---
title: brainmaxxing or the art of failing better
canonical: https://mll.sh/brainmaxxing-or-the-art-of-failing-better/
published: 2026-08-10
modified: 2026-11-13
tags: [misc]
author: miguel llamazares
---

# brainmaxxing or the art of failing better

Well, I don't usually post about personal stuff, but hey, hoomanity (and me) deserves something different every now and then.

Turns out _I'm honored (and slightly amused) to share_[^1] that I recently joined [Mensa](https://www.mensa.es/). *\*play doom_eternal_theme.mp3* 💀

Here, I wanted to describe my experience and expectations, as well as some related personal background so you can roast me later if you want to.

## mens-what?

Mensa is this organization for people with high IQs. To enter, you need to take an in-person test and score in the top 2% (98th percentile), which is two sigmas away from the mean.

It started in the 40s in the UK and in Spain around the 80s. Since then there have been tons of replications in different countries. Their mission can be summarized as:
1. identify and promote human intelligence for the benefit of humanity.
2. encourage research on the nature, characteristics, and uses of intelligence.
3. provide a stimulating intellectual and social environment for its members.

## my background

Spoiler: I was not the typical gifted kid. At all.

Ever since I was a kid, I've loved making plans about everything. I'd want to repair a bicycle and would spend more time planning, making budgets and drawing sketches than actually doing it. I'm an only child, so I spent a lot of time by myself and could stay focused for hours in my own world[^2].

I was also a terrible student. Not the kind who gets bored because the level is too low or the content isn't challenging, I simply didn't care about school. I never paid attention and failed an obscene number of subjects. Every year I ended up carrying a ton of subjects over to September, and then suddenly passed all of them[^3]. TBH, I'm not proud of that phase of my life. It felt like I was wasting a lot of time and energy. It was also quite frustrating for my parents[^4].

Then my father taught me programming when I was 13. That clicked! I became obsessed[^5] with it, and I spent all day in underground forums taking part in performance contests to see who could implement the fastest algorithm in VB6.

After high school, I decided to first study an HNC in web development, with the plan of starting uni afterwards (perhaps software engineering). However, I got hired at my internship, so I decided to keep working and put the uni plans on hold.

Fast-forward some years, I did start studying at [UNED](https://www.uned.es/universidad/inicio/en/), but for a BSc in philosophy (plot twist!). There I managed to get several honors while working full-time, plus doing some freelance collabs on the side. I was particularly fascinated by the analytical stream: logic, philosophy of science, etc. I was living in the UK at the time. That was an \*intense\* period of my life, but somehow I look back on it with nostalgia.

In order to prioritize my career, I put the degree on hold[^6]. I hadn't taken it up with a career focus, plus having kids and whatnot, for obvious reasons. However, I think it had an indirect positive impact on my career in terms of structured reasoning, writing, creativity, etc.

Then I pivoted from development to cybersec, then to offsec specifically, and [my linkedin](https://www.linkedin.com/in/mllamazares/) tells the rest of the story. Along the way I failed miserably (still do, but with style 😎) at tons of projects, but they somehow contributed to who I am today. For instance, years ago I built an algotrading setup that didn't translate into anything useful, but it was a great excuse to learn statistics and probability, as well as how to design and implement high-frequency, data-intensive systems[^7].

To wrap up, I've never considered myself a particularly gifted individual. More like someone with decent processing power who's willing to spend an unreasonable amount of energy on the stuff he enjoys.

## why i tried

There were two main factors that motivated me to take the Mensa test.

First, my older son. He is currently ~4 years old, and I think he is showing early signs of giftedness: extraordinary memory, a complex sense of humor, musicality, the ability to focus for long periods of time, etc. But well, I’m his father, so I’m probably super-biased. I believe _there are more parents of gifted kids than actual gifted kids_, kek. At least it was enough to make me question it, since there is a decent heritability factor.

Second, I stumbled upon [Javier Recuenco](https://www.linkedin.com/in/javier-g-recuenco-70a708/). He was a Mensa Spain ex-president. I discovered him thanks to [Heavy Mental](https://heavymental.es/) podcast, where he talks about a wide range of topics. I love his communication style because he is not the typical nerd, but actually exposes complex stuff in a very aproachable way (a la Feynman, but with more sideburns)[^8].

