So this is a big deal. Our very own Melissa Proxenos may be crowned CTO of the Year. But can we call ourselves surprised? Not so much. In the last 18 months, Melissa has been awarded: - Lead5050 Awards 2025: Mentor of the Year - CTO Craft 100 2025 - Computing Tech Women Celebration 50 2025 - Women in Tech APAC Awards 2024: Global Leadership - B&T Women Leading Tech Awards 2024: Engineering Plus, she's been a finalist 10 other times and nominated another six. Sometimes, talen

Why Some Things Take 10,000 Hours and Others Take 10 Seconds A Framework for Understanding Task Complexity Across Biological and Artificial Intelligence This paper is a companion to Critical Depth: When More Layers Unlock New Capabilities - which explores how neural network capabilities emerge suddenly at specific architectural depths, paralleling biological development. Here we ask: if certain tasks require minimum processing depth, what determines how long it takes to lear

Never liked geometry? Neither did geometry, particularly. But there's a new shape to get your head around. And it looks like a trident. Those of us who have marched off and started to put AI agents into our everyday workflows are increasingly reporting that we seem to be developing three key skills: 1. Curating the right work. When you can achieve so much, you have to ask: 'What's worth doing?' And the corollary: 'Which thousand ideas need to be given a firm no?' 2. Running t

How the environment changes along the way In our first part of this essay, we considered the difference between Amodei and Hassabis' conceptions of AGI. Now we can return to the question that kicked the entire enquiry off: What does this mean for the environments organisations have to survive in? This feels quite important. The environment is, after all, a set of forces that decides who prospers. It includes customer behaviours, competitive tempo, regulatory regimes, supply

A Thought Paper on Parallels Between Deep Learning and Biological Intelligence The Phenomenon A recent paper from Princeton University won Best Paper at NeurIPS 2025 — one of only four selected from over 20,000 submissions — by demonstrating something striking: when training neural networks for robotic control, performance doesn't improve gradually as you add layers. Instead, nothing much happens until you hit a specific "critical depth" — then capabilities suddenly emerg

Why there’s no real disagreement Our last essay ended with what we believe is a significant realisation: abundant digital intelligence doesn’t just accelerate progress, it changes what kinds of organisations can survive. AI creates selection pressure through new customer demands, competitive responses, internal behaviours and regulatory regimes. Which will mean organisational forms start to look exactly like what they are - animals evolved for a different ecosystem. Because a

How 2026 produces divergent forms Our previous chapter argued that cheap intelligence reveals the organisational phenotype. The visible behaviour. The muscle memory. The habits that usually stay half-hidden behind the sheer effort of getting work done. This final chapter goes one step further. Because once you accept phenotype exists, something else must too - the process of selection. And when selection runs for long enough, divergence follows. In biology, speciation is what

What's it like to work at Brightbeam? Here are the exact contents of an email sent by CEO Brian Hanly earlier this week: Hi All, We had an important conversation in our management call this morning that I want to share with everyone. We're growing fast, and that's exciting. But growth means nothing if we burn out the people making it happen. So I want to be direct about something: no delivery timeline, no customer demand, is more important than your wellbeing. A simple shared

How cheap intelligence reveals cultural truth Our previous chapter framed the problem of AI adoption as a set of choices. Because in choices is where agency lives. And where responsibility can be assigned. And where the potential of AI either converts into real gains, or leaks away. Even so, limits remain. Even when the choices are sensible. Or indeed optimal. And these limits sit in places less accessible to rapid change: inside strategy, inside tooling, inside programme pla

OpenAI just named the 'capability overhang' - the gap between what AI can do and the value people actually capture from it. We have data that shows the textures of that gap. And how it can be closed. Brightbeam surveys professionals before an AI coaching sprint - and again afterwards. The results are revealing, especially if you're trying to understand and close the overhang. For instance, nearly half are using AI daily - even before training. So obviously they're the more ca

How to convert capability into defensible productivity As acknowledged in our previous chapter, the collision between the exponential improvement of AI does not match the ingrained pace of institutional change management. Linear systems do not spontaneously accelerate when they need to keep up. So whether an organisation successfully adopts AI - or not - depends on a series of choices. Choices that are often framed as operational or cultural, but are in fact strategic. Becau

Sometimes a collision of ideas can lead to a glimpse of the future. And that happened at Brightbeam yesterday. Anthropic released Cowork. And Apple adopted Google Gemini. Just as we delved more deeply into Microsoft’s steady threading of Copilot into everything, everywhere. Whilst we already assumed intelligence would be woven into the fabric of almost all work, we realised success will be defined by how well groups of people can think together. Clearly. And coherently. Anthr

