How effective they are is dependent on the inputs (materials, model) and the skill of the operator. You have to model the entire shape of your output(s) to be successful. But the operator has to understand how to ensure a successful print with the appropriate level of intervention that matches your needs & expectations.

At the low end, you have Creality producing affordable, powerful — but limited — 3D printing accessible to anyone. At the high end you have LPBF machines from EOS that will print you a metal component for a plane or rocket in highly complex shapes.

LLM coding tools such as Codex, Claude Code, OpenCode, and GitHub Copilot CLI are the 3D printers of the software world, and they’ve already transformed what is possible, and the way that the possible is achieved. The hope is they will produce from fixes to features to entire products.

And, just like 3D printing, their adoption & usage is unevenly distributed.

Your coding agent output is dependent on your input materials (specs, details, guidance) how you operate it (follow on prompts, skills, reference materials, validation).

It’s the difference between a useful print, and a pile of plastic goo.

This is both grandiose (look what I did!) and self important (look what I did!). And LLM coding agents are radically changing the connection between you & the materials.

It’s fine that it’s changing.
Code becoming an unimportant detail is fine.
Software Practitioners will be fine.
I will be fine.

But the refrain of “the code was never the point” in response to the lamentation of this foundational shift is dismissive & lacks nuance — it lacks respect.

The journey mattered to those on the fucking journey. It actually wasn’t just about the destination, it was how you got to where you were going.

And it does matter that people feel a sense of… sadness? Loss? that the thing they honed, pined for, and got lost in, is going away. What’s being lost — what’s going away — is not the “typing at the keyboard to put arcane incantations into the ether”, it’s how it feels when you manifest something useful from nothing and share with an audience — a sense of accomplishment.

The LLM is the Temporal Loom.
And we’re The TVA.

I continue to be a believer in “goggles” being “the future” — The Chat Box™ can’t be it. Nor can it be screaming into the void, hoping it screams back.

Public companies that make $10bn in profit every quarter, but don’t increase that profit, are perceived as effectively $0-revenue businesses.

When coupled with the transfer of wealth not to the service, but the infrastructure, I wonder if we’ve got this all the wrong way around. Not only does local compute give power to the user — what happens on your local device, stays on your local device — but it also distributes the power consumption more broadly.

Are SaaS vendors moving calculations to the client today, and only storing the results in cloud storage, off-loading work to the clients? Does this end up trading computation for network egress costs?

Maybe I just don’t understand the aggregate power usage patterns?

My plan is to post them here posterity purposes. But I’ll also be posting social media (e.g., Bluesky and Mastodon) in a threaded format, and link back to the associated blog post.

It’s not the quality of the code, it’s achieving the outcome at all.

This steered us onto the topic of “quality” of output, and they said something closely approximating:

If it works, and it did it faster than a human would have, does it really matter? Ok, it’s not how you might have done it — or how sustainable you feel it may be. But unless you have concrete reasons why it’s not ‘good enough’, does it really matter if it works?

Fam, this got me. My whole career flashed before my eyes. And those of every single developer who has ever been told ‘write better code’, ‘write cleaner code’, or been put through the ringer of an interview where their code was ‘messy’ or ‘inefficient’ and they didn’t get the job.

Now we’re saying it’s OK? Now?

This is with the ‘background radiation’ that ‘architects should be writing more code’. Bro, what. I have to write more code so I stay sharp? But the thinking sand is YOLO? Why do we even bother with in-depth PRs? Why do we follow style guides? Why do we slow it all down, to make sure we get it right when it’s a human, but maybe it doesn’t really matter when it’s a robot?

This person wasn’t being douchey, or aggressive. It was a totally reasonable conversation. But in that moment — that singular moment — I saw the matrix.

Day 0 (Experimentation)

Look, we’ll start small. If we get feedback & DSAT (dissatisfaction) increases, we’ll pull back on them. They’re just to help offset the cost of maintaining the services that make our product so compelling. We’ll keep ads off bundle subscribers.

Day 30 (Rationalization)

Oh, they didn’t make much money — but that’s because they’re still learning & iterating on the targeting & right partners. That’s also why feedback says they’re annoying because they don’t feel targeted. It’ll get better.

