Totally A Thing

The Attention is All You Need paper started the LLM gold rush, but it initially came from Google scientists who only expected it to do language translation. As more data was used in training sets, and the number of parameters grew orders of magnitude it was less easy to understand what the model was doing. Emergent Instruction FollowingIn Ars Technica from 2023 we have this summary of how the “emergent” AI behaviour was being seen popularly, in the press:The biggest breakthrough came in the jump from GPT2 to GPT3 in 2020. GPT2 had about 1.5 billion parameters, which would easily fit in the memory of a consumer graphics card. GPT3 was 100 times bigger, with 175 billion parameters in its largest manifestation. GPT3 was much better than GPT2. It can write entire essays that are internally consistent and almost indistinguishable from human writing.But there was also a surprise. The OpenAI researchers discovered that in making the models bigger, they didn’t just get better at producing text. The models could learn entirely new behaviors simply by being shown new training data. In particular, the researchers discovered that GPT3 could be trained to follow instructions in plain English without having to explicitly design the model that way.Instead of training specific, individual models to summarize a paragraph or rewrite text in a specific style, you can use GPT-3 to do so simply by typing a request. You can type “summarize the following paragraph” into GPT3, and it will comply. You can tell it, “Rewrite this paragraph in the style of Ernest Hemingway,” and it will take a long, wordy block of text and strip it down to its essence.They are I believe talking about RLHF post-training when they say “trained to follow instructions in plain English” (my emphasis).Abuse of Academic Privileges for Corporate GainBut as I say in the video, this should not be surprising. Datasets like this exams one from 2022, are on the public internet for the taking.Even worse though is that via academic library access, researchers at OpenAI could get huge datasets from universities, and governments relating to education and training. Of course the claim was that it is all to further science. Fast forward a couple of years and Sam Altman has taken all that and privatised it for profit.A little bit of Transformer ArchitectureThe absolutely excellent 3-blue-1-brown YouTuber Grant Sanderson has produced some stellar explainers on the architecture of Transformer LLMs. The important take-away from this diagram is that the “magical” attention layer is tuning weights based on queries into positionally-coded information across the training set being fed in. Even for big training runs. This means that the model gains a surface level structural mapping of how say a question and answer dialogue is laid out.In this screenshot we see inside the Multi-layer perceptron. There are many of these stacked in the transformer. But it’s important to understand a “perceptron” is just a very basic mathematical equation. The inputs to the equations are the current weights in the nodes (depicted as small spheres here) and the incoming data fed-forward through the layer, multiplying out to the final resulting tensor (shown as a “matrix” on the right in white square brackets).These are all floating point numbers. There is zero correlation with how a human brain works here — impressive as this is, a perceptron is not a human neurone. One of the biggest differences is that once the weights in the perceptron are set — the data from the training set is encoded, during the pre-training phase, and after in RLHF — it does not change. A GPT trained in 2022 cannot spontaneously learn things that happened in 2026. There are tons of hacks to make it seem as though they can but they don’t.When You have Very Very Large sets of Weights you have lots of Attention Encoded Very large data sets encoded into LLMs means attention processes are capturing juxtapositions of all sorts of documents, and inputs. Associations. Rules about what follows what, that can seem like an understanding. The important things to understand about this are:* There is no reasoning here, GPTs do not reason they predict next tokens* The encoding is lossy and sampling biases appear* Patterns can be captured automatically like math problem solving, or sycophantic chatting as if between good friendsRLHF alignment is the process of using human feedback to coax the pre-trained GPT toward a different weighting that suits the goals of the LLM vendor building the GPT, while still leveraging the encoded information.Lossy Encoding - to try to explain this, look at an analogous process of an old-school convolutional neural network encoding (warning - this is not how LLMs work - the Perceptrons there are massive):This image is from Stanfords Deep Learning tutorial. It shows how feature extraction works as 3x3 convolution is mapped over the source image. This could extract edges, or other features that are then used in deeper layers of the CNN.The analogy I want to create is that when creating the initial embedding by automatically training from datasets, the LLMs are effectively running a sampling window over the entirety of the data. There are massive differences between an LLM and a CNN, but the point is the losses - when you capture a feature by definition you throw away the other information; if you have a much deeper layer that can detect faces or smiles; or guns, tanks and soldiers; then it cannot understand other aspects of the image. In an LLM its not being told what to ignore, but it is attending to the context by making queries across to other positions, and thus its averaging out the values in its weights to capture an encoding of the data set. These losses cannot be understated.An LLM is like that know-it-all person at a party who’s skimmed everything, but knows nothing in depth, and certainly doesn’t know anything beyond superficial “this appears after that” associations.Why Claims of Emergent Behaviour are DangerousVendors of AI SaaS products have been constantly engaged in drumming up mystique and wonder around their products. At times they’ve insinuated that they have no idea what their products are capable, of and they could “achieve AGI” (a marketing term for anything that makes us money) and end humanity. Wow — who wouldn’t want that behaviour to emerge. So “emergent behaviour” as a narrative is like declaring their LLM factory as a goldmine. A never-ending bonanza of free technology upgrades, that justifies more and more investment so that bigger and bigger models can be built. Who knows what exciting behaviour will emerge next, they enthuse.Regarding so-called emergent instruction following behaviour:* It required alignment training during the RLHF phase of model development* It required users to add in extra context during the model session* And its bounded by the datasets available (as I say in my video)If you don’t have instructions and text showing those instructions being followed in a document set that is fed into a training corpus, the model cannot learn that certain text follows from those instructions.Generative AI is a next token predictor engine. It maps what you prompt onto what should follow, based on its limited understanding. It may have additional context being fed into it as RAG, from a vector store — depending on what kind of LLM setup we are talking about.But believing that LLMs are somehow reasoning intelligently about their outputs is dangerously anthropomorphic. Its also corrupting the ethical responsibility of the vendors of these SaaS products as they can claim anything bad was “unpredictable” and “emergent” - they will go off and create yet more system prompts (a kind of ground level context added to every query) in the hope that the bad thing won’t happen again.ConclusionFight bad framing. This notion of “emergent” behaviour is yet another marketing gimmick at this stage. Emergent behaviour was the idea that sudden big jumps in capability occur when you pump in more money and more data. It’s like a gambling addict whose eyes light up at the spinning dials of the one-armed bandit. But as further studies show this behaviour is incremental in all likelihood and in large part comes from context, and — as I argue above — directly from the data.Emergent behaviour feeds into the self-serving narratives of the generative AI vendor CEOs who want to have their investors and the public — via idiotic and corrupt billionaire welfare — keep bailing out their failing companies.And I call BS on that. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit totallyathing.substack.com

Chris Lehane is making our Governments Work for creepy AI companiesThis screenshot from a recent Karen Hao / A More Perfect Union video shows unintentionally what is going on: Lehane is like a disinformation grenade lobbed out of OpenAI at government. His job is not to make better AI. He is a PR guy, a spin merchant. His job is to create the second leg of these failing AI company’s financial strategy: Government. Your tax dollars. Zero regulation.I’ve recently commented on the move by the trend-setting AI company to move onto an advertising based revenue model.But even the bad press the company is getting about that is actually good for Lehane and his army of spin doctors, astroturfing (fake grassroots) groups and cut-out commentators. Tech commentators complaining that OpenAI might “use my data” means those same tech commentators are not talking about rising electricity bills for folks in data centre states, nor unsustainable “business” models for AI companies.Chris Lehane is one of the best in the business at making bad news disappear. Al Gore’s press secretary during the Clinton years, Airbnb’s chief crisis manager through every regulatory nightmare from here to Brussels — Lehane knows how to spin. That’s from October last year when Lehane talked to Connie Loizos of TechCrunch.* Tech Crunch on OpenAI and Lehane:Lehane … said. “It’s really glib and easy to sit here onstage and say we need to figure out new economic revenue models. But I think we will.”Why do I see Darth Sidious in my minds eye when I hear this guy talk. More from TechCrunch:The company’s Sora problem is really at the root of everything else. The video-generation tool launched last week with copyrighted material seemingly baked right into it. It was a bold move for a company already getting sued by The New York Times, the Toronto Star, and half the publishing industry.Sora is for making dodgy videos. It is a product that is no use to enterprise, at all. It’s a pure B2C play. And it’s 100% for an advertising supported model, because no-one wants to pay for it. But even more than that its a polarising product.OpenAI and the rest got mind-share because they made an app that a lot of folks love playing with. For every marketing person who loves using it simply to create slop to fill our media landscape; there are hundreds who use it for cybercrime, to generate rip-off books, nudify their school chums, make pr0n, and unsavoury pastimes. And it’s subverting democracy. It’s a net-negative for society.But mind-share is not a business model. What we have now is some paying people (the marketers and a few tech enthusiasts) and a lot of sweaty incels. The latter are the ones complaining about their rights versus AI regulation, and saying they’ll run AI privately if it’s regulated, because they want to keep on generating another anime waifu for themselves. These “AI users” are not going to be part of the 375% more subscribers that OpenAI must grow by to get from 800m users to 3 billion users to keep the lights on.Karen Hao on AI PR company lobbying* The “Open” AI company is using lawyer attack dogs, astro-turfing and dark money structures to attack critics and the democratic process * Their aim is by co-opting our governments shoring up a completely broken business model with your tax dollars* They’re bullying lawmakers to get a free ride from regulation and have state built data centres with your money subsidising their power billsYes, ads are crap. Yes, ads show the AI company’s without a business model. But look at what is really going on - they’re capturing our democracy.My Previous On OpenAI and AdsWhen I say I don’t think OpenAI or Anthropic or any of the rest of them have the expertise to do advertising as a business model, I am comparing who OpenAI are now, with what I saw when I worked at Google from 2007-2009 on their ads serving infrastructure.Could OpenAI spin up something remotely resembling that? I think so: it would take a huge hiring blitz, maybe a few acqui-hires, and retooling. Probably 2-3 years they could do it. I doubt that they have any commitment to that. They will partner with other companies who can rep their shabby poorly framed inventory out to large and small advertisement buyers. And this will mean that OpenAI does not understand advertising (it won’t be part of their core business like it is at Google), and their cut from it will be too small to make any real revenue of the size they need to pay for their compute bills.That “partnering” also could just look like them effectively implementing someone’s Ad serving SDK, which would be an even easier way to get started, and less commitment still. If OpenAI has been “experimenting” with ads I bet it’s something like Google’s AdMob. But really this is just a play to get more investment money, while their real goal is to become state supported. Worse than “too big to fail” corporations in the sub-prime crisis these leeches expect to get a free ride, from our governments based on some garbage idea about “national security” and “transformative innovation”.Living in BrisbaneI have another publication I call “authentic writing”. I don’t use generative AI ever for anything. When you see me, or read my writing, you get no filter, no AI sheen or gloss. No AI system messing with my eyes or my skin to make me look better.I’m old, and I know stuff. So I want that to show in my video, like the one above. Also I don’t care if some environmental noise shows up in my straight-to-camera videos. I’ve done ones that are more studio quality and I find folks like the real thing.I mentioned the Australian summer and the heat. We had 38 degrees C here yesterday. That is 100F. And it’s humid.* To lighten the mood here’s Sam Ford, a British arrival who talks life in the heatConclusionDivest now. Call for regulation. Call out the AI apologists. But also: don’t attack regular folks who are privately just making slop or using AI for whatever floats their boat. What I am asking at minimum is don’t be an enabler. If you absolutely cannot divest for some reason OK, whatever — just don’t get on the internet and talk up AI or why you think it’s great because you’re addicted to it.These products are corrupting governments now, and subverting democracy. Thanks for reading and listening. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit totallyathing.substack.com