Exponential intelligence meets linear systems In late 2025, in many organisations, the same discussion played out in different rooms. The final annual numbers were being forecast. Numbers were being adjusted. Assumptions were being tested. Heads of function were asked - politely, then more directly - whether the gains from AI everyone had been discussing could now be reflected in guidance. Earlier in the year, in the very same rooms, there had been enthusiasm. There had been

Don't ever feel sorry for CEOs. The perks and privileges of the job make them among the most pampered people on the planet. However, the job is not without its frustrations. When change is the order of the day, being a CEO can feel like being the captain of a ship. Whilst being shackled to the deck and wearing a straitjacket underneath a hazmat suit. Yet needing to coax the vessel into performing the tightest of turns. One very specific shackle has been the dependency on othe

No more voting. It’s time to weigh. Earlier this week, in What Will 2026 Be, Really?, we argued that the significance of 2026 will be determined by whether digital intelligence begins to show up as defensible productivity inside real organisations. Or not. The hinge of this thesis is the Productivity Clock - the countdown to the moment when, as economies, markets, organisations and individuals, we decide whether sustained investment in AI is delivering sustained improvements

When we started working with ALONE, we were very focused on helping older people. We were thinking about those who needed connection. About volunteers who needed better tools to match older people with others giving up their free time. And about a charity doing vital work with limited resources. It's very safe to say that the project exceeded all expectations. And so it's an utter delight to see it shortlisted for Impact of the Year at the Digital Business Ireland Awards. The

Never mind the noise, let's find the signal If you’ve been taking heed of the slew of commentary of the last few weeks, you’ll be acutely aware that accelerationists believe it’s going to be the year that: We all become vibe coders and use agents to get our work done; Enterprises face the reckoning of integrating AI meaningfully - or accepting their terminal fate; The economy looks even more ‘K-shaped’ - those already prospering will accelerate far more quickly, whilst thos

WHAT WILL 2026 BE, REALLY? If you’ve been taking heed of the slew of commentary over the last few weeks, you’ll be acutely aware that AI accelerationists believe it’s going to be the year that: - We all become vibe coders and use agents to get our work done; - Enterprises face the reckoning of integrating AI meaningfully - or accepting their terminal fate; - The economy looks even more ‘K-shaped’ - those already prospering will accelerate far more quickly, whilst those strugg

Ever get the feeling that your body is just middleware? It pokes at apps, scrolls through dashboards and translates intent into clicks. Our brains are the actors but - at least at work - they interact with almost all their primary tools through sheets of glass. Mustafa Suleyman, CEO of Microsoft AI, suggests this era is ending. During a Peter Diamandis podcast, he envisions a shift from 'direct computing' to a world in which the interface dissolves. We won't scroll, tap or cl

An Essential Pattern for Intelligence in Enterprise Systems Executive Summary Every successful system - whether powered by human intelligence, traditional code, machine learning, or generative AI - requires a clear specification of what 'correct' looks like. This fundamental truth of systems design has become more critical than ever as organisations deploy increasingly sophisticated forms of intelligence. This whitepaper introduces a practical methodology that transforms abst

Science progresses in bursts. And sometimes, especially given the intensity of the science-news cycle, interesting bursts make very little impact on the hypegeist . So we have started an irregular series to keep you informed with what might otherwise go unnoticed. We're looking for the marriage of science and AI. And this month there were three papers that raised our eyebrows. Especially given their parallels with digital intelligence. This trio of biology preprints that caug

So 'they' were only a couple of days out. GPT-5.2 landed yesterday. And was the feedback heard? Well, it turned up in pressed trousers and a lanyard. Given Brightbeam's early use, the press release - and far deeper reports from those with pre-access - OpenAI’s intent seems clear. This is a model shaped for professional output: structured documents, spreadsheets that survive scrutiny, slides that do not need rescuing, long-context reasoning and multi-step executions. The empha

Here's a fairy tale that explains how you get locked in to one AI model. OpenRouter and a16z speedrun just published their State Of AI report. Among all the data is something they've called the Glass Slipper Effect. The metaphor works like this: Users constantly test AI models against their toughest unsolved problems - trying on shoes, looking for a fit. When a new frontier model solves something that was previously impossible, those users lock in. Hard. And they don't switch

'They' would have had us believe ChatGPT-5.2 was landing yesterday. It didn't. But the interesting bit is what triggered the rush. OpenAI-related stocks, like Softbank, have fallen. Google and its suppliers are in the ascendency. The market narrative has moved from: 'fund OpenAI at any cost' to 'back Google's verticalised scale'. Google has the best model (Gemini 3); Google designs its own chips (Broadcom); and Google has the best unit economics. Marc Benioff might also have