Day 180 (Dependence)

Yeah, we are getting a lot of DSAT, but the ad revenue is really going well. It’s helping fund the next big feature, and the CFO loves us and is giving us more headcount to improve the core product.

Day 365 (Tolerance)

We know that these have tarnished some customer opinion of the product and has marginally impacted sales in the EU. But that’s been offset by the exponential growth in revenue — which is almost entirely profit, given our 85% margin!

Day 1095 (Escalation)

OK, so, we need to target these ads better to try to save the core business — so we can invest in it. For some reason, our sales have started to drop. We also want to focus on increasing the brand quality of the advertisers so we maintain a premium feel. But we also accept that we can’t grow on our core product, so we’re also investing in a cross-platform app, a better web app, and are working with car manufacturers to integrate our apps directly into the vehicles. They’re going to get a cut of the ad revenue. Plus, we’ll get more data access to improve our ad targeting — which we’ll also use to use time & traffic dependent ads.

Day 1825 (Identity Loss)

Oh, we make apps & technology products? I thought we were an ads business.

Seeing the Signs

There was a rumour in Mark Gurman’s Power On Apple newsletter recently:

Apple considers monetizing maps in another move to boost services revenue

… Now, Apple is giving this notion more thought. In a recent all-hands meeting for the Maps group, Apple said monetizing the app is a lever it is exploring. While there is no timeline or active engineering work being done, the company has again floated the idea of charging for prioritization in search results. It also could make certain locations appear more prominently on the map …

Under a week later, Apple announced ‘News+ Food’ to bolster its News+ subscription service. Their most recent quarterly results showed record subscription revenue driven by 14% YoY growth with 76% margins. Like so many in tech, Apple is becoming addicted to Revenue-as-a-service.

There’s no way back

RaaS feels so good — the validation from the market with a pat on the head every time the numbers go up. But there’s no way off this merry go round. Reduce your ads, or lower your subscriptions? The validation stops, and chaos begins. Focus on your core product? Branch out into a new non-RaaS area? You’ll never match the margins or scale of your RaaS products. You are trapped in your addiction.

Technology

Some what meta comment: Is AI separate from technology, or is it all part of technology know? 🤔 Anyway, I’ve lumped it all together.

• Alignment faking in large language models: I thought this was interesting — not so much the concept of a model ‘concealing’ it’s true thoughts, but the extracting some ‘secret’ thought stack into a separate scratch pad. It’s not clear from the post if this is in the token stream (and trained to skip over?) of if it’s distinct from the token stream, so doesn’t influence the output token stream. On ‘concealment’ itself: It doesn’t feel that odd given the large input data set that even in a ‘pure’ token prediction scenario that linguistically the concealment would be covered through text. It doesn’t feel super insightful?

• LLMs have say everything out loud. But maybe they don’t: I’ve long been… displeased? Disappointed? That the core capabilities of the LLMs seems to be exposed through… english prose. We’ve come thousands of years, a 100 years of computers, with hundreds of formats for data and we conclude… english? Is the lingua franca of the future of intelligence? That seems weird, and terribly inefficient. But this article suggests that there is hope to being able to have the conversion to english/text be optional. This gives me hope, because surely the future isn’t built upon a keen understanding of their / they’re & your / you’re…

• Faith & Fate: Fuzzy Transformers: insert that standard distribution graph with the amateur at the start, enjoyer in the middle, and the expert at the end. Amateur & expert say “LLMs are just fancy auto complete”. Enjoyers ascribe consciousness…

• The AI Summer: Theres something different this time with AI. But it’s not that it’s going to be the fastest technology transformation — it’s going to take a long slumbering, lazy summer, to find out how they can actually be useful; how they can have purpose; how they can add value. How they can be something beyond a distraction.

• Machines of Loving Grace: This is a great read as the contrast to the fever dream that is Situational Awareness. This seems to have its feet on the ground — albeit hopeful, aspirational feet — about what might happen. I think it’s too positive in its hope for biology/medical breakthroughs, and too hand wavy for the social/governmental impact (“idk, might be hard” doesn’t cut it). Definitely worth a read to at least level set how those that are running the foundation modelers are projecting their own dreams.