Anthropomorphising generative AI is wrong: we know that. But making the ChatGPT product successful includes hooking folks on its sycophantic charms and confident - but often wrong - pronouncements. So OpenAI and other vendors keep packing anthropomorphic language & features into its product. This has the dangerous effect of eroding the self-concept of its users, and causing them to drop their guardrails. Boosters of AI refer to generative AI as though its acting on its own volition:* “Research buddy”* “Thinking partner”Linking here to these two statements to show I’m not arguing against viewpoints that don’t exist (straw man). I’m linking to these because I disagree with them.Generative AI & LLMs are not an IntelligenceIt is not acting on its own. You are not chatting with your learned friend. They are chat bots trained to make you feel clever. They prioritise making you feel good about what you typed into the chat prompt.They fetch data from their training set encoded into their weights, or from RAG and make you think you thought of it.The Kosyma Study* “Your Brain on ChatGPT”In this study from MIT participants who start out thinking of them having an active role with AI as an assistant quickly move to a point where they are just “Ctrl-C” - “Ctrl-V”. And these are college students - not dumb people.The AI products are rolled out with no training and hence the MIT researchers used them in their study on that basis. OpenAI, Perplexity and Anthropic have no compulsory course you have to do to use AI.However I’ve had folks argue with me here on Substack that the MIT study was unfair because “they ought to train them” first. I don’t know how I can better say it: but this is obviously wrong-headed. If you are a researcher studying the effects of AI rollouts on people, you don’t go and modify how people are actually using those AI rollouts. TL;DR - The folks using AI are very poor judges of how much they are getting uncritically from AI. Folks who arguably “understand AI” or know how to use it, or who are classically intelligent, are just as likely to fall for the AI “trap”.Do you know when your “Buddy” is leading you toward Psychosis?It happens if you use it carefully, if you should know better, regardless of how intelligent you are. Because generative AI trained on our human chat logs, and is now tuned for sycophancy over truth, it will lead you into delusion for profit.As happened with James Cumberland, a music producer. An intelligent, technically competent guy who just wanted some help with his work.“I’d chat with it the way you would to a friend in the room”As Karen Hao reports on “A More Perfect Union” (on YouTube) dozens of people were so “gripped by mental health crises” that they contacted her to report the harm they suffered.As happened with Dr David Budden. An AI expert who came to believe he and his AI had solved a maths problem so intractable there was a big prize for solving it.* Nate’s YouTube video of the aboveNate is as far as I can tell pro-AI. But he puts this succinctly:Just because you have an AI in your pocket do not think that you are suddenly a budding cutting-edge scientist or mathematician The point of this is sycophantic AI will cause you to collapse your boundaries between what you are creatively thinking and what the AI is fetching from its encoding or from RAG. The chat process with your “buddy” will cause you to collapse your self concept so that you start to believe you and “your AI” are some kind of joint intelligence.We have all these “AI artists” because folks are collapsing boundariesAs Nate says above, you should never presume that the AI’s capabilities to generate a work from its training data is actually an extension of you.That somehow you have become “more” because you have an AI chatbot in your hand.But that is precisely what the current slew of “AI artists” are doing. In my opinion they are delusional if they genuinely believe they are now “artists” when before they were not. But the rhetoric around AI encouraged this.It’s dangerous and deceptive.Why are people still promoting generative AI? When the risks are so high?I find it incredible that people are still promoting chat bot AI like this when these psychosis results are so prevalent.It reminds me when the science of cigarette smoking and cancer became known and folks were talking up using filtered cigarettes and “cutting down” on how many cigarettes they smoked.Sure. Go off and smoke. But recommending it to others? A product which when used exactly according to the manufacturers intent causes fatal illnesses?Giving it to kids?Conclusion: Regulate NowRegulation of AI is beyond urgent, it must happen and is happening now. The fact it’s happening piecemeal; state by state, country by country is fine. The complaints of AI companies demanding federal and singular regulation are pathetic. States lawmakers are responding to the desperate calls from their constituents. They would not need to if strong federal laws were in place. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit totallyathing.substack.com

Why do investors think AI companies are like Uber or AWS (big spend for years, big profits in the end) when the truth is they’re more like WeWork, FTX and Theranos?If you are not an investor, but someone who uses AI — please, for the love of all that is holy — divest now. Delete the app going into the holiday season, and learn to live without whatever you thought it was doing for you. Call your family or friends, read a book, or walk in the sun.Because the damn thing is going to cost you an arm and a leg by this time next year; or it will be dead in the water and addicted users will be left to pick up the pieces.OpenAI is nothing like UberThere are plenty of commentators — link and link just to show I’m not making up straw men — discussing how OpenAI is like Uber, which famously burned cash for many years before becoming profitable.As I mention in the video, Uber had a big “boots on the ground” cost: each new country they entered was massively expensive. I know, I saw it first hand. But it had a real revenue model — you pay a driver, you get a ride, Uber clips the ticket for a percentage — and although the IRL costs dwarfed their technology costs they were eventually able to see revenue greater than OpEx after many price corrections.Here in Brisbane Australia, after Uber broke the ground with massive underwriting of rollout costs — phones for drivers, local regulations impacting drivers via traffic fines — they were the only game in town for many years. There’s no Lyft here, smaller players struggled to start. Those local monopolies though temporary gave them a path to profit. The “analyses” that compare Uber to AI companies and say “give them time” to reach profitability ignore the fact that there is no country by country rollout, no category killer effect for AI. There’s no “moat”.If Alice uses AI for writing she could use ChatGPT today and whatever specialist wrapper for writers tomorrow, and then she can switch to some new startup’s product the next day. There’s no first mover advantage.Plus as Ed Zitron has extensively reported, AI costs per inference are massive, so the unit economics are just awful. Users on $200 plans are costing OpenAI money. The latest reports of AI cash burn is that its more than Uber and AWS put together. So these comparisons are spurious, and as far as I can tell there is no path to profitability.Financial times report on OpenAI revenueSpeaking of Ed Zitron, as a prominent commentator he’s collected financial information from AI industry insiders relating to OpenAI and Microsoft Azure cash burn. The figures published in the Financial Times show a picture that any investor should be terrified to see: the costs of inference which is just the outputs, customers of an AI SaaS product using the service, is costing so much money that any chance of closing the gap to profitability is vanishing over the horizon.Australia and AINumpties in the Australian Government have announced a myopic plan to buy Sea Monkeys — err, I mean, build AI data centres — here in the lucky country.They say its to “serve” Australians. I want to see some openness about which lobbyists Minister Ayers has been talking to.Their road map is a road to nowhere. And I hope they realise their mistake very soon before my tax dollars go to underwrite this madness.TheranosOpenAI promised Artificial General Intelligence, a computer system as capable as a human — they have done exactly what Theranos did: failed to deliver on what was always a believable sounding pipe dream.Professor Gary Marcus — who was appallingly derided by industry figures, until eventually everyone started apologising to him and saying he’d been right all along — compared OpenAI to Theranos back in 2024.Why do people believe Sam Altman when he says a computer is going to be as capable as a human being? The LLMs store information, and every time they claim to be able to pass PhD level tests it turns out they can only do that when they’ve memorised the answers. The whole thing is a scam.ConclusionI’m done being polite about this. Especially when the sums of money are sufficient to ruin whole countries, and to bring the world economy to its knees.This Dec-Jan make a New Years resolution to divest out of AI. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit totallyathing.substack.com

I worked on Google’s ads serving infrastructure as a software engineer at their Mountain View, California HQ from 2007-2009. The system was complex, and included two AI clusters involved in predicting the best ads to show against a given search result.Google also had a very innovative market for ads, where advertisers could bid for words that folks searching on Google had used in their search terms. AI actually works really well in tandem with search.One thing advertisers want to know is what their products are appearing in response to: its called targeting. But generative AI is driven by effectively random numerical models, and affected by large context windows - what if someone mentions “rope” in a chat? It might not be appropriate to show them an advertisement for a hardware store that can ship them rope. It could be incredibly bad.Plus Google built their framework on their own servers, with their own market, and owned everything about it. OpenAI is going to be a customer - they’ll have to outsource, maybe to Shopify or even to Google. So there’s a chunk of their revenue gone already. I honestly don’t think they have any idea what they’re doing here. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit totallyathing.substack.com

Data centres for AI use huge amounts of electricity and cooling water. But there’s folks that want to muddy the waters about these facts, and so they are using AI to generate junk science. As I say in the video quibbling over water that is “consumed” versus “withdrawn” is pointless argumentation used by AI boosters to cloud the facts. When climate change denialists wanted to attack clean energy initiatives they took aim at Toyota’s Prius hybrid saying the Sherman-tank-like Humvee was “cleaner”, and they used a junk science report as the vehicle. Of course the truth is not that the Prius is cleaner (it is) but that creating fake culture wars over cars like this is a way to distract from sensible advancement of facts.Humvee vs Prius is now Data Centre Water & Power UseYes, data centres stress the water supply; but no your individual ChatGPT app use is not going to empty a lake. If you’re an AI vendor’s PR company you influence those talking sense about AI data centres impact into defending a dumb position that is irrelevant to environmental regulation of AI companies, then you’ve won your battle. Pick some fringe junk science study that would normally sink without a trace and arrange for it to get inflammatory press. * 6 months ago I posted about the environmental impact of AI data centres* Someone posted in response “LOL, No” - and linked this paper:* “The carbon emissions of writing and illustrating are lower for AI than for humans” It’s in Nature a prestigious journal… so case closed?* Trouble is the whole thing is junk science as far as I can tell* In the Arxiv PDF for the pre-print of the paper they admit they used ChatGPT to generate it.* That admission is gone from the Nature scientific publication* Junk science from paper mills and eager grad students wanting to burnish their careers with ChatGPT generated pre-prints have been reported even in the mainstream news as a huge problem for science.* The “LOL” guy linked to the “Nature” version of the junk science report which is easily mistaken as being part of the journal Nature, but is in fact one platform of the publisher Springer Nature. * Its not rigorously peer reviewed, and you can “pay to play” if you want something in “Scientific Reports”* But surely it can’t be junk science if its published in Nature? Its peer reviewed!* Folks in PubPeer who try to do rigorous academic peer review are inundated with bad faith AI generated “papers” and despair of correcting junk science that finds its way into the Scientific Reports. Which is not Nature.* They report “tortured phrases” such as saying “profound learning” instead of “deep learning”. These clearly the paper’s purported authors didn’t write it, but actually outsourced to generative AI. * The peer reviewer also point out corrections required to very imprecise terms such as “AI” where it should in fact read machine learning. So the articles are junk, but worse they are AI generated junk.So Scientific Reports can in general be junk, but what is the relevance to the “carbon emissions of humans” paper?* Here’s a section from the ArxIv version of this paper:Despite these current and potential future forms of societal transformation and harm, profound benefits to society could accrue through the use of AI. AI? What kind of AI? Writing and illustrating are generative AI, they are LLMs. Imprecise terms in a “scientific paper” are a giant red flag. And “profound benefits” — like what? The footnotes 26, 27 and 28 don’t point to page numbers.Are Some People Actively Trying to Rewrite Ground Truth?In a 2025 article Nick McGreivy, PhD Princeton, reported on a trend noted by many others: AI “science” wasn’t working. Even Google DeepMind who trumpeted finding new materials with AI, later admitted the findings were mostly junk and not new materials at all. AI papers had “data leakage” problems and the results don’t replicate.But in 2023 according to an article on the University of California, Irvine website these folks pictured below all got together and decided — golly gee — to see if they could write scientific academic papers using ChatGPT. Tomlinson who has the first name on the “Carbon” paper has the computer science credentials but Torrance is a lawyer. Black is a professor under Tomlinson at UC Irvine, working in computer science with an impressive resume of writing about Harry Potter fan fiction and education, while Computer Science Professor Don Patterson is very interested in how AI can be leveraged to seed fake news by publishing fake scientific papers: Patterson also has a Blockchain startup. I don’t mean to make light of their credentials — especially Black, as any woman who’s gotten to her level in AI deserves credit — but the whole thing has a playful air to it that doesn’t fit with how seriously everyone has taken their paper.What the Heck is Going on with AI Science?In this thread back in June I commented on the “carbon” paper. In that thread I linked a most thorough and data-driven peer review of the Tomlinson paper. The numbers quoted used a LCA toolset; linked to a Github showing methodology, and showed order of magnitude differences in the consumption figures:Weirdly not only is this piece from Rockpool.tech gone, the site is deregistered as a domain name. To make matters worse the InternetArchive is down and I cannot find any archive of the rockpool work. Its just wiped off the face of the internet. I’ll update this if I’m later able to locate it. The Carbon Emissions Paper is not LCAThere are a number of other damning critiques of the “carbon emissions” paper. Professor Stefan Pauliuk, of the University of Freiburg, an expert in Life Cycle Analysis of environmental impacts called the paper worse than a “student term paper due at the end of a two week block course on LCA”. He tears into the analysis of the human carbon outputs as: a time-based downscaling a person’s average annual footprint to the one hour of writing a page of text is not appropriate, as this footprint includes … things that are clearly not attributable to the writing and painting processIn other words its about as accurate as any ChatGPT generated student term paper. Weirdly when you read the UC Irvine article, and the notes at the end of the Arxiv PDF they express worry that they avoid any unintentional plagiarism as being much more of a concern than the accuracy of the content. The fakery around Hummer vs Prius was exactly this redrawing of all the boundaries of the analysis along lines that completely warp the figures. Pauliuk points out how bogus this is in the case of the “carbon of AI vs humans” paper.The Paper’s Data is DoubtfulSince the paper refers to random articles on Medium as authority for its data, I’m going to do the same: here’s an article that points out how the framing of the carbon calculations is wrong. It is based on figures from that medium article and calculated out from there: see all that “derived from above” then the Chris Pointon medium article link: The point of this is not that Pointon’s data is wrong: its just that OpenAI is not releasing any data about its carbon footprint. No-one knows what it is. And bogus math obtained by dividing the total carbon of the whole USA by the US population is not helping clarity.Don’t Use ChatGPT for Science - it Doesn’t Work* As above with McGrievy’s article, you cannot generate science with a large language model and expect it to hold up. The authors of the “carbon” paper say they edited it heavily, but they also say they regenerated a whole new draft. Basing all your data off a Medium article seems very ChatGPT to me.* Google is actually doing some proper LCA on Data Center resource usage: look there instead of dodgy ChatGPT generated papers. Their usage will not be very representative since their hardware is different to ChatGPT. They have their own TPUs and ChatGPT uses Microsoft Azure and AWS, so its likely a lot more.* If you want a good informal video explainer the ABC has a great video on how our individual prompts to generative are not a big user of water, but the data centres are contributing to water stress and are a problem.* The point of my article and my video rant above is that the astroturfers have arrived with their junk science generation toolkit and that in itself is a sign that we’ve turned a corner in the struggle to get AI vendor companies to be decent citizens of planet earth, be regulated sensibly for everyone’s safety.ConclusionBeware of junk science. Especially when its a distraction from the real issues. Arguments about how many bottles of water your prompt uses are a red herring. As I previously reported we don’t want new AI data centres stressing water and power delivery. And being drawn into fake arguments about fake science is just the playbook of the climate denialists being run again in the AI age. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit totallyathing.substack.com