## the access test

I took the Mensa online test, then the paid online version called T2, which is supposed to be more accurate. Since I got decent results in both, I decided to give the in-person test a try. They arranged a session at a public library. The very same day, they corrected the test and told me I got accepted! 🎉

Something to highlight is that the exams are _culture fair_. Mensa is not politically, sexually, or culturally biased. The exam aims to capture your raw fluency in identifying patterns across different contexts and forming abstractions that relate ideas. Due to time constraints, you essentially have only a few seconds to connect the dots and mark your answer. I confess it made me sweat. 

## motivations

I joined Mensa for the following reasons:
- **networking**: we are trained with the same dataset. And as soon as you get older, you're somewhat limited in making new connections. Here the premise is quite interesting: you meet people you share something in common with (high IQ), but they can be virtually of any background, profession, etc. I find that very enriching. 
- **conferences and events**: they organize recurring conferences that are quite interesting. [Most of them are uploaded to YT](https://www.youtube.com/user/mensaes). Low-key, I'd been reviewing them for a while before actually joining. 
- **SIGs (Special Interest Groups)**: a fancy term for forums that gather people with shared interests, but for some reason it sounds cooler here. They also organize meetups every now and then.
- **SIGHT (Service for Information, Guidance, and Hospitality to Travellers)**: is a mensa hospitality network that links traveling members with local hosts who offer accommodation or travel recommendations.
- **occasional discounts**: I noticed there are some discounts for members, for instance on board games.
- **bragging rights**: I have a super fragile ego; this is a way of being able to sleep at night, kek. 
- **job opportunities**: also, high IQ often correlates with better job performance. So a potential employer (not currently looking for a change, HR guys) would value that. There is also a specific [job board handled by Mensa Spain](https://mensajobs.mensa.es/es/), btw. This is controversial but I don't care: I think the controversy is born from the misunderstanding that IQ is everything (more on that later).

## iq is \*not\* everything

I'm not a big believer in IQ as the *ultimate indicator* of success, but it's just another variable in the equation.

Having a nice set of tools is the equivalent of IQ for a carpenter. But if he doesn't put in the effort, take risks, make mistakes, and so on, he won't become a good carpenter. On the other hand, someone with only a spoon and grit might still end up creating awesome pieces of woodcraft[^9]. 🪑

The same applies to effort in isolation; it's also not a good KPI. People who tried to build a [perpetual motion](https://en.wikipedia.org/wiki/Perpetual_motion) machine spent a lot of effort, and some of them were pretty smart. It was still a waste of time since it violates the fundamental laws of physics.

So effort and intelligence are _necessary_ but not _sufficient_ conditions for success. Then, we need to focus on the outputs, that is, the objective achievements (what you've done that sets you apart). We don't remember Einstein because he was a smart guy, but because of his specific contributions to science (and for sticking his tongue out in those funny pictures).

When I interview a candidate for a tech role, I put more weight on verifiable stuff you've done (conferences, github repos, bug bounties, certs, blogs, etc.) than on years of experience or standard education. I want proof of work and leading indicators that reflect passion and show you can actually solve problems.

## fluid vs crystalized intelligence

There are two types of intelligence: _fluid_ 💧 and _crystalized_ 💎.

_Fluid_ intelligence is the raw problem-solving horsepower. It shoots up fast, hits its personal best around age 23, and then starts sliding downhill like my will to live after the third meeting of the day.

_Crystallized_ intelligence, on the other hand, is all the stuff you've actually learned and stored. It climbs more slowly, peaks later, around 60–70 years, and then declines at a gentler pace.