• Where are we on AI expectations?: as they say “it’s artificial intelligence until it works”, this takes a look at some of the historical cases of the last few AI boom-to-bust and asks us to learn from the past

• What Do We Want Computers to Do?: This is a great article that gets to the core of what the value of generative AI is. Everyone’s own personal bar will be different. There are levels of care & passion that go into the various jobs we all do in our lives. But there is also context — if I’m unskilled (in art, as I am), and I wish to obtain an image for a flyer etc, I have different choices available. I can pick from pre-existing stock art (from free clip art to a getty image), I can create something that does not meet what I envisioned, but is ‘authentic’, or I can accept something that gets closer, but still a long way from my minds eye (aka Generative AI). It’s not an absolute measure — the context does matter. But it’s also influenced by people who have something else in their life that to them matters more than creating something without ‘generative’ tools — either because of cost, time, or they dgaf. There is no one answer.

Software Engineering

• Decision-Making pitfalls for technical leaders: Making decisions is more than just making the decision. Theres so much more about the context of the decision — not just the things that go into the decision, but your own framework of making that decision. It’s very easy apply one perspective to all decisions, but really you have to think about what it is you’re actually trying to achieve and why.

• Systems: The purposes of a system is what it does: Reading this article, I realised I do this all the time. I just wasn’t thinking about it in a pure systems sense. I was caught up in ‘incentives’, and how when people rail against behaviour of their coworkers — a faceless process implemented by their coworkers — I say ‘think about the incentives that the humans involved here have, and how they may cause the behaviours you see’. But this I think is so much better. The system is doing what it does. It is not ‘broken’. The context, and purpose of the system might be broken, and instead of changing the system — wagging the dog — change what the system is supposed to be doing.

• Poets and police: This feels like “Dreamers” vs “Absolutists”, and I’m so in the Poet/Dreamer bucket. I love the contrast between someone painting a picture of a better future — a path forward — and someone who calls out the gap between what is being sold, and the reality ultimately in an attempt to destroy the dream.

• Software Engineer Titles Have (Almost) Lost All Their Meaning: There is a trope — one which I have observed first hand — that titles have been inflated over the last 5-8 years or so. I saw it before that with the phrase “Senior is the new SDE II”, and I’ve seen it recently as ‘Principal it the new Senior’. The reality is that it’s not that clear cut, but theres also more than a grain or nugget of truth here.

  There is — of course — the counter-argument that this theory is powered by capitalistic motivations on company and personal levels.

  1. As an employer, you of course want to keep titles deflated — it saves you money!
  2. As a coworker, you want to keep getting the bigger slice of the pie, and to laud your title over others. You need to punch down to keep yourself elevated.

• Eng org seniority-mix model.: Will Larson has been on a tear recently using Systems Modeling to look at the impact of different policy or investment choices you can make in your organization — they’ve been great. This one, however, shone a light on a slightly uncomfortable truth: You can’t promote everyone all the time. You have to constrain and be intentional about your mix. You have to also manage those senior people out to promote from within.

  This is an interesting companion article to ‘Title Inflation’ I’ve also linked.

• Writing Down (And Searching Through) Every UUID: I love how everything is “fake”. None of it is an anything like what you would build to meet the “spec” because it’s all tweaked meet what your perceive correctly rather than the “factual” interpretation of the “spec”.

  For historical job experience reasons, I’m still impressed he got the scrolling almost perfect, when there is, infact, no scrolling happening.

• Microsevices are technical debt: Interesting video, spicy title. More seriously: “Microservice all the things” does lead to technical debt. But it’s better termed ‘sociotechnical debt’ rather than pure technical debt.

  But it also sparked this thang I’ve been grinding on for years: Microservices are ‘dynamic libraries’ from client software development with higher latency. It’s the same problems but with latency. For the longest time I’ve been trying to find the right way for me to talk about it like that without people going ‘wtf’. This video actually made me realise: there is more active discussion of resolving these tensions in the ‘services world’ than the client world (E.g., big honking windows monolith), and that I should instead be trying to get the client monolith people to engage with the services world to make forward progress on understanding their problem.