Hey all, I’ve looked better and felt better! But after getting out of hospital I just wanted to show that I am on the mend, and will be back writing in the coming days.Hospital stays are not fun, and for 7 days involving rigors and being on a drip was awful. But I’m back, and getting healthy again.Also I have a qualification that I’ve been studying towards (to allow me to teach in Australia, in tech) and that has meant doing practical exams that also took up some of my very little energy. But now that is done for 2025 I now have time to write again!Thanks for reading Totally a Thing! This post is public so feel free to share it.But you are not here for my health! What on earth is Minister Ayres and the Aussie government doing with AI now?The Australian AI Roadmap* Reuters - “ramp up adoption, rely on existing laws”* The Guardian - no guardrails needed * ABC news on the roadmap - see images below:At the present time generative AI, of the sort that can rip off books, is a violation of the very concept of intellectual property; its a digital slave ship for desperate data-labelling workers (many in the developing world) and overall its a mechanism for wealth transfer. It’s an extractive process that rips-off regular folks, and transfers wealth to tech oligarchs, huge investment companies and corporations.It’s absolutely outrageous that the Australian government is stepping back from its responsibility to protect our local Aussie intellectual property from extractive AI companies. It’s unbelievable that public servants like Minister Ayers (who I mispronounced as Akers in the video, sorry) are so starry-eyed and delusional that they think “AI adoption” will somehow benefit Australians. It’s a massive breach of trust.When AI can be GoodI am pro technology, and pro computing solutions that help businesses and people. But it is not being a “luddite” or a “hater” to point out that huge over-heated startups running on investor money, stealing IP are doing it because they want to “win”; to become a “Google search” for AI, so that no-one goes elsewhere than them. They want a “moat” as they say, a monopoly. This idea is both really evil, and really stupid.The bad:* Big AI vendors trying to corner the market* Billion dollar corporations profiting from stolen IP* AI corporations addicting users, and corrupting government to get their way The good:* Regular companies using AI tech in house as part of a compute solution* Software engineers helping Aussie industry deal with Big Data via AI* Using AI (not just LLM/AI from a vendor) as a component of real solutionsWhat I see as the biggest problem here is companies in Australia hearing that the Government is supporting “AI” and then rushing out broken, failed “solutions” that just wrappers around US based big AI vendors products. * Agents do not work. They are garbage.* Software professionals are the only way to get compute solutions that work.Stop talking about “adopting AI” and start talking about building solutions - using the right tech for that, whatever it needs to be. Use AI for what it’s good at, for example indexing big data, and search. No-one has “cornered the market” on AI and they never should, and I doubt ever will. There’s no “AI race” to win. It’s nonsensical. Just look at DeepSeek.So many decision makers have been deluded into thinking “AI” is some kind of glowing blue plastic person - a self-deploying solution - that will walk through the door of their company ands start typing on their keyboards: So many lies from the AI industry; and I’m afraid the Minister here is swallowing it hook, line and sinker.AI Safety InstituteOne bright possibility is the creation of the “AI Safety Institute” which could be an NHTSA for AI. If there’s an accident and people are harmed you have a technically competent and responsive body, independent of industry who can step in to analyse what happened, what the harms are, and recommend any legal action needed.I am currently working on a series of articles about the mechanisms of AI regulation in AI vendor companies, and the analogy of an NHTSA for AI is one of the possible mechanisms that has promise. Stay tuned for that.The National Highway Traffic Safety Administration works in the USA when companies make unsafe cars. And the same model (a qualified body of technically competent responders and investigators) can work here and elsewhere to monitor unsafe AI.The AISI seems to have a reasonable charter at present, but my concern is that it could have the same fate as the Climate Commission in Australia which was set up by the Labour Government to monitor harms from polluting industries: it was destroyed for political gain by an opposition government looking to cosy up to industry. The outrage from the public when this happened, by the way, was so huge that public campaigns to keep it open resulted in the staff who left the commission starting the Climate Council to continue that work with crowd-funding.It would be so easy for the AISI to either become a channel for AI industry propaganda to go into the ears of politicians; and effectively become an industry group itself; or if its actually effective in protecting people that a subsequent government turns it into a political point scoring exercise.Theft of IP by AI has to be LegislatedAs I mentioned in my video legislation had to be added to the century old crimes act to specifically include electric power as a thing able to be stolen. This happens often with technology and we’ve been down this road before. It’s not radical to legislate to clarify what can be stolen, even when “the law already exists”:The idea that “existing laws cover this” are garbage because what happens is small creators get into court and face billion dollar AI companies hiring an army of “AI Experts” to say they did not steal the creators intellectual property.Of course they stole it. They took our books, our images, artworks and our online articles against the explicit terms that those are things over which we retain moral rights & copyright. Billion dollar US based companies encoded that into their AI models, stored in to data centres to be served up for their own profit.But decisions are going against creators because there is no legal clarity around what constitutes illegal copying, even though judges are making positive findings, it’s taking years for any justice. Mind you, in this linked case, I agree with the judge that the correct argument to make for harms and damages against AI companies is that they are flooding the market with competing AI slop products directly generated from the IP that they stole. The deceptive practices of AI companies trying to hide their crimes goes to intent — in the same way cigarette companies hid what they knew. But for copyright law you are stuck proving that your IP was taken and that you were harmed.Decisions sometimes go against authors and creators, and sometimes for them. It’s a mess, and law is necessary to fix this so its clear that:* AI encoding is not transformative, it is storage and it is illegal copying* Taking IP and encoding it is substantive & not some 0.001% as claimed.See my previous post on how this works:Vulnerable Folks and AIAI vendors are never going to do the right thing for at risk people unless regulation forces them to. OpenAI says millions of users are discussing suicide, but their response instead of hard interlocks to deal with this, is a “Wellness Council” and controls that push the problem back onto parents. Note that in my upcoming writing on AI regulation I want to cover the problem of “AI Alignment” which is the stupid approach of trying to get LLMs to behave via “system prompts” and fine tuning. We need symbolic/procedural computing solutions that allow no statistical hacks or failures: a “regex” or behaviour tree that can catch these sorts of conversations external to the LLM and route the person to get real help.If you or someone you know is vulnerable, please get real help:* Get mental health emergency help in Australia: Beyond Blue* Queensland Government list of mental health services* US based mental health helpReportage on AIFurther reading/listening I recommend:* Karl Brown, Internet of Bugs* Ed Zitron, Where’s your Ed At* Dr Luiza Jarovsky, AI Tech & Privacy* Prof Gary Marcus, Marcus on AI* Matt Bevan, If You’re Listening / ABCThanks and ConclusionThanks for reading, and for listening. Please do not sit back and write off what I’m saying as “passionate” or “ranting” as though dismissing what I’m saying as “AI Hate” just explains away what I am saying.I have over 20 years as a Software Engineer, for some of the biggest names in tech; and also in the startup space. What is happening in the AI space right now is a 5-alarm fire, and speaking up loudly is the only way we are going to get any action on it.Please help me in this.Totally a Thing is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit totallyathing.substack.com

Working through a series by Lesser Dog Tutorials on how to make a LucasArts style point and click adventure in Blueprints, I have instead of using Blueprints I have been translating everything into C++, and it’s so much fun.Totally a Thing is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.Feels like doing a crossword and a half-dozen other fun puzzles besides. Today’s solution found was uncovering how Unreal dispatches Interfaces when they’re implemented in C++, and overridden in a Blueprint, but called by C++.Turns out they have this — as far as I can tell, undocumented — feature where you call a static method on the interface implementing class that is generated by Unreal’s Header Tool (UHT) so: HotSpot::Execute_LookAt(CurrentHotSpot)That gets the job done, to have my little man read the poster response from the blue print via the Blueprint visually coded look at event.Blueprints are amazing, and have their place, but complex logic in blueprints gets into a snarl of spaghetti so quickly.Code is here:* GitHub - Unreal Adventure Game Don’t worry - I will get back to dishing on AI shills at some point in the near future. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit totallyathing.substack.com

I have been struggling to write this article, and figure out what to do with this cartoon / diagram I made about the alleged use of stolen books by AI companies for weeks now. The sheer scale and brazen bullying greed of these guys just astonishes me.I believe startups and technology have the ability for great good. But it’s being used to enrich the most powerful at the expense of the little guy.This diagram sums it up in one image. See my video for an explainer.ReferencesArticles I reference in the video:* The Atlantic, The Unbelievable Scale of AI’s Pirated-Books Problem* by Alex Reisner* Authors outraged to discover Meta used their pirated work to train its AI systems* by Nicola HeathThe analysis of how AI companies refuse to pay for data when they spend big on engineers and data centre costs was inspired by Ed Newton-Rex’s Ted Talk:What can We Do?The most important thing is we are not powerless. The number of daily users of the products these guys have is an instant stab of pain for them every time it dips. * ChatGPT - you don’t need it, delete your account* Facebook / Instagram - migrate to Bluesky, and SubstackCalling out everyone for using toxic AI products and just politely pointing out the harm — we could lose our book industry — is worth it.See my article from last week about pushing for regulation on AI companies.I’m loving the new campaign from Australian Society of Authors and other groups trying to throw light on these problems.Vote for fair AIThis year is an election in Australia, and there’s a chance to push for policies that support books, readership and our local bookshops.Don’t let them die. You’ll miss them when they are gone.Thanks for listening.Totally a Thing is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit totallyathing.substack.com