Here's a cool chart made by my mate claude to illustrate both concepts over a lifespan:


<script src="https://cdn.jsdelivr.net/npm/chart.js@4.4.1/dist/chart.umd.min.js"></script>
<style>
  .chart-wrap {
    background: transparent;
    max-width: 800px;
    margin: 0 auto;
    padding: 16px;
    font-family: 'Agave', ui-monospace, monospace;
  }
  .chart-box { position: relative; height: 430px; }
  @media (max-width: 600px) { .chart-box { height: 340px; } }
</style>

<div class="chart-wrap">
  <div class="chart-box"><canvas id="intelligenceChart"></canvas></div>
</div>

<script>
/* ---------------------------------------------------------------------------
   FLUID (Gf)  ( one source, unmodified.
   Dual-exponential latent growth model from McArdle, Ferrer-Caja, Hamagami &
   Woodcock (2002), Developmental Psychology 38(1), 115-142, Table 8.
   Woodcock-Johnson-R, N ~ 1,200, ages 2-95.
       W(t) = mu0 + mu1 * [ exp(-Bb*t) - exp(-Ba*t) ]
   Evaluating it reproduces their published peak age of 22.8.

   CRYSTALLIZED (Gc)  ( two sources spliced, because no single study covers both
   ends well. McArdle's Gc is a single test (Oral Vocabulary) and peaks at ~35,
   which is earlier than the adult literature converges on.
     • Childhood rise: McArdle's Gc dual-exponential (fast vocabulary growth).
     • Adulthood: Salthouse's cross-sectional slopes for the vocabulary
       composite  ( +0.02 SD/yr to the peak, -0.011 SD/yr after (Salthouse 2019,
       Psychology and Aging 34(1), Table 2; Salthouse studies, n > 3,000).
       Converted to W units using SD = 18.5, the latent between-person SD at
       the Gc peak from McArdle's Table 9.
     • Peak set at 65. Salthouse (2019) finds vocabulary rising into the 60s;
       Hartshorne & Germine (2015), n = 48,537, put it in the late 60s to early
       70s. (Wechsler normative data suggests the late 40s  ( the low end.)
     • The two segments are joined with a smoothstep blend over ages 15-35 so
       there is no kink where the sources meet.

   Y axis: percent of each ability's own lifetime peak, 0 = the model's value at
   birth. A valid affine transform of the Rasch W scale. Note this means the two
   lines are NOT comparable to each other in absolute terms  ( each is measured
   against its own trajectory.
--------------------------------------------------------------------------- */

(function () {
  const GF = { mu0: -116.5, mu1: 156.3, Bb: 0.0052, Ba: 0.1539 };
  const GC = { mu0: -116.3, mu1: 179.2, Bb: 0.0026, Ba: 0.1104 };

  const W    = (t, p) => p.mu0 + p.mu1 * (Math.exp(-p.Bb * t) - Math.exp(-p.Ba * t));
  const PEAK_GF = Math.log(GF.Ba / GF.Bb) / (GF.Ba - GF.Bb);   // 22.8
  const PEAK_GC = 65;

  const SD_GC = 18.5;                  // W units, McArdle Table 9
  const RISE  = 0.020 * SD_GC;         // Salthouse: +0.02 SD/yr up to the peak
  const FALL  = 0.011 * SD_GC;         // Salthouse: -0.011 SD/yr after
  const HINGE = W(25, GC);             // where the two segments are pinned

  const gcAdult = t => t <= PEAK_GC
    ? HINGE + RISE * (t - 25)
    : HINGE + RISE * (PEAK_GC - 25) - FALL * (t - PEAK_GC);

  function gcRaw(t) {
    const s = Math.min(Math.max((t - 15) / 20, 0), 1);
    const w = s * s * (3 - 2 * s);
    return (1 - w) * W(t, GC) + w * gcAdult(t);
  }

  function normalize(fn, peakAge) {
    const base = fn(0), span = fn(peakAge) - base, out = [];
    for (let t = 0; t <= 90; t += 0.5) out.push({ x: t, y: (fn(t) - base) / span * 100 });
    return out;
  }

