-made. The equation makes the math visible: substantial effort, diminished deposit, accumulating residue, low density.

The closure pattern is stalled because the option set never actually closes. The chosen option is provisional in the system even when it is final in reality. The work that resolves it is not better maximising. It is converting most decisions to calibrated satisficing and reserving maximising mode for genuinely high-stakes irreversible choices where the cost of exhaustive search is justified.

How do I become a satisficer if I'm wired as a maximiser?

The work is not to suppress the System's optimisation reflex; it is to redirect what it is asked for.

1. Distinguish high-stakes from everyday. Maximising is appropriate for one or two decisions a year. For everything else, the cost of exhaustive search is greater than the benefit. Name the few decisions where maximising is honest.
2. Practise threshold-setting on small choices. Restaurants, weekly groceries, low-cost purchases. Define good-enough in advance and stop at the first option that meets it. The reflex builds through repetition.
3. Refuse to re-open closed decisions. Once chosen, a decision is closed for a defined window — ninety days, six months. The System's promised payoff from re-evaluation is almost always smaller than the residue of leaving it open.

Practical steps

1. Take an honest inventory. List the categories where you maximise. Backpacks, restaurants, partners, career paths, subscriptions, vacations. The list itself reveals where the strategy is costing you.
2. Convert two categories this month. Pick two from the inventory where you commit to calibrated satisficing for the next six weeks. Define the threshold; honour the threshold; refuse the post-decision sweep.
3. Install information hygiene. Unsubscribe from comparison emails. Mute forums about products you have already chosen. The System's counterfactual access shrinks when the alternatives are no longer cognitively retrievable.
4. Track the residue cost. Notice the sleep-loss, the time-loss, the relational cost of bringing maximising energy into low-stakes domains. The cost is often larger than the cumulative quality benefit.
5. Reserve maximising for the genuine few. A medical decision, a major investment, a once-in-a-decade move. The reserve preserves the System's optimisation reflex for the contexts where it earns its keep.

Reflection questions

• Which categories of choice in your life are you currently maximising in, when calibrated satisficing would integrate more cleanly?
• What does the fear-of-regret motive feel like, separated from the care-about-the-choice motive?
• For the most recent decision you maximised on, what was the actual cost-benefit of the exhaustive search versus a calibrated good-enough threshold?
• Where has the maximising reflex become an identity load — the kind of person who chooses carefully — rather than a strategy?

Frequently Asked Questions