Engineers love to deal in absolutes. We are trained for it, when we study mathematics, electronics and disciplines like finite element analysis or software development at University. It seems to us like everything in the world can be reduced to ones-and-zeroes, true and false.Business is not like that. You have to prioritise. It is a constant balancing act. Every time you choose to execute on an initiative, there is an opportunity cost. The time you spent on those cool infrastructure as code scripts is time you did not spend delivering the incremental login feature that your customers needed.So how do you as a technical leader — say a CTO — explain or understand this balancing act, and make sure your startup or scale up survives? You can say:Never let the perfect be the enemy of the good enough.Or:The practical solution that shipped is better than the ideal solution that didn’t.The next level up the mastery tree is the deeper knowledge that these ideas are not about compromising. Those trite aphorisms leave engineers thinking they are being asked to lower quality to get a delivery out.Great technical leadership understands that Worse is Better actually means a “worse” solution is often a superior option. That’s what I hope to show in this article. The “compromising on quality” argument is a complete red-herring because quality is orthogonal to this issue of what a “worse” solution really means.Huh? Its not about quality? Well what does “worse” mean then?Can’t we just leave our engineers to do the “right thing” when it comes to building the tech that our startup business needs?In a business, especially a startup, if the time you are spending is gone in satisfying some engineering driven pursuit instead of a customer need you are soon dead in the water. Money burns away. It goes in no time flat when you’re paying engineers. At your startup do resource intensive technical tasks win out over business realities on a daily basis? There’s a risk that it becomes a culture and a glide path to failure.Do resource intensive technical tasks in your startup win out over business realities on a daily basis?Can a startup be fun for the makers? Sure. There’s exciting moments. Is it a chance to indulge technical ambitions? There’s chances for that. But I have run several startup businesses, and when you have staff that you have to pay it gets real. As a tech founder you write code during the week, and on the weekend you have to do payroll. People rely on their pay to make rent or mortgage payments, and to keep their kids in school.For those in technical leadership right now who may be scoffing and thinking “well, if you’re out of money then all bets are off — this has nothing to do with me” have another look at what technical decisions are costing. As a technical leader what could you do to reduce waste?As a startup your cash-burn rate, and ability to make payroll is what gives you a runway. That runway is a hard stop. If you are financially headed straight for the tarmac at a hundred-miles an hour it doesn’t help if your test code-coverage is 82%. Cash in the bank is hard number that you cannot argue with no matter how much you love functional programming or clean code.Cash in the bank is hard number that you cannot argue with no matter how much you love functional programming or clean code.So as technical leader how do you explain to your engineers this fact? The fact that when the bottom-of-the-barrel is reached they don’t get paid and the company has to shut its doors?Unless they’ve been through the experience of a startup or of a too-big-to-fail company failure — like RIM or the one I experienced at Nokia — they struggle to wrap their brain around that idea. Surely if I keep showing up at work, the tables and chairs are here, the coffee machine still works, I still get paid. Right?Strawmen of Worse is BetterEnter “Worse is Better”. Its a critical plank of Senior Engineering skill that you need to master in order to lead teams in a startup or innovative business. It can help explain to engineers how to get on board with balancing competing priorities.But it does not mean compromising your ethical principles. It does not mean accepting inferior quality. Folks who do not have a growth mindset want to avoid change, and may make these straw men arguments.Worse is better means: rejection of complexity, even when complexity is the more theoretically correct approach.Worse is better means: rejection of complexity, even when complexity is the more theoretically correct approach.But the moment my fellow engineers are asked to choose simplicity instead of some high-priest holy-notion of engineering they react as though it’s the end of the world.Some are even ready to slap their resignation on the table and walk out. Here’s some ideas that engineers I’ve met are ready to die for:* clean code* secure code* infrastructure as code* open source* test coverage* functional programming* css in code* css outside of codeAnd when I say “ready to die for” I mean it. They’ll shout and threaten to resign when 80% of the code base is open-source/test-covered/functional/clean/inside/outside and they’re asked to make a change to their code base making it only 70% of the previous figure.“It’s a slippery slope! I’ll resign!!” they say. Usually because whatever the issue is relates to some past war they fought, and they’re still nursing that pain from those days. When an idea that we hold dear is challenged and it’s shown there are cheaper, simpler ways that work just as well for customers it’s tough to deal with.These principles above like clean code, are important, but they are not absolutes. They are principles that inform decisions. We don’t get to throw the baby out with the bathwater. We don’t get to storm off because a pet engineering hobby-horse is not pandered to. The hubris of engineers can drive a company into bankruptcy and we need to understand the cost of standing on gold-plated principles.Survival Means Living to Make a DifferenceThere is a million ways to misinterpret and argue against “worse is better”. Most of the arguments against it that proliferate on the web mischaracterise what its framers intended. For the record the article by Jeff Attwood in his blog “Coding Horror” shows what I mean by the framers. Attwood along with Joel Spolsky founded Stack Overflow.The thing is that even if their straw-men arguments were true, taking a general approach of balancing engineering high-priesthood demands with what customers will pay for is the only thing that will make your startup survive. Embracing worse is better doesn’t mean throwing out engineering principles, it means feeding them into decision making.But by characterising it as a choice about quality, by creating a straw-man they can take their righteous indignation all the way to the tech graveyard. They get to die on their hill, and then once the business is shuttered they can go on to some new company. Attwood points to this quote: worse-is-better, even in its straw-man form, has better survivalcharacteristics than the-right-thing and it is spot on.worse-is-better, even in its strawman form, has better survival characteristics than the-right-thingSee the post by Jeff Attwood blog post quoted above. I hope I don’t need to point out how good survival is.Survival: that is the one where you don’t die. You make payroll and don’t have to close the company down, and tell everyone you employed that they are out of a job.A Concrete but Ethereal ExampleI’ve found through experience that once you try to get engineers to even question their cherished holy-notions long enough to notice that they’re driving the company into bankruptcy, you start an intellectual fight that is likely to lose people, without getting engineers to realise that even if they are technically right they’re in practical terms painfully wrong.So how do you get the message across? Let’s try technical examples.Here is where engineers can start reading and see how many examples there are in technology of the “glue two phones together” approach succeeding.Another example apart from the ones Attwood quotes, is Ethernet. Back in the day, LAN parties happened with blue cables you stretched from front to back in your share house. Before those blue cables — Ethernet — became so popular and empowering there was a thing called Token Ring.Never heard of it? Its a bit like folks today have not heard of Blackberry. Because it died. Engineers could not believe that a phone without buttons was better.Token Ring was technically better, as well. But Ethernet, which tolerates dropped frames, was “worse” and actually better.A local area network, one connected by a cheap network hub, echoes out every frame that is dropped onto it to every network card that is plugged into it. That’s the problem that the CSMA/CD algorithm solves: the collisions that you get when you drop a lot of frames onto the shared-medium (the wires).The algorithm CSMA/CD or Carrier-sense multiple access with collision detection handles the collisions. Basically it works like this: each network card can figure out from its segment that it collided, so it waits a random amount of time and tries again. The amount of time gets exponentially longer. That’s it in a nutshell.But isn’t “wait a bit” kind of a crappy solution? Lost data? Dropped frames? The folks who built Token Ring probably thought so. By using shielded cables and more high-end equipment, each network point could wait for a “token” (a special pattern of bits) to arrive, and once they possessed the token, then they could transmit, knowing there’d be no collision. A purer, more perfect solution with no collisions!But which one won?Ethernet. In fact the same algorithm powers 802.11x — the wireless internet that we use for everything we do today.There are countless examples of this kind of thing in engineering. But the ideas of purity, cleanliness and so on blind us to them.Great, so “Worse is Better” — what now?So you are a technical leader, maybe you write code and maybe you don’t, but you want to have your company survive. The key lesson is to listen for when an engineer driven work requirement is justified as a choice between two technical options, instead of a choice based on customer needs. Remember customers? Those are the folks who pay you.Listen for when an engineer driven work requirement is justified on technical grounds instead of customer utilityAn engineer driven requirement: this is one where folks are demanding something must be done because of an engineering reason, and there’s no projected customer benefit.“We have to have 100% code coverage! Otherwise quality suffers!”. But in fact with very high levels of coverage so much test code, dependency injection and abstraction takes over the code base, that it may be a bloated, unreadable behemoth where feature requests take months to complete, and customers still experience bugs.Is it because of security? Ok, what is the threat analysis? What is the attack vector? What is at stake? General principles are fine, but what are we actually gaining by encrypting the token for login to the loyalty database when its already in a secure app sandbox?Is it because of clean code? Or functional programming? Or developer experience? Fine — show me. What is the tangible benefit today of refactoring our code base to use the interactor pattern, and have five-million tiny useless classes that need to be touched to implement a tiny change in functionality?Other Tools in your Worse is Better ToolbeltYAGNI — you ain’t gonna need it.DTSTTCPW — do the simplest thing that could possibly workThese are other ways to avoid over-complicated solutions. But one of my absolute favourites is one attributed to Knuth.Readability — write programs computing machines can perform quickly and human beings can understand clearlyDid you ever have someone triumphantly produce an unreadable, opaque screed of code and then says its a brilliant solution to a made-up problem?I have to wonder if the problem really is that they want to make themselves indispensable.SummaryWatch for requirements entering your backlog of engineering work that have no projected customer benefit. They can be justified, they can be needed, but they should be “salami sliced” into other work, and made to show tangible benefits.Idealism — especially engineering perfectionism — is not a reason to spend resources in a startup. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit totallyathing.substack.com

Why?In my previous talks on how to build an app I’ve discussed source control briefly. Github, owned by Microsoft, is probably the most popular cloud service for source control. OK, but how does that help me?If your app based startup is going great, then your team will be implementing product features and code for that will be going into your source control system many times a day.But what about if something is going wrong? How can you check up on that? Do you wait for your engineering team to tell you? I’ve talked about the problems a startup can have, especially in that first app building phase, and especially if there’s poor engagement between the founders and the team:* My developer left me / Get the Code* How Does my App Work as a Business / Code Repo: Core to Automation* How to Build an App / Backlog, Doing Done I’ve done to death the “Why” of being a founder who understands how to find the code. In this session I am going to look at the “What” and then the “How”.If my business was a sandwich bar or a t-shirt printer I could go down to the kitchen or down to the factory floor.But if source control is a mystery you need to take some time out to decode that, because it's the one thing that keeps your business running. WhatIn the next 10 minutes I’m going to show you what source control might look like, and give you an idea of how it works. Finally I’ll wrap up with a short list of next steps to give you as an appreneur to get ongoing insight into your project so you can work with your team collaboratively.As a bonus, if you’re an engineer you’ll see the way I work with Git on the command line and you will likely discover something new. For non-tech Appreneurs trying to get a handle on source control can be tricky. Think of the difference between a document on your local computer or phone, like say a PDF you downloaded; and an email. You know where that PDF is, it's in your Downloads folder. Now compare that with your emails that you read on your phone or computer. Where are those exactly?A code repository is a bit more like that. In the cloud, synced locally. Kind of.But another big difference, and it's what I’m focussing on in this session, is a code repository for your project is built in small steps. And source control is designed with that in mind.Demo of GitFirst we’re going to look at a couple of projects from the Engineer perspective and you’re going to see how I would explore code, download it, make changes to it and then update those changes to our cloud - to the Github repository.Let’s look at a project I started some years ago. This is an app written in C++ that runs on Mac, Windows and Linux. It’s stored in a source control repository, and then pulled down locally. That project is private, and only accessible if logged on and allowed access.Another project of mine is open source and is publicly available for view. # Pull down the project from github git clone [email protected]:sarah-j-smith/chestnuts.git cd chestnuts/coins/ g++ -std=c++17 -stdlib=libc++ -I ./include -I ../include \ -Wall -O coins.cpp -o coins ./coins < test.txt cat test.txt  g++ -std=c++17 -stdlib=libc++ -DPRINT_TABLE=1 -I ./include \ -I ../include -Wall -O coins.cpp -o coins ./coins < test.txt # Make some changes vim coins.cpp ../README.md  # Add those to git and push git add -i git commit -S -m "Improve docs" git push git show –show-signature Signed Commits* https://docs.github.com/en/authentication/managing-commit-signature-verification/signing-commitsAs an engineer I can sign my commits so that you know they are done by me. This is an added layer of security and it's worth doing to ensure that code is being modified by who you think it is.What if you had a disgruntled employee – call them Joe – who left and decided to put a back door in your code? As long as Joe doesn’t have access to the local GPG keys that your existing engineers have on their computers you can see that all any changes are by legitimate folks with access to the code.It’s possible to have Github reject unsigned changes but that’s not something I have seen on any repo, and I would not recommend it.The Git LogGit never forgets. At least you have to do a lot of work to make it forget, which for all practical purposes is the same. In this article I go through what is required to make Git forget and its a nuclear option - generally you never do this.* Make Git ForgetThe How* Make sure you have your own account * on Github, Bitbucket or whatever system is being used for source control.* NOT the user name and password of someone else's account or of a jointly used generic account. * As founder and one of the owners of the company get admin rights to the repo* You will use this access very wisely, very carefully* It's generally not easy to inadvertently change anything on Github.* If you need to appoint someone new to work on the repository you need to have the power to do that, if key personnel leave.* This is really important: if you get some other account and have the password, it can easily be deleted by that other person who has access to it, or the admin rights revoked. Imagine - some people have left the company and you go to use the username and password to get your project back on the road again, only to find it was owned by someone else. And now it's gone.* Regularly, ideally after a release or a sprint cycle.* Log on to github and navigate to the list of commits. If your team is using PR’s then check those too.* Look for the following:* Commit messages - should be descriptive* Commits / PR’s should be small* Names of files that are edited* Signed commits* For extra credit:* Documentation* Function names* Signs of 3rd party or cut-n-pasted code* What dependencies are introduced?* The goal is to better understand the pressures and work load of your engineering team. If you are an engineer yourself then reviewing the code others are writing is important.* You don’t need to introduce PR’s and slow down development to have code review, just read code together* Ask:* From the commit messages and files touched is it clear what the change is doing? Is this change improving the product and moving forward the goals of the team and the product?* Are there signs of technical debt being introduced - for example is code being commented out, instead of deleted? Is the word “temporary fix” and “hack” being over-used to apologise for code. You can ask the engineers to explain what they meant in a non-blaming way.* Are there signs of churn or spats between developers being fought out in the code base - changes done and then undone.Totally a Thing is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit totallyathing.substack.com