  // Flexoki  ( stephango.com/flexoki
  const BLUE   = '#4385BE';  // blue-400
  const ORANGE = '#DA702C';  // orange-400
  const TX     = '#878580';  // base-500
  const GRID   = 'rgba(135, 133, 128, 0.22)';
  const FONT   = "'Agave', ui-monospace, monospace";

  const peakMarkers = {
    id: 'peakMarkers',
    afterDatasetsDraw(chart) {
      const { ctx, chartArea: { top, bottom }, scales: { x } } = chart;
      const marks = [
        { age: PEAK_GF, color: BLUE,   label: 'Gf peak \u00B7 23', align: 'right' },
        { age: PEAK_GC, color: ORANGE, label: 'Gc peak \u00B7 65', align: 'left'  }
      ];
      ctx.save();
      marks.forEach(m => {
        const px = x.getPixelForValue(m.age);
        ctx.beginPath();
        ctx.setLineDash([3, 4]);
        ctx.lineWidth = 1;
        ctx.strokeStyle = m.color;
        ctx.globalAlpha = 0.6;
        ctx.moveTo(px, top);
        ctx.lineTo(px, bottom);
        ctx.stroke();
        ctx.globalAlpha = 1;
        ctx.setLineDash([]);
        ctx.fillStyle = m.color;
        ctx.font = '13px ' + FONT;
        ctx.textAlign = m.align;
        ctx.fillText(m.label, m.align === 'right' ? px - 6 : px + 6, top - 8);
      });
      ctx.restore();
    }
  };

  const line = (label, data, color) => ({
    label, data,
    borderColor: color,
    backgroundColor: color,
    borderWidth: 2.5,
    tension: 0,
    pointRadius: 0,
    pointHoverRadius: 4,
    fill: false
  });

  new Chart(document.getElementById('intelligenceChart'), {
    type: 'line',
    plugins: [peakMarkers],
    data: {
      datasets: [
        line('Fluid (Gf)', normalize(t => W(t, GF), PEAK_GF), BLUE),
        line('Crystallized (Gc)', normalize(gcRaw, PEAK_GC), ORANGE)
      ]
    },
    options: {
      responsive: true,
      maintainAspectRatio: false,
      interaction: { mode: 'index', intersect: false },
      layout: { padding: { top: 26 } },
      plugins: {
        legend: {
          position: 'bottom',
          labels: {
            color: TX,
            usePointStyle: true,
            pointStyle: 'line',
            boxWidth: 28,
            padding: 18,
            font: { family: FONT, size: 13 }
          }
        },
        title: {
          display: true,
          text: 'Fluid vs. crystallized intelligence across the lifespan',
          color: TX,
          font: { family: FONT, size: 16 },
          padding: { bottom: 20 }
        },
        tooltip: {
          titleFont: { family: FONT },
          bodyFont:  { family: FONT },
          callbacks: {
            title: items => 'Age ' + Math.round(items[0].parsed.x),
            label: c => c.dataset.label + ': ' + c.parsed.y.toFixed(1) + '%'
          }
        }
      },
      scales: {
        x: {
          type: 'linear',
          min: 0,
          max: 90,
          title: { display: true, text: 'Age', color: TX, font: { family: FONT, size: 13 } },
          grid: { color: GRID, drawBorder: false },
          ticks: { color: TX, font: { family: FONT, size: 12 }, stepSize: 10 }
        },
        y: {
          min: 0,
          max: 100,
          title: { display: true, text: '% of lifetime peak', color: TX, font: { family: FONT, size: 13 } },
          grid: { color: GRID, drawBorder: false },
          ticks: { color: TX, font: { family: FONT, size: 12 }, stepSize: 25, callback: v => v + '%' }
        }
      }
    }
  });
})();
</script>


### bottom line

In my case, that blue curve peaked a decade ago and there's nothing I can do about it. The orange one keeps climbing for another three decades and that part is almost entirely on me. So the only variable I still control is the boring one: showing up and accumulating stuff. 🧗‍♂️

But something has to turn the blue curve into the orange one, and in my case that mechanism has always been failed projects, and failing is just the build step nobody puts on their linkedin. 

Keep grinding! 💪

[^1]: yep, this deserves the linkedin cringy cliché
[^2]: still do, tbh. However, I never considered myself an introvert. I'm a pretty social person.
[^3]: sacrifycing the summer, ofc
[^4]: and now that I'm a dad, I can empathize with that much better, jeez
[^5]: I can get quite obsessive sometimes
[^6]: which I will resume when I retire or something
[^7]: this was pre-llm without claude code, can you even imagine?
[^8]: he's also an expert in complex systems, a topic that fascinates me and I've talked about earlier [in this very blog](/how-to-not-be-a-llm-kiddie).
[^9]: hey, I think this analogy was pretty visual, huh?