  (Post that took me to this video)

Leadership / Management / Career

• Economic Termites Are Everywhere: This would have been better titled as “Hidden Monopolies”. It opens really strong, and sets a great picture for an interesting deep dive. But then whiffs it by basically exposing some relatively obvious monopolies, rather than resolving the opening scenario of an expensive commercial space refit. Still an interesting skim.

• Nobody knows whats going on: Working in tech, at a time that tech is written about everywhere, really throws this into sharp relief. We’re all just moving around on hopium & copium highs.

• Story Points are Pointless, Measure Queues: I have, for over a decade, used the phrase “story points are not a convertible currency” to mitigate the inter-team battle of how-many-points-did-you-do that the Pointy Haired Types always catalyze. This article talks about this, and some other suggestions. It’s conclusions are reasonable, grounded, and well thought through (breakdown to tasks, measure you queue length). But at the same time it feels like it’s written from the perspective of ‘This is a pure way to do it’, and misses how you can actually get it in to an organization. It also feels grounded in ‘my problem can be mapped out without reams of pre-work’, which I feel some ‘high-tech’ companies can’t do — bringing up a new AI model integration into an OS seems like it’s not a ‘discovered set of work’, and makes it hard to extrapolate further out in reality.

• Things I learned about strategy: While short on ‘data’, this post resonates. “You make things, or you sell things” is a truism — I always thought “don’t work in a cost center” was also a good way to apply this. And the strategy — so much yes. “strategy is not something that some staff person does, strategy happens every day in every decision and your line managers need to be your best strategists”.

• Grifters, believers, grinders, and coasters: The article says this, but before you click: This isn’t about deception or fraud in the workplace. You need to go in thinking of different words to describe the archetypes. I would have picked ‘Pleasers, Believers, Grinders, and Minders’ — Pleasers want to present a perspective that ensures they move forward by pleasing people; minders are just minding their own business doing whats needed and getting on with life. Anyway, the article talks about the different relationships that they have with their jobs, and how you need a good mix for a healthy organization.

• Why shouldn’t I go back to my ex?: “Why shouldn’t I go back to my ex?’ He said, ‘If you see the same tree twice in a forest; It’s because you’re lost.“. I can’t stop thinking about this — not in the context of romantic relationships (I don’t dispute in that context!), but life in general. That job you once had. That house you lived in. When you’re searching for a repeat, it means you’re not sure where you are any more and you need comfort and familiarity.

• How AI will change democracy: The interesting take away isn’t “AI & Democracy”, it’s that automation has outsized impact when it enables order of magnitude changes (increases) the scale the system or process being automated. You can see echos of this across other times – where scale has changed through automation. Publishing (the internet) becoming free — changes everything about information flow. eCommerce changes how prices manifest — they change in a blink of an eye, and are even less uniformly distributed than “before”. Be conscious of what a step change would mean.

• The Ghosts In The Machine: Musicians are taking contract work to make ends meet and feeling the loss of their ‘soul’ is the same software developers doing their job where they have become unmoored from passions - side projects are their true passion. The musicians are aghast at the fact that business went and businessed something that was clearly going to happen, even without Spotify/Streaming. Boy/girl band formulaic pop of the 90s-00’s for told this. Bowie was the harbinger with Bowie Bonds. We’re now surprised by the overtness, but it was inevitable.

  Casual Viewing is essentially the same, but about the movie industry. It’s more impassioned, more existential, dare I say ranty. But it’s come across the same point — commoditization of content, because it turns people don’t care about what they read, what they watch, and what they listen to. It’s not chewing gum for the eyes or ears — it’s chewing gum for the soul. And it’s full of empty calories.

• Home-cooked software and Barefoot developers: I’ve long had this vibe that a lot of software is built solely in the context of ‘hitting it big’ or being ‘a success’ (by the larger social norms), and that we’re missing the fact there is a different world for software that ‘solves peoples problems’ — problems that are terribly narrow, and absolutely not a business. But they do make peoples lives better. This presentation/transcript from Maggie goes down this path under the banner of ‘local-first software’ (really, she means local software for local people) with a side helping of a concept of “barefoot developers”.