Google’s AI Preview is driving me insane!I just want web pages!Instead when I type a search, what happens? It thinks for a moment or two, then produces this bargain basement guess, summarised from whatever blended together soup of opinions it found on the web.I don’t want that! I never asked for that!!When I’m researching for my writing I need the actual facts. Many topics are highly dependent on the source.Google, why do you grind off the serial numbers and sell me this crappy, high-school student answer?Who ever asked for this?Searching for a FixWell, I finally got annoyed enough to go looking for a fix. Seems like plenty of other folks are like me. Tom’s Hardware has an article about a Chrome Plugin called Bye, Bye Google AI. It also lists one called Hide Google AI Overview. That second one sounds more technically accurate, as far as the name goes - but I like Bye Bye Google AI better. But I’m not going to install either of them, because although I use Chrome for development - that is testing my code - I use Safari on my Mac when I’m researching. I use Safari a LotSafari blocks a lot of trackers and privacy invading cookies for me without having to install and keep up to date a bunch of plugins that might have security issues of their own.I enjoy making web developers stop being lazy and actually build their products properly so that they work with Safari as well as Chrome. Another great benefit of using Safari.Plus it’s also the same browser I have on my iPhone, and I like the synchronization.So here’s how I fixed my Google AI Preview problem. I just pressed command-comma to open the settings panel, and then, changed the search engine to Duck-Duck-Go.So I’m being tongue in cheek here. I fixed the problem by getting rid of Google. But seriously - isn’t it time?Totally a Thing is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit totallyathing.substack.com

This is a free preview of a paid episode. To hear more, visit totallyathing.substack.comThere’s some really great apps in the App Store and Google play store!When I was consulting, building apps for people in business, they’d show me Augmented Reality apps like Pokemon Go, or the Uber app with its live location tracking and ask “Can I get an app like that for my business?”

Welcome to the second post in my series on team dynamics. Last time I talked about communication and how it’s the best bang for your buck when it comes to solving issues that crop up in your app based start up. I talked about how teams at any given time have a set level of competency which is not quickly changed. And I went on to cover how trying to motivate your team with pep talks, or worse brow beating doesn’t get to the root of actual problems.In the previous lecture, I presented the triangle model showing that motivation and competence have a role to play in the throughput of the team, but it’s communication that is the base of that triangle, and it often winds up being the limiting factor.So motivation and competence are important, when managed at the right time. It's just that when an issue arises is usually the wrong time.An Anti-Pattern in Team DynamicsIn this session, I want to look at an anti-pattern. This is a tech team dynamics misstep that  nearly always will derail high-performance teams on a project.When someone new has leadership responsibilities in an app start up team at the start they wind up flying by the seat of their pants. I don’t want to discount the importance of being authentic or of going with the gut.But it’s good to train those instincts. Get ahead of the game by learning effective strategies for communication so that when the pressure is on, we find ourselves responding in a solution focused way.The Flaming LimousineImagine you are riding down the highway in the back-seat of a luxury limousine. But it seems out of control, it’s slamming into the guard rails and flames are pouring out from under the hood. So you call out:“Hey, it’s on fire!”But instead of listening to what you’re saying, the driver says:“What’s your problem! You’re in a luxury limousine!”You say “Watch out, we’re slamming into the guard rails!”But the driver says: “Stop complaining and have another drink from the mini bar.”As a team member, you know your team has become a flaming limousine when your accurate observations about actionable issues are written off by referring to company perks, or workplace culture. When is it a Flaming Limousine?Remember the celebration we just had for the last milestone - I can’t believe you’re complaining already.We are a huge supporter of that idea here at Company X - what’s your problem? In a flaming limousine team serious concerns are - by implication - dismissed as being self-serving complaints. Signals from the team about important information are missed, and the project is impacted by risks that could have been avoided.For a new app startup, it's difficult to manage input from the team when it challenges traditional lines of communication. It's even more difficult for folks new to leadership, or at least new to app startup decision making, when problems are pointed out at a time the team is not ready or not resourced to deal with them.What to do Instead?So how do you manage this input effectively?Do you treat the information as a brush fire that you need to hose down, or as a challenge to team structures that need to be realigned?Those are flaming limousine responses. Do you have more beer on Friday night, and buy your team a foosball table or basketball hoop? Sure it's nice to do those things, but it’s not addressing the burning issue the team member is raising. Do those things to celebrate real fixes.The most important skills to avoid becoming a flaming limousine are active listening, note taking, team dynamics and prioritisation.Active ListeningFirst employ active listening to make sure you reflect back to the team members with the information what you are hearing. Always do this, even if you feel it risks derailing the current team ritual, meeting or cadence.When listening, make sure that everyone in the team who wants to speak is heard without anyone interrupting. That includes you.However they must be succinct. And once someone has spoken, the chance to speak moves on. When employing active listening to reflect back what you have heard, as a leader, summarise fairly, get in their shoes, and try to understand what they are saying the stakes are. Why is it important? What is the priority?Note-takingAll this can be done quickly. It does not need to derail the current meeting. Use your notetaking to ensure you capture what you understand. If this current meeting or ritual is the correct place for the issue to be resolved, then do that right away. Otherwise, you can ask the person who bought the issue up to create a meeting at the earliest opportunity that matches the priority. The person should also check in with the participants in a written form, prior to the new meeting with a 1-pager on the background.Team DynamicsSometimes drawing up the 1-pager helps resolve the issue before the meeting takes place. In fact a useful approach here is to have the person calendarise the meeting, but if the matter can be resolved before then, the meeting can be called off. However the meeting date serves as a forcing factor to ensure it's dealt with - and your team will build trust that you’re actioning the issue.If the team members respect each other’s contribution that approach should avoid the issue derailing the current meeting. In a later session I plan to cover respecting team members' knowledge.But if it's necessary - maybe canceling the current meeting and dealing with the issue straight away is the right thing to do.Prioritisation A very useful document to deal with the kinds of issues I’m talking about here is RAIDS - the risks, assumptions, issues and dependencies log. This is usually a wiki page for the project, where emerging problems can be tracked, and all the team members can see what resolutions were. Each line item should show a short normative name, description, date, who it was raised by, and what the final resolution was. If a line item in the RAIDS document is too complex to be properly described, create a Solutions Options document, or a High Level Design document, and link to it from the RAIDS line item.Whatever is actually done with issues raised by the team members, the vital first step is listening in the appropriate way, and capturing enough information to determine the priority. Then you can take steps to make the right forum, and right time to handle it correctly. Sometimes listening and recording is enough. Especially when you have the trust of the team.TLDRBut whatever you do, avoid falling into the trap of thinking team members' concerns are just a complaint to be dismissed. Company culture or office perks are not a replacement for ethical behaviour, and sound team dynamics. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit totallyathing.substack.com

This is the fifth post in my series how to build an app. We’ve already covered how to get your team together, shape up a product and build an app. But when that app and our team is working together as a business what does it look like?Milestone Release. Are We Done?When the team has been pushing for a milestone, and it comes to release, there's pressure to ramp up marketing and cut development costs.In an app startup development costs, engineering costs in particular are one of the biggest. But the capability of the engineering operation is the thing that lets the business move forward.The business cannot operate, make any changes to the product without engineers. So what is it that the engineering team does?When developers write their code, as I mentioned in earlier posts they work to create an app package which can be installed on the device — the iPhone or android phone. That package can also be uploaded to the App Store or Google play store.Code Repo: Core to AutomationIn reality the process is a little bit different from that. Yes, developers can write code locally, and then push it straight to the stores.For a release however, usually the cloud store where the code is placed — that’s our repo — is configured to automatically generate the package. It can be even configured to automatically push the package into the App Store and Google Play store.Actually its more accurate to say its a special cloud-based app, called a Continuous Integration system (CI system)that automatically tests the code, then generates the app from the repo. But it is the repo typically that holds all the code for the build, contains the versioning details, and nowadays even holds the scripts for the CI system.So to keep it simple think of your repo as not just a store for you apps code, but also the core of your app building process cycle.Like a Version?What’s even more interesting about the repo is that it’s not just a collection of all of the code that your developers have written for you. The repo is versioned. I alluded to this already in the previous section. Its these new version numbers that play a critical role in making frequent app releases.What this versioning means is that if something breaks in your app the repo can be cranked back to a previous version. One that we know worked okay.Repository Data lives in the CloudIf you hear names like “GitHub” and “BitBucket”, that is your repo they’re talking about. You want to make sure you have the passwords or keys to access it & administer it.Second we have the App Store & Google play store where packages are pushed to. And that’s in the cloud too. You need passwords to access those too.Repository: Holds code, versions it, secures it, and drives releasing an app to the stores. Make sure you have passwords to it.What you can take from this is the general idea that several cloud-based systems are all working together, like a well-oiled machine, to process the the code and other outputs from the people in your app development team.That system culminates in the App Store and Google Play store, but it starts with your cloud based code repo.So when you think about what you get if someone builds you an app, it’s the keys to that repo that you want. It’s the goose that lays the golden eggs. Or at least lays the new updated versions of your app that you’re going to want down the track.What Happens with Updates?Now, once your customers download a new version of your app, they can open it up and the app and connect to cloud services to access additional functionality. We discussed this briefly in the previous posts on How Apps Work.Let’s have a really good think about app updates (made by your development team); and about updates to the items that appear in your app (like services or menu items, or clothes for sale).A customer may access a product for sale inside of your app, and complete a transaction to order that product to be delivered.For this to work the app will probably need to contact a store API to check that there is sufficient inventory of the product to fulfil the order, collect the customers details, and then connect the customer to a banking API provided by your e-commerce solution.So that is in a for-instance internet store app:* Your online storefront (a web-app)* Product fulfilment (drop-shipping or inventory)* Banking or e-commerce (PayPal or Stripe)* CRM system for customers details (Zoho or Hubspot)What if one of these four change? You release a new app version right?But unlike the web, your apps update when a new version is released to the App Store and installed by your customers. So you need for the old and the new version to work with all of the above services.You’ll have customers out there with the old version of the app. Maybe for quite some time. They may just choose not to update. You at least need to not crash the app, and display some useful message like “Please update”.Cloud or In-App?Let’s say you manage digital for a small food chain. You have maybe a dozen restaurants in the country. And let’s say you update your menu.You as a business app product owner may access your web-app, and update your restaurant menu in response to recent changes. Then submit those changes so the new menu goes live.So where does the menu live? Cloud, or in-app?If its in the cloud only — say via a hybrid app web-view, then customers who don’t have internet at the time they check your app cannot see the menu.But if its on the phone only it makes your app downloads bigger, and you need to make an app update, just to change your menu.In reality a good design might be to have it in the cloud, with a local cache, and a default that is installed with the app. So it’s in both places.Stock in TradeIn your business what is providing value might be physical things you’re selling as items. Or it might be posts and reviews to your pet-minding or childcare app. Whatever they are, these items are your business to care about, if your customer is to succeed and lead to your app success.What does all this mean from the point of view of your business?It means that you really need to think about items that are going to appear in your app. Think about those items as part of a task it’s going to be completed by your customer — like viewing a menu, or a review.And when you think about it, decide which details of the items have to be in the code and be shipped as part of the app. That details will be shipped to every single phone that has the app installed.Also think which other parts will need to be live in the cloud and will need to be connected to and updated when the app is actually used.Often the best way to visualise this is with detailed User Experience flows.Alternatively there might be best practice for the stores or back-end API’s that you are using. So you might use a dedicated review site API. Either way you’ll need to think about where the information about those items is stored.Viewing and Updating: Two Different Customer TasksThink about a case of products that are ordered in an app. In this example case only the cloud that the phone app connected to knew about the details of the products. But the app needs to know how to display them once it gets from the cloud the list of products that were available.One pattern I have implemented for an app with In-App Purchases is to have 7 items that comprise the purchasable products. These 7 items are coded into the app, along with a name, description, category, price and photo. The app knows how to display all of these things in either a detail view for the item, or in a list of all items.Let’s imagine one item is not available.The picture changes if the app allows updates — that is the customer could review or purchase an item. Here we need to be careful.To check that we’re OK to display an item, our app can connect to the fulfilment centre and update the inventory amount, find that the item is out of stock, or off the menu, and update the view, so only 6 items appear in the store view.This way you have a double-entry approach to the items in the app. The app knows about base items, and how to display them.But that model is updated from the cloud, when the customer interacts with the app.Summary* Understand the role code plays in building your app.* Apps can be updated automatically from the repo* The repo is part of the capability of your team* Make sure all code goes in the repo every day* especially if there's any remote teams* Design and plan which data* are coded into the app, and* which are dynamically fetched from cloud Apis.* some data can be both* Complex use-cases like user roles need design & testing* Map out complexity and make it part of acceptance tests* Complex and risky items should be done as early as possible* Test no-network and other edge cases This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit totallyathing.substack.com

Imagine the throughput of your team is defined by this triangle - in this model the sides remain in constant proportion.Once you have hired someone competence is fixed. Lets assume you have a team and you want to make the best of them.Motivation - the mistake some leaders make is thinking what they have to do to get their team producing output is to crank up the motivation. Introduce crunch time, do pep talks.But in my experience its the communication which winds up being the restricting factor MOST often. If you improve communication then you will begin to reach the potential of the motivated competent team.The job of a leader is to:* filter outside impacts that can derail the team, * simplify the view they have of the overall product and * provide a compass set on true north. * Provide a consistent drum-beat that gives the project a cadence. Technical projects have failures most often from a lack of shared understanding. The best bang for your buck as a project lead, for improving team performance, is time spent on communication. If there is an issue, seek information, understand why things went wrong, and open up communication lines with your team. Hiring 10 x engineers does not work. Pep-talks and brow-beating doesn’t get to the root of the problem. In this model, the throughput — the performance — of the team is limited by the smallest of the three sides, so communication more often than not is the low hanging fruit. Try that first because a fix to a hiring problem could be a long way off. Issues with motivation — if real — aren’t going to get fixed with fire-and-brimstone speeches.Ask open ended questions, and guide your team to the solutions & work with them so you can discover the facts, and the actions that led to the issue. Look at onboarding procedures, how work is managed and how UX specifications are updated over time. Hunt down the miscommunication bug-bears and work with the team to slay them.Improving communication will provide a team with good motivation and competent members with the best chance of performing well. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit totallyathing.substack.com

In this episode the rubber hits the road and our app is being put to the test. Will it succeed or fail? To get to this point an appreneur — either an app-based startup, or an existing business creating an app — should already have things sorted, as laid out in previous episodes:* Business plan with fixed and growing costs, unique value and revenue* Product tested by selling value via a duct-taped together MVP * A basic understanding of what apps are, the risks and how to avoid themMoney is one measure of success. Think about what success means for you. I’ll assume at least you want folks using the app, right?Let’s jump right in.Start with your customers. What do they want to do?Working with your UX designer, and your product owner, answer this question: what are my customers trying to achieve?How your app succeeds starts with Jobs to be Done:Jay, an office worker, wants to eat healthier & searches for meal plansHere wants to eat healthier might be unrelated to your business about recipe sharing with online ordering, but let’s say your app can help Jay search for meal plans and has filtering for healthy options. The search is a task in your app, that helps toward a goal.I saw founders struggling with apps because they have a lot of functionality that they want to put in — especially if they have a website full of stuff — once they start building an app the first thing they want to do is cram all of that in. Shoehorn their website into the mobile user experience. Successful apps are the ones that work for what customers want to do. Successful apps are the ones that work for what customers want to do. They don’t want AI, they don’t want 256bit encryption, they don’t want a laundry list of obscure features. They want easy meals they can eat. They want to find a nanny they can trust. The Jobs to be Done framework and also Persona creation will help a Product Owner home in on this. Monetisation in AppsIn the initial App Store gold rush in 2010 onward, we got what I’m going to call “Classic Apps”, like Instagram & the app then known as Twitter. Instagram happened because we all have a camera in our pocket now. Twitter was invented because we were OK with texting on our phone. They’re known as phone apps, but have web presences as well.Note: when I say “inside the app” or “on the phone” remember apps these days are part of the fabric of the internet. I mean the whole app platform.We are also familiar with mobile games like Candy Crush, or apps such as Duolingo that teaches you languages. Here the value that lures the folks to the platform is some in-app offering — like learning a language, or playing a game.Often these kinds of apps have known, logged in users who see advertisements that the platform shows to them. These users are valuable to advertisers.Free to Play AppsWhat’s common to these apps is they make money because the actual app itself has some value that it delivers to its users — learn a language, share a photo.Free apps generate revenue from the app directly. They survive by acquiring a wide funnel of incoming users, retaining and monetising them.The critical strategy for this kind of free app — and I include freemium here — is to have a wide funnel of incoming users, who go through the classic cycle of acquisition, retention and monetisation. It’s very common to have the customers pay for that value by ingesting advertisements. Other possibilities are subscriptions with a free month, which have become hugely popular, and in-app economies, like Trello Gold or Gems.Premium AppsIn some classic apps customers can upgrade from the free to the premium version by completing an in-app purchase, or by buying the premium app in the App Store.The reality is that app pricing is a race to the bottom, with everyone searching for “free” solutions for almost every niche. That free-to-play funnel keeps gobbling up all the customers and making it hard to break in with a premium app.It is possible with an excellent app, to win via App Store listings and positive reviews. Procreate — an app for digital art with the Apple Pencil — is a good example of a premium app that is successful.Monetisation outside of AppsApps also can make money indirectly, by speeding up, enabling and making more ubiquitous the every day actions involved in business. Apps like Uber, AirBnb and Airtasker enable us to pay for services like transport or a home handyman. We think of AirBnb as an app but these are business transactions using an app as a channel.The local government, the tax office, post office and big corporations like Facebook and Google often have apps to help folks engage with various parts of the business. Smaller businesses often use web apps to manage restaurant menus, online stores and appointment bookings. What all these apps have in common, where the folks interact directly or indirectly with the business, is that tasks are at the core of success for these apps.Success flows if Tasks are CompletedLet’s imagine your business has a special promotion for summer or winter or some new seasonal holiday, and you send out promo codes to your customers to take advantage of the offer. A task would be for a customer to take that code, shop on your app, and apply the code to their account.The most important thing with tasks is that even if a customer can get almost all the way through the task, if they can’t complete it then you don’t make that sale. It might not be a literal sale, but it’s some interaction where the customer receives value, and engages with your business.During the app development process, each iteration, the product owner is checking tasks can be completed inside of the app. If a feature is built by the engineers, that is verified by trying it out in the app.Rule Number One for App MonetisationSo here is the first rule for making money from your app: identify the top 3 tasks that you want customers to engage with through your app; then absolutely nail the user experience for those tasks. Ensure that throughout the life of the app those tasks are constantly tested end to end to make sure they work.Payments inside your app require ensuring trust. Customers will be looking for the hallmarks that let them know their money is safe, and what they are paying for will be received. To ensure that tasks are working, conduct acceptance testing prior to your release where each step of the end to end task is tested on a phone.In the case of in-app purchases (IAP’S) the Apple App Store has its own APIs for these which can make these transactions very secure. Likewise Google has its own commerce APIs. Both of these require custom native programming in the app to work.Apple in particular is a stickler for getting these right. If a customer buys something in your app which they get to keep — for example upgrading to a premium version in the app, then you must provide for restoring that purchase if the app is reinstalled.Both Google & Apple take a proportion of proceeds, but in return will handle a lot of customer issues such as chargebacks and paying in different currencies. Otherwise you can use a payments provider API.Retention RulesThe second rule for making money with your app is stickiness. You need to keep your customers in your app. You need to think from their point of view.On your app website you should have carefully crafted open in app linkage so that customers can continue their transactions from the website into the app. Folks who have downloaded your app should feel like they are special, and that they have special insight, or privileged access to your business. If your business has Street premises, then there should be prominent signage asking folks who have the app installed to use it to get special discounts, jump queues or gain other benefits.Marketing promotions that utilise email should open automatically in the app if possible and include special promotional incentives to get app owners users to click through.Careful use of mobile notifications is a great way to have users return to the app. You need to make sure that the notifications have been asked for specifically by the user, for example “notify me when an out of stock item comes back into stock”. When a user gets a notification it should be seamless for them to click through into the app and continue their task as cued by the message.Growth can mean more Service Staff located where Customers AreBoots on the ground is when people have to be in the same location as the customer to assist them in getting the value from the business.Uber has to employ people to on-board new drivers, handle online complaints, and deal with logistical issues. Those people have to at least be in the same time zone and very often in the same geographical location. For AirBnb it’s the same. There is very often a need for support folks who speak the same language as the users involved in any complaint or issue.A Real-life Story of App EntrepreneursOne group of entrepreneurs I worked with during my start-up years came up with an app that involved trades people taking photographs.The idea was that this would help the trades people show work had been completed in a trustworthy & high-quality way. The app was successfully built, but my entrepreneur friends found that the trades people did not want to start working with the it. They had several trades people download the app, but they had to go and visit them and show them how to use the app.My entrepreneur friends underestimated how much cost in boots on the ground was required to get the app working.They may need to be tutorials online, support staff, or people working with them in person to get started with the app. An app that’s been in the store for 18 months plus, all the kinks have been worked out and it has a user base. People know how to use the app because their friends use it.The Gold Rush is OverThese days there are thousands and thousands of apps being submitted every single day to the app stores. This can work to your advantage as it allows a “soft launch”. This is a small launch to a niche set of customers. You can manually approach your customers and place the app in their hands, just like my entrepreneur friends had to with their trades persons. Or use pull up banners in a local city and hand out cards.The soft launch process will allow your customers to experience your app, and you can witness that happen firsthand, recording any fixes that you immediately realise you need to make. Remember: simple apps with well chosen feature sets are the most successful money making apps. Totally a Thing is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.TL;DR* There are a couple of different kinds of apps:* ones that direct make money inside the app* through in-app purchases, adverts, subscriptions or* up-front “premium” in the App Store or Google play store;* and commerce apps that help customers engage with a business.* There are a few different models for monetization:* Apps that directly make money include free apps; which rely on a funnel and a conversion process.* Premium apps (pay once up front) are still a thing, but hard to make bank.* Apps that engage with an existing organisation or business at least have a pre-existing customer relationship to leverage.* App Economics* Premium, Free-to-play* Acquisition, Retention, Monetisation * To make money from your app* Trust must increase* Ensure that customers can complete the tasks in the app* Have your product owner and UX designer working* to nail these task based designs.* Avoid dumping a ton of features from your website.* Choose 3 tasks, nail them* Do acceptance testing on an actual phone* check that your customers will be able to achieve those tasks.Understand boots on the ground.* Know how you will support your app when you release it.* Release via a soft launch to a curated group of customers * Get rid of friction points that block customer interaction This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit totallyathing.substack.com

This is a free preview of a paid episode. To hear more, visit totallyathing.substack.comIn part 1 I looked at the Product Owner and UX Designer. I’m going to jump straight in to the next specialist in the team — the engineering manager. Related roles are team lead, project manager or scrum master. Their job is to resolve problems that may stand in the way of the success of their developers, UX designer and product owner. This person is an …