• Design doesn’t have to end like this: A very thought provoking article about the relationship between business, AI, and the discipline of Design. Theres a thread of ‘stick it too the man’, and ‘it’s about the craft man’. But then I realized that if you substitute ‘design’ and ‘designer’ with ‘engineering’ and ‘engineer’, and it hit differently. It was clear I was saying the same things, taking the same stance — unwilling to embrace the inevitable, and thinking about ‘taste’ as the de facto determinator in everything.

• How I use “AI”: This is such an interesting article. It’s how a real person really uses AI/LLMs. And it blows my mind in a way that I have to introspect a lot. This person deals in a currency that feels somewhat ephemeral — nothing is permenant. And the LLM does a great job here. But also seeing the level of detail and discussion they go into throws me off a little, and I can’t quantify why. We invest orders of magnitude more effort & time to get actual fucking humans to do this stuff. But this — chatting with an LLM — some how feels like more work for less valuable outcome. But, thats just the feeling.

Technology

• Your tech or my tech: At what point, and what trade offs, do you make when you decide the thing is no longer your core competency?
• Distracted: This is something I think about a lot. I have so many thoughts in my ‘ill thought through pontifications’ pile related to this. We’ve lost sight of something — but I’m too distracted to really understand what that was.
• The Next 40: The iPad and Apple Vision Pro are held back by software policy. I understand the motivation for those restrictions, but they have to relent. We have to allow a greater depth of capability in our software environment — it’s critical to unleash a whole new era of amazing hardware in amazing places. The hardware is ready — waiting to be unleashed.
• Cyber-security pre-war reality check: I’ve had similar — not as well articulated — thoughts in my idle moments wondering how the giant jenga that is modern tech continues to function when we all know it’s sticks & bubble gum. At least the US, for the most part, does still have the expertise to ‘rebuild’, or ‘own’ the infrastructure. Except where it doesn’t — say, repairing underwater cables, which seems to be something the US doesn’t have domiciled within its control (except maybe the military?)

“AI” / LLMs

• Intro to Large Language Models: a great intro to the high level mechanics of how an LLM comes into existence
• How the frontier became the slogan of uncontrolled AI: Brilliantly scathing piece on the hubris, and expansionism around AI. I’m not entirely sure I’m 100% aligned with it, but it’s thought provoking nonetheless.
• The Value of LLMs: This resonates well with me. LLMs produce things that are believable, but maybe wrong. I have to do this all the time with everything in my job — adding another layer (multiple!) of indirection & ambiguity does not make my job easier or better.
• Looking for AI use cases: A great take on AI (well, chat bots / autonomous agents), and I’m in total agreement. It reminds me of the arc of Goggles. AI is the future, but we’re not in the future. Yet. (and it’s a long way away)
• AI isnt useless: Molly white does a brilliant job of capturing how I feel about The AIs. She writes so well, and covers nuance. Love it. (I wish we could agree to call ML ML, and leave AI to the future)
• A series of papers that tell a journey for Apple, and how they think they’ve found a real world use case for the LLM. Reading these makes me feel they’re really about accessibility scenarios, but maybe they’re able to get them sufficiently rich to work for the Siri case.
  • MARRS (reference resolution)
  • MM1 (combining ferret model)
  • ReALM (more reference resolution)
  • Ferret-UI (putting all of it together)
• Among the AI doomsayers: Maybe I’ve been around too long, but this article feels like an echo of the various booms of the last 25 years — The Internet (DotCom), “Technology” (Web 2.0), and to a lesser extent Crypto. It’s quirky (to the external observer) written about by an outsider seeking insight and failing to find any. But because of the quirkiness, it feels like it’s shining a light onto a unique story. But I remember this with the DotCom boom/bust, and most definitely with the nascent Web 2.0. It’s not a failure of the times, or even the article, but it’s important to remember that when we say ‘history doesn’t repeat, but it does rhyme’, that includes the cycles.