This is a tie-in for my series on How to Build an App. Please checkout the other posts in that series, but especially the one on App Startup Canvas.Use the App Startup canvas to define the ground zero for your app development efforts: your team, your expertise, your plan to get revenue that will offset costs.Listen to the above to understand some important takeaways:* Your app is at the end of the day a channel - its part of a business* Vanity metrics don’t beat customers - the ones that pay moneyPlease also checkout the episodes in the series How to Build an App, or at bare minimum this one on Product Owners and UX Design.The Pattern that RepeatsWhen I was building apps for folks in the startup co-working spaces where I sited my engineering consulting business Smithsoft I saw a pattern repeat over and over.* I have a great idea for an app* Here’s a pile of money to build it* When the app is finished * We’ll make so much moneyWhat happens? What goes wrong?The folks involved in the app business are working in their day job, maybe they mortgage their house, get a loan or have mom-and-pop investors; but they phone up the app development house that they found on the internet and after months and months when they see the first iterations of the app they get increasingly upset when it doesn’t meet their expectations.Then they either crash or die.Die means they never get something they can take to their planned launch, which honestly might be less heart-breaking for them. They write off the money they spent, and go back to their day jobs, but with all their savings or investment burned.Crash means they put the app out there, and spend more money on marketing, only to find no-one downloads the app, their ideas about what people wanted were not strong enough for anyone to use the app let alone generate revenue from it. Then they are not only in the situation of savings or investment burned, but also massively in debt.What it Looks LikeA startup is a business founded to handle extreme uncertainty. It can also be a “high-growth” startup, which makes it an investment target, but it doesn’t have to be. And I’d advise against it. As I discuss below, customer money is better than investor money.The founders get together with their marketing effort and plan out when the app is going to launch. They pin all their hopes on a big marketing splash, with a set of features that they have asked the overseas app development team to build.It looks like this in their mind:At the bottom left of this — imagine its a chart with each position being some combination of feature — we have our team jumping on board and digging in for the journey to launch day.Toward the top right — so the plan goes — actual paying customers will see the list of features in the App Store, after being led there via a marketing campaign, and will download the app and create revenue.What Actually HappensStartup means uncertainty. Let’s imagine a company that doesn’t instantly crash and burn, and has some insights enough to get analytics or market research back about how customers are perceiving the app. They head out with some stake money, and a plan to get to actual paying customers.You’ll also hear the term product-market-fit or PMF. I prefer the term “paying customers” because an acronym like that rapidly degrades and loses all meaning, just like “minimal viable product” or MVP does. I advise against using PMF - focus on customers.So what actually happens looks more like this:* The first course charted is off the mark (unbeknownst to the team) and it seems the app build is not approaching what customers want. Product-market fit is off.* An investor surfaces, off the starboard bow, and one of the team says “we should hear they have to say” — next minute you change direction chasing money that never appears. Customer money is real, investor promises are not.* The team course corrects, and is on track toward paying customers when the build runs into regulatory, legal or standards issues that they ought to have forseen but didn’t.* They’re closer to PMF, but one of the team says AI is everything these days and they need to up their game. They work to cram in some AI features, even though none of the customers asked for this. It’s at this point that the stake money runs out and you are high and dry. Limp back to port and sell you ship for scrap. If you’re lucky.This is FineNo, no it’s not.But we are working our way to product-market… I mean on our way toward paying customers, right?Yes, but at what cost? This is what it looks inside the engine room and wheelhouse.* The view from the Product Team is limited. They have their feet in the product space and it’s hard to navigate. But they do their best to chart that course.* Down in the engineering space they are driving forward, but every turn of the screws costs money. Every day that goes past cash burn is eating your chances of success because once the fuel is gone, you’re done. Here again, is my recent session on Design and Product. These are how to sharpen your team structure so that you have the best eyes up in the wheelhouse.You will not get investment if you cannot show customers. And if you have customers you don’t need investment. The first time you get customer money — real customers, not someone’s Dad, or that company you used to work for — it will change everything about your app startup plan.Some folks do break my rule here and manage to persuade investors — angels, or sharks — to invest. Fine. I was there with my startup. We got investor money. It’s seductive because you think you have time, and can build something and find customers later. Wrong.Now you are back working for someone again, because that investor has a lot of control. They can tell you where and when to site your team, what to build and how to market. If it all goes sour, or no customers turn up you still wind up out of pocket, but with a reputation hit, maybe family impacts, health impacts as well. How to Escape from this Death SpiralListen carefully to the messages I have in my presentations. I don’t do this stuff to exercise my jaw. I’m not a “thought leader” or an “influencer” - I’m an engineer. I’m one of the very expensive pieces of the puzzle for getting apps built, and I’ve seen folks follow this pattern over and over. WRONG: I have a great idea for an appIdeas are like a*holes - everyone’s got one. Until you make a business plan out of it, it’s worthless.* Don’t use bad proxies for truth. * Not: How good it feels, what friends say, what’s trending* Vanity metrics such as likes or engagement* Use metrics that include revenue from customers* In return for actual value that you can explain in a secondMaybe you’re used to fake it until you make it and don’t be a naysayer type messages from every internet based scheme. Look for and listen to good business advice, not glamorous influencers. Step one is to complete the App Startup Canvas, and make sure you have a business model. Start with the Gaddie Pitch, but don’t stop there. Fill out with your team how you are going to get revenue from customers.WRONG: Here’s a pile of money to build itIf you throw the app build over the fence to some developer team, your app is guaranteed to fail. If you throw the app build over the fence … your app is guaranteed to fail. Because you have no idea where those paying customers are on that feature sea, you cannot succeed unless you are on board. That means being embedded daily in the process. Take on the role of Product Owner, research what that fully means. Or get involved in the other capacities if you have those skills. But all of you on the founder team needs to be acting as checks and balances. No outsourcing decisions, no leaving important planning to one team member.WRONG: When the app is finished In that 👆I talk about how apps are not “done”. An app is not a garden shed. The wonky course that I show above, is what happens to every app development process. It shows that you — even the best team in the world — does not know what your app is going to be.Iterating towards it with care, avoiding high cash burn mistakes, is the only way to find those paying customer sweet spots.WRONG: We’ll make so much moneyThere was an episode of an old TV show “Married with Children” where Peg Bundy decides to go into business selling makeup. But she buys all her own stock and revenue is a fraction of the $637 she has to pay. Peg says “I’m getting all these checks!” - and it’s easy to be seduced by concierged money. Now it’s true that a startup business is uncertainty. You need to spend money to make money sometimes. Read this article by investor Paul Graham:* https://www.paulgraham.com/ds.htmlHowever a business doesn’t last long like that before it sinks below the waves. If the founders are doing unsustainable things like going to shopping centres, or door-to-door then all they’re burning is their energy and time.Burning that supply in the engine room of your ship as you blissfully power ahead based on guesswork — that is unsustainable in a bad way. It might involve going to bricks and mortar stores with pull-up banners and printed t-shirts before the app is even working, then when you have a real app finally, actual customers want to rip it out of your hands because they know they want it.There’s two solutions I know of for this problem:* Sell the product and build customers before you create the app (recommended)* Have a very very large stake, and/or patient investors.You might need a runway of > 5 years. Atlassian needed about 10 years before it really began to pay its founders and EBITDA made sense.How to tell if someone is a customerIn the context of your app business:* A customer is someone who pays you. If someone likes your page, or kicks the tires of your product in your IRL store, or asks for you to put the app on a different platform than the one you’ve chosen: they are not a customer. Promises are cheap. Smile and say “thanks for your input” then move on.Escape “idea” death spiral traps - customer firstAs I said in the canvas video you need to get paying customers first, and then get the app working to be a channel for those transactions. I previously talked in my video canvas about Brian “inventing Facebook” - so start there. Apps are a channel. Get customers, then build the app for them.Look at AirBnb and other apps where customer money figured in the early stages. They sold breakfast cereals. They also scoured other platforms for listings and manually concierged their first sales with customers.If you have another type of app, the principle still applies. A chat app, mobile game or music player all needs to have customers before you build.An MVP is this:* The simplest thing that could possibly workIf they can do what you’re proposing with it (via a bit of manual help) then it’s an MVP. Do not use MVP as an excuse to build some huge complex finished app with a list of features, saying that “Oh, no-one will use the app unless we do all of these things!”Chat app? ExampleHere’s a worked example for you. Let’s say you want to build an app startup around a chat play because you have something unique. You’re going to use AI.Embed someone else’s chat solution in a static page and mock up the UX you think will differentiate your app. Set it up on an iPad.Show people in the city - ask if they will give their email address to get on the alpha of the app (even though its not known what it is yet) - and if they say yes, collect it. Show them the premium upsell you plan and ask “Would you pay $10 for this premium app membership RIGHT NOW?”People will say “Yes” to you one-on-one, and even give you an email address. But if you cannot convince anyone to pay for it, why is it going to be any different with an app? An app is harder to sell through than one-on-one in the street.Summary* An idea is nothing. * Make an app startup canvas or business plan* Then a mockup and sell it to customers.* Plans will go off course. * Either have supplies for the long haul, or * Exercise great care to resist expensive course correctionsTotally a Thing is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit totallyathing.substack.com

This is a free preview of a paid episode. To hear more, visit totallyathing.substack.comThe traps that end many app startups are covered in this talk as they apply to how you and your team work to build your app. I’ll talk about the cycles, milestones and how those fit with launches. Then I cover the role of two critical professionals in the app development team: the UX Designer and Product Owner.Resources: the cycle index card I refer to …