Software Engineering

• Breaking down tasks: In my career, one of the pivotal learnings that let me become efficient at work was breaking tasks down. Before going through the ringer to learn this, I’d just split out work as a series of hand-wavy, laissez-faire buckets of work without a real plan. Would it be easier? Would it be harder? idk man, i’m just going on vibes. But having to break them into tasks that represented no more than 4hrs of work transformed how I thought about it. The reality is: It’s not the tasks that matter — it’s the process & journey that enlightens you to the real work you’ve got to do
• Laws of Software Evolution: This hit hard; so much we do in software is ‘tear it down and start again’, and not enough ‘how can set this up to evolve’. There are so many different approaches, and people get stuck in those ways of thinking — often with the misguided belief of ‘If we just got it done in this one right way, it’d be solved’, and thats so rarely the case. Definitely worth the 3-5 minute read while waiting for the kettle to boil & your tea to steep.
• Swift concurrency waits for no one: Lovely read on the perils of concurrency runtimes - in Swift, in this case. While I’m told this is very different to the C# async/await, it feels very similar to me - unexpected forward progress problems with thread starvation. But maybe I’m just a noob and pattern match too much

Leadership / Management / Career

• The Builders Guide to Better Mousetraps: A nice, short – and low-preaching – review of how you should think about tackling new problem areas. Reminded me of the phrase “is the juice worth the squeeze”
• Developer Productivity For Humans: How can we understand, measure, and improve the “productivity” of developers? What are the real things that we need to understand & measure to make it possible to actually improve it. This is a great multi-part (Part 2 (not interesting), 3, 4, 5, 6, 7) series from a team at Googles purpose was do original research into this topic.
• Layers Of Context: Understanding context is crucial. Being aware there is more than one context is crucial. Do not be blinded by your local context.
• Multi-dimensional tradeoffs: So often we look at trade offs in this kinda single or maybe two axis choice. This way, or the other way. However, there are often more than those first-glance dimensions to them — and people can’t see the wood for the trees. But uncovering those additional dimensions of insight can help you make it much clearer which direction you should head.

Random

• Money Bubble: AI, Financing, the end of ZIRP, and the weight of the expectation of profits go up.
• Muse Retrospective: Building it well, with love, passion and perceived problem-solving does not guarantee success. Also I feel like this specific is something many have taken a run at, and no-one has cracked it. Apple with Freeform, Miro, FigmaJam etc are not far from this particular Apple tree. Makes me wonder if it’s just not a good paradigm.
• Coming of Age at the dawn of the social internet: I lament the loss of the internet — both social- and the wider- internet — in a way that feels very strange. This article captures a good sense of that — although, entirely different in its detail. I wonder if my continuing distaste of ‘optimization above all’ extends beyond pure commerce, to the social web? We have driven ourselves to optimize our social projection, to maximise some quality of it. We can’t just let it be — we can’t even be authentic, in our authenticness.
• Politics and the English language: George Orwell opines upon the relationship between language and politics. I think this expands to all writing - technical writing gets caught up here too. We can do better.

Technology

• Cursorless is alien magic from the future: I am forever struggling to accept talking to my computer, but this one seems pretty rad. I like that it’s not ‘speak code’ but ‘speak operations’.
• AI, and everything else: Great presentation every year. Worth a read if you like to think more than a year out, and where the puck might be going.
• AI and Trust: An interesting way to think about “trust” in AI. We - humans - keep making category errors and (my words) personifying the AI. We then try to regulate that personified construct. We should be regulating the creators - the corporations.
• AI Agents: This feels too Sci-Fi. This is where I can’t extrapolate to that future on anything other than “infinite time frame”. I believe we will reach that point — but the article feels like it’s written on the expectation of ‘very soon’. But this picture is the same that was posted 20 years ago. I know we’re closer, but we’re still not on the downward slope.
• What kind of bubble is AI?: Cory Doctrow looks at the AI bubble through the lens previous bubbles (dotcom, crypto, gfc), and asks “What will this one leave behind”. The general sentiment here aligns with how I feel about AI right now, although I think the cherry picked example of Cruise is too perfect, too neat.

Software Engineering

• Creating Technical Leverage: I love it when people talk about capabilities, and leveraging existing capabilities in new ways. Technology is about enabling people to achieve new things. But rarely are we building single-solutions to single problems — when you break it down it’s actually about composing existing & new capabilities into solving the problem.
• Maybe Getting Rid of Your QA Team Was A Bad Idea Actually: Don’t like the title. Do like the content. Triage, Defect Tracking, Regression, End To End are very important. You can’t eliminate them. You could reduce them, but be careful how far you go before it falls apart (not very far)

• A Coder considers the waning days of the craft: I’ve thought about this a lot since I read it. The sentiment, I feel. I enjoy “crunching code”, and hewing something out of cold, hard, electrons in my editor and unleashing what I hath wrought upon the world.

  But theres something about the story that makes me think about the “Tri modal Engineering Salaries”. Specifically that there is a set of software work that (1) will be obliterated by the LLMs (2) will be augmented, or (3) is untouchable for a long while (until we get the AGI). I think — I hope — I’m in that second bucket. I think I’d like to be in the 3rd. But I’m screwed if I’m in the first. But I think the authors role might be in bucket one, which kinda makes me unsure about what to read out of the whole story as a commentary on ‘coding craft’.

Leadership / Management / Career

• An Exhausting year in and out of the office: A reflective article on the intrinsic challenges of digital communications, and how many struggle to adapt. There’s a lot of truth here, but I can’t avoid also thinking “a bad craftsperson blames their tools”: The tools can be used in different ways — some effectively, some not. Not everyone has adapted or learned to wield digital communication tools effectively.
• Cathedral vs Bazaar People Management: Stolen from the OG Eric S Raymond, this paradigm applied to managing people is interesting. I think the biggest challenge is you have to be able to do both, concurrently, on a person-by-person basis to get the maximum benefit. Worth a read as you think about managing people.
• Why Should You (Or Anyone) Become An Engineering Manager?: A brilliant breakdown on what it means to be a manager. Perfect.

Random

• Colin Mayer’s ‘Prosperity’ and the Future of the Corporation: “shareholder value” as the mantra by which we run businesses has lead to some pretty bad behaviour in aggregate. I, someone who knows bupkis about the nash equilibrium, (great movie!) feels Colin Mayer’s suggestion for the purpose of a corporation might be better in the long run
• Nervous Energy: This is a journey I’ve been going through — getting that habit of circling the stupid websites out of me to let my brain slow down. I was semi successful in 2020, for about 10 months, of just Getting Off The Socials™. I need to take a serious run at it again.
• Seeing like a bank: A lovely essay about why bank customer support & systems seem so bonkers. But I would also extend this to all customer support.

Technology

• The Age of AI has begun: Bill Gates does a good intro to high level thinking of the impact of AI. Good, or bad. Efficient or inefficient, it fits my view on some of the opportunities and end-use of the current crop of AI. I’m not sure I’m bullish on it, or optimistic, but the story is something I agree with.
• Why chatbots are not the future: A text box isn’t the future of UI. I enjoy this thoughtful, and reasonable walk through of the realities & challenges of ‘TaaUI’.
• You are not a parrot: From a researcher who boldly out that language isn’t just parroting syntactically correct words. It’s backed by so much more — and how if we forget that, we’re going to be caught like the emperor with his new clothes.
• Catching up on the weird world of LLMs: What was the technical development journey got us to the current LLM situation? This talk — and its transcript — is great at trying to wrap it up and put a bow on it.
• Cargo Cult AI: So many have jumped on the bandwagon of AI Doom / AI is magic, and they’ve lost sight of the wood for the trees. This is a nice taking a step back and looking at this from a less loaded angle.
• AI isn’t good enough: AI is hailed as replacing many job. Yet, in many situations is far from even barely getting by. A look at this from a jobs perspective.
• Unbundling AI: We’ve been presented with the omnipotent chat agent. We are beholden to an unadorned box of opportunity and infinite possibility. But, this is unlikely to be how it really plays out — we’re going to unbundle it!
• Big Tech’s Biggest Bets (Or What It Takes to Build a Billion-User Platform): Ever thought about how much money, time, and sTrAteGy goes into the big bets of the decade? Cars, AR, Search, AI… a good (long) read on this topic.
• Parallel futures in mobile application development: What are the parallel futures of ‘native’ app stacks? Do they all look the same, siloed by the seed that spawned them? Is there a monoculture ahead of us? A look at some of the interesting paths for ‘native’ app development in the future.
• We have left the cloud: I find this interesting because while there is clearly survivorship bias here, I think there is a nugget of value in ‘maybe we don’t all end up in the cloud’. I think, in my limited experience, this speaks to there being a gap in the cloud infrastructure, pricing wise, that makes the cloud too expensive, and on-premises cost effective. But below a certain size, the cloud is the winner.
• Will AI become the new McKinsey: What if AI isn’t the greatest leveler, the great bicycle mind, but — effectively — the management consultancy distilled into its purest form, and weaponised against us? I dunno. But I thought it was interesting to think about how the LLMs will be deployed to accelerate things that are already in place, not change the game — at least in the short term.
• The Next Larger Context: Often it’s said “understand one more level of abstraction”. This is a good read on a more pragmatic telling of that — here it’s framed as ‘what is the context that your solution sits within’.