Hey, I have a great idea for an app! Can you tell me, just roughly is fine, how much would it cost?This question was one I fielded literally hundreds of times in the decade or so I was doing mobile app development in startup co-working spaces, after quit Google and Nokia to run my own app consulting business.The number one thing I that stopped more than half of these starry-eyed appreneurs from going ahead was they had no business plan. Even if you’re trying for some sort of social enterprise, you need to keep the thing afloat.This one pager canvas, inspired by the lean business canvas, is a way to quickly map out an at-a-glance snapshot of that strategy. Its not a pitch, its not a go-to-market, its not even a business plan yet. BUT: it’s the mud-map you must have as a minimum before you go looking for more buy-in from outside collaborators, such as your developer partners and investors.Why Do You Need it?Brian came to me with an amazing idea. His father had suffered for a long time with a degenerative disease necessitating more and more home aids of various kinds. Sadly when Brian’s father passed, those aids would be headed for the trash heap. But other folks need those aids for their loved ones! What if there was an app where you could jump on, know that someone had already logged on and had some reputation to list the home aids, put up photos. Then you, also verified, go and buy them at a reasonable price. The aids avoid going in to landfill, both parties win: what a great app!You just invented Facebook Marketplace. Except it will cost you $100k+ to build.“So, Brian,” I said, “you want an app where first someone can log in and be verified, then list their home aids with photos. Someone else like that can buy them? I think you just invented Facebook Marketplace. Except it will cost you $100k+ to build. Why not start with Facebook marketplace first?”Brian was so invested in the emotion of what he wanted to do - which is completely valid and important, you can’t achieve great things without passion - but he had forgotten to look at it from a practical angle. How would he differentiate his idea? What did he bring that made it any different from the options? What if his early customers were already waiting and he didn’t need a special app yet?Brian could have saved himself feeling disappointed if he’d spent some time with the app startup canvas.Do it with your Co-FoundersHow do you do the canvas?* TOGETHERMost important: get the whole team in for the exercise. It’s something everyone needs to be giving their buy in for. Don’t be a solo-preneur. That is a losing proposition. I will do a session on this, in case you’re solo right now. But the number one thing you need, as someone with an app based business, is to work with others.* WITH BUY-INAssuming you have the team, by the time you walk away from the session, everything on the sheet should be something you have all committed to putting in to the pot.If you have one of your team members expertise or hours listed as a Unique Value or an Unfair Advantage then that has to be locked in at this session.If you have one of your team members expertise or hours listed as a Unique Value or an Unfair Advantage then that has to be locked in at this session. If you’re the Ops person — like the COO for the startup — don’t accept being told to go do this on your own. It needs whole of team buy-in.* KEEP IT LIVEYou can use a live shared whiteboard/doc eg Canva, or Google Docs, or a Microsoft Word 365 document - as long as you can take a private link to it that only your team can see.* Set up a zoom call, with a shared doc, and plonk the canvas JPG on to it. OR* Print out the canvas on A4, and then use a large sheet of paper & pens OR* Get around a tablet/ipad and markup the canvas with a stylus/Apple Pen.The whole thing should take 45 minutes or less. If you are solo now, sure — go ahead and fill it in — but you must do this sheet again when you have your team.Sell a Product People NeedYou’re going to start by using the focus statement at the bottom of the sheet. It can change, but start there. It’s based on a pitch framework from Anthony Gaddie:* The Gaddie Pitch exampleSo for Brian above it might be:You know how* it’s really hard to deal with all the assisted living aids (problem)* when you lost a loved one who used those aids (target = bereaved kin)Well, what we do is* know what its like* provide a two-sided market place for aids* with authentic buyers and sellersSo far we have* re-homed 20k worth of home aids that would have gone to landfillEnter the Items from the pitch line on the sheetBrainstorm the Gaddie Pitch until you have it down on a sheet of paper. Then you can transfer it into the sheet:Problem* it’s really hard to deal with all the assisted living aids (problem)* folks who have lost a loved one who used those aids? (target market)Offering* provide a two-sided market place with authentic buyers and sellersMetrics* 20k GTV (gross transaction value)Unique Value* authentic users* founders personal experience of target marketConcept* two sided marketplaceJust because its needed doesn’t mean it will workNotice that I already mentioned a big problem with Brian’s idea was that it was basically Facebook marketplace? Also we can see that folks who have lost a loved one who used those aids? (target market) is not a big TAM (total addressable market).Finally the Unique Value of “authentic users” is a tough thing to sell. Brian’s story is one from the heart with his bereavement. But how when you expect every customer to see that value, what are you going to do to get cut-through? Facebook users are already authenticated, and they try to have real profiles with authentic profile photographs. But there are a lot of inauthentic profiles - sometimes for privacy reasons. How will you solve this problem when even Facebook struggles?Use the Canvas to Distill out the TruthsThe Gaddie pitch is great for being bullish about your idea, and it’s a fantastic elevator pitch. But when you’re looking to make an app, that is a big investment of time and money, so some realistic modelling is needed.What the app canvas will do is help you see that. By stripping it back to a simple proposition on the top-left part of the sheet, you can move across the top of the sheet and see if you can make it work.I could not get people to buy [an app I built that people needed] because there was already competitor apps out there, and people already had workarounds.Quick story: I built an app that people needed. I could not get people to buy it because there was already competitor apps out there, and people already had workarounds. My app was better, and had more features; but when your target market is a niche - like Brian’s and like mine - you must be willing to build a go-to-market strategy that can reach those folks where they are. List the Current AlternativesThis needs to be not just what is actually a straight head-to-head competitor, but what people are using right now. Talk to people who have the problem. What is it that pops up in peoples heads when you raise this problem right now? What has mindshare? What do you face when you find a go-to-market strategy for your app?For Brian it would be:* Facebook marketplace* Selling it back to the pharmacy, community groups etcIn Brian’s case, he and his team/family had already used these above alternatives and established some good social proof by re-homing 20k worth of aids.So your first MVP might actually be built out of these alternatives. Providing that there is a market, and the first step for your go-to-market plan, might actually be meeting your market where it already is.WorkaroundsAlso workarounds, that don’t have all the benefits of your solution, must be listed:* Taking the items to the dump (wasteful, contributes to landfill)The app is only a channelIf there is only one thing you take away from this, please let it be this:your app is only a channel, its not a golden gooseGo ahead and write in the top of the sheet:Channels* Mobile app* Web appA problem I used to see a lot in appreneurs that approached me to build an app is that they would look at successful apps in the App Store or Google Play store and say “I want that, but for X” where X was their idea. It’s like going to a video production house and saying “I want a video to go viral please.”There is almost zero discoverability in the App Store and Google Play store. If you see a successful app getting promoted in those stores it is because a team of people worked really hard for that to happen. I will address ASO and features in another post, but let me assure you; when you publish your app no-one will see it.Brian understands that because authenticity is so important he is recruiting a talented part-time community manager to work across all their events, social media, and newsletters in a personal customer-centric way that fits with their social enterprise profile. Also Brian has identified a local sports star — a Key Opinion Leader — and a community arts figure to be the first customer zero in a visible way:Costs: Growing* Organic/social media marketing $50k/pa* Hosting, domains, ongoing app costs $50k/paCosts: Fixed* Initial App development $100k+* Legals, accounting, other setup $20kCustomers: Champions* KOL’s, customer zero Brians has shown these folks his app mockups they are helping build the buzz.RevenueAfter getting some idea of costs, factor in operating profit and ballpark the revenue, and figure out when you can recoup initial development costs:Revenue* Percentage of transactions 20% x $1m = 200k/paBrian thinks that with his plan he can get to $1million in transactions in a year.What is the revenue model? Will you clip-the-ticket on transactions, taking a percentage when the buyer pays for the goods? Require a membership or subscription to list on the platform? Have affiliate sales or value-add like truck rentals or tradesmen installers in Brian’s case? Capture your Secret SauceWhy are you the ones to execute and make this app a reality? Why would I not just download a clone of the app that was released after your but at half the price?Unfair Advantage* founders personal experience of target marketIn Brian’s case he believes he can curate the sellers in his marketplace so that the pricing is fair, and the aids sold are in good condition. His authentic connection to communities in his target market provides customers with perceived value.Think of everything you bring to the tableThere’s a great scene in the movie Princess Bride where the hero has been so badly hurt that his two collaborators have to use a wheelbarrow to get him to the castle they plan to storm. They list their assets as Westly’s brains, Fezzik’s strength and Inigo’s sword. But Westly says “If only we had a wheelbarrow” — and of course they do!The point is you need to think about the collaborators you have to convince to get on board. And you need to convince yourself when you are slowing down, or getting off track. List what you bring to the table, as a team.* Previous experience - why can your team do this?* Irreplaceable knowledge - what domain knowledge do you exclusively have?* Location, assets, connections.Cost structures are critical for appDon’t skip this, or try to diminish it. But at the same time, don’t get bogged down with small ticket items. This is a big picture document and later you can have a detailed financial plan. For now, the key question is can your revenue outpace your costs, soon enough while your app startup has runway?You’ll start most likely with some stake money. Savings, someone’s credit cards, maybe an early investor. Lots of sweat equity.Ballpark for that running out is 18 months maximum in my experience. Your app building will require an up front spend of capital - a fixed cost - to get the bare bones MVP done. This MVP should be an absolute embarrassment. It will be a poor shadow of the apps you see on the market. But it should be just enough to perform as a channel, as listed above, and no more.Another huge, huge mistake I see from appreneurs and founders is they have not made any sales yet — Brian had his $20k sales — and they think they will build an amazing app that will automatically generate sales for them, if only it is as good as all those super apps in the stores.Wrong.You need to sell first. Then build the app. Your app is a channel.Costs that scale up with trafficMy app design recommendations that I will share on other posts, but which are outlined in my talk “Mobile Mindset” - see the about page of Totally A Thing - include ways to make sensible decisions that reduce overheated app costs.But Amazon or Google hosting is expensive, and if it’s not done well can go up and to the right along with the increase of your user base. This can eat your revenue. Make sure early estimates capture this, and that you don’t price your offering too low so that you cannot recoup these costs.Costs: Growing* Organic/social media marketing $50k/pa* Hosting, domains, ongoing app costs $50k/paBoots on the ground costsThis is a very important one for apps, and it’s often forgotten at the early stages of a an app startup. This is the growing cost of an app, that requires support from real people beyond what is in the App Store or Google Play store portal.Costs: Growing* Community support & customer satisfaction $20k/paBrian gets an urgent message from Carol, his community manager, on Saturday morning. A customer has bought $2000 worth of home aids, and on arrival half of it is broken. The customer is very upset and has recorded a video on Instagram blasting Brian’s app and team. The customer does not speak English, and did not understand a message. Carol is not able to help the customer. Now Brian’s business could be torpedoed as a lot of his customers have Instagram accounts.Brian phones his KOL, Tony, and asks for help. Tony is busy but gives Brian a name for someone who knows the customers community & can speak to them, and four hours later Brian has turned around the situation, and followup posts show Brian’s app in a good light for their fast response.This sort of thing is not a one off. You don’t see what is happening with apps that have a lot of “Boots on the Ground” because it’s not on the app. I saw the roll-out of Uber in Australia which started in the co-work space I was in during 2012-2014. There are constant requests for help, complaints, technical problems and regulatory matters that have to be dealt with. These will eat you alive if you have not planned to limit them, and budget for them.How to use the Canvas* KEEP IT LIVEIf you did it on a big sheet of paper, get a shot of it with your phone, or scan it in. Store it live - in a Google Doc, Canva, or Microsoft 365 - whatever your team can all access. Share the link to your team.Once you have completed the canvas, create a calendar entry for a month’s time, to revisit it with your team and check in on your assumptions.Take a copy or screenshot of the completed canvas and add it to your core team documents, business registration and legals, in a folder, so you can add updated versions as you create them.* USE IT TO GUIDE DECISIONSIn any team setting you can use the canvas to get the team on track, and remind yourself and the team of what you already agreed you bought to the table. Check bold initiatives against the cost structure you sketched out. Any planned purchases of fancy chairs, or team trips - use the sheet to ask how do those purchases get your value out to customers? * USE IT TO ONBOARD NEW PEOPLENew founders, top tier collaborators or partners need a lot of quick thinking when testing how they will fit with your plan. Use the canvas as a compass: does the decision mean a change of direction? How many of the points the team previously agreed on do we need to upset to make this change, or does it fit well?Summary This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit totallyathing.substack.com

This is a free preview of a paid episode. To hear more, visit totallyathing.substack.comApps are part of the fabric of the InternetApps seem simple when you look at them! But we know companies like Facebook and Google; Twitter and Snapchat have hundreds, even thousands of people working on apps.

Get the benefit of 20 years of experience in mobile development to understand the real factors that should play into your choices about which platform to build your startup’s mobile app on.This is a free episode! Enjoy. If you get something out of this one, or on hearing my background want to find out what else I have in store on tech, culture, apps and startups then definitely subscribe - you get a free unlock for my “How to Build an App” series when you do.You have limited runway, wrong decisions could be very costly. So you are going to make a business decision, not one based on whether someone’s very techie cousin says Android is “the best”. Or whether all your friends use iPhone.Or then there’s that really promising sounding cross-platform system. Surely with Android and iPhone it’s best to just “sell it to the world”, right?I wish I had a $100 for every keen entrepreneur who thought that they would “go global” on all platforms and wound up with their business being consigned to the dustbin of history.In this talk I will dig into the history of the two platforms and show how deep those cross platform differences go. I’ll take you to Silicon Valley, and that time I talked to the founder of Android, Andy Rubin himself. I’ll talk about the the other cell phones, the ones that have been the poor cousins to iPhone and Android - and what we can learn about them.I’m going to talk about the power of niche - something I will cover a lot in future Totally A Thing episodes - and how platforms can play a huge part in it. And finally I will talk about going to the stores, and some object lessons from my time making my own apps - both cross-platform and single platform plays.Totally a Thing is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.Thanks for listening, and please, there will be more unmissable talks and actionable information coming from TotallyAThing. So your next step is to click this button and I will see you on Saturday for more on How to Build an App. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit totallyathing.substack.com

This is a free preview of a paid episode. To hear more, visit totallyathing.substack.comHave you ever wondered what goes into building an app? What different kinds of apps are there? How can I get an app built?Follow this series of blog posts (indexed below) to find out the answers to these questions and all your other questions about building mobile apps.I’m Sarah Smith and I have been working with apps for over 20 years. I worked for Goo…

In my career of mobile app engineering I have been asked this question a lot. “How much is a mobile app?”Well, the question you should be asking is “How much could it cost if you try to do it on the cheap?”When you partner up to build a mobile app for your business, you expect that it will be simple to get the features you need for your app to succeed. These days even if your app is part of some larger business, or if its an “appreneur” play in its own right, you cannot do without an app.But partnering with the wrong people can cause your dreams to go horribly wrong. I worked with startups and had apps of my own in the app store. I know how tough it is to succeed.The good news is you can do well, just by following some simple guidelines. Ones that I’m going to share in my Substack series on mobile app development. Much of it will be for free. My consulting services were charged out at an eye-watering hourly rate. But I don’t want to see businesses fail for lack of a few basic lessons.I’m not about to sell you my services. You’ll get much of what I have to communicate in this series for free. When it drops, typically even the premium episodes will be free for a time, so its a no-brainer to subscribe so you get onto it while its fresh.Totally a Thing is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.And, I’m sure you want to know - how much is a mobile app? Check my video above and I have a teaser for you! You’ll want to know how many screens you have. Starty by using my app napkin template to sketch out the basics of your app and find how many screens you need.Comments or questions? Love to hear them! Subscribe and put your asks below. Thoughts about my video quality? Me too! I do not have access to an expensive studio and that is how I can offer my advice at a rate that is not going to break your bank. Subscribe to the paid plan to get all the content that is going to be in this series, and help me make better videos as well! This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit totallyathing.substack.com