Software Engineering

• Choose boring culture: It’s often said ‘choose boring technology’ — e.g., tried, tested, reliable, don’t go spicy (I subscribe to this thinking). But what about culture? People seem to be trying to ‘innovate’ with their culture — but as the article boldly states: No one wants to work in an “exciting” culture.
• Software and its discontents: “software engineer” / “tech, from inside” has been negatively vibing in different ways for a while. From early in career to cynical old farts, theres been a greater sense of ‘theres something not right’. This series of posts are well worth a read — the author has tried to drill into this. It’s a thought sparking read. Give it a shot. Part 2, Part 3
• My 20 Year Career is Technical Debt or Deprecated: We spend a lot of time saying ‘we should avoid technical debt’. We make processes, systems, cultures to avoid taking on too much, and to ensure we pay it down. But, ultimately, the truism is that all code is tech debt. All. Of. It.
• How platform teams get stuff done: Not everything is — or should be — a platform, but when you have one you could do a lot worse than follow this set of organizational & process patterns to make sure you’re meeting your (internal) customers needs as the platform they need to depend on.
• My Approach to Building Large Technical Projects: Side projects, large projects - all face the challenge of staying motivated when faced with a multitude of parts, and wanting to see progress. This article tells a story of how one person breaks down a large technical project to stay motivated.
• In the middle of planning: Planning is a thing in many organizations. Some do well at continuous planning. Some work better with annual planning. Some are in the middle. But if you’re a middle manager, you gotta show two plans - up to the PHBs, and down to the peeps who really do the work. This is a good article providing a practical view.
• How to communicate like a GitHub engineer: This pretends to be about how GitHub uses GitHub to do its thang. But it’s really about how they communicate & information. It sounds fantastic!
• Bottlenecks vs Bandpass: Most applicable to platforms, but has relevance elsewhere where. Tl;dr: don’t try to review & support - look at the things that most likely to go off the rails

Random

• We need more women founders on offense: Glossier is an interesting cosmetics company, coming from the startup world rather than the big cosmetics companies. Founded by a woman, and somewhat had the press telling an odd narrative. This article is from their former head of communications, and is a great insight into the way narratives about women are just told differently. Loved reading this.
• ‘The creative process is fabulously unpredictable. A great idea cannot be predicted’: This is an interesting interview with Jony Ive — I love the reframing into creating not just designing. Because thats what we really got in to this thing for — creating something new. It’s also a lovely philosophical walk through a positive way of thinking.
• Multi layered calendars: A common nerd trope is note taking, can capturing of everything we do so we can find it again in the future (See rewind.ai, for example). But often you’ve gotta make sense of it all. I love this article as a way to think about calendars differently, and how given that time is such a defining aspect of our lives, maybe temporarily through layers is a great way to think about that?
• We can leave the Solar System, but arriving anywhere is not happening soon: Sometimes it’s easy to forget just how large the universe is.
• Buy my course and make 6 figures: Former colleague Claudio Guglieri wrote a lovely short article about the ‘Grift’ that has followed the embracing of ‘design’. Although, with the recent perception that ‘design is dead’, I wonder if these grifters can really survive?