Saul Howard

Ignatz Mouse

I’m a hacker in NYC. I'm building AI for healthcare at Anterior.

In 2026, I gave a talk at AI Engineer World's Fair: Why your enterprise tech stack isn't ready for AI agents

I write on this site and sometimes on a substack at 31 Seconds.

From 2016–2021, I led a team at Apple building the CloudKit developer platform. Before Apple, I worked at startups around London and Asia, including Hailo.

I produced the feature film Brighton Wok. I work on applications for Drama Theory.

I’m on GitHub, LinkedIn and Twitter.

Articles tagged with knife-fights

  1. The kids are alright

    Social media, mobile phones, video games and now AI are among the crowning jewels of human creation. Infinite libraries of information are in everyone's pocket. Entertaining new formats for instruction and diversion are being created, not by media institutions, but by ordinary people in their spare time. Children are no longer kept apart from each other in classrooms, but have their own virtual worlds in which to create knowledge and share it.

    The response from our gerontocracy is predictable: ban it.

    As usual, Douglas Adams summed it up:

    I've come up with a set of rules that describe our reactions to technologies:

    1. Anything that is in the world when you're born is normal and ordinary and is just a natural part of the way the world works.
    2. Anything that's invented between when you're fifteen and thirty-five is new and exciting and revolutionary and you can probably get a career in it.
    3. Anything invented after you're thirty-five is against the natural order of things.

    The truth is that technology is disruptive: it changes societies. In their time, movies, books and even the bicycle all instigated widespread moral panic. Bicycles meant that for the first time, young people could easily meet friends under their own steam, the social network technology of their day.

    Today, teachers worry about children in their classrooms "addicted to their phones". So the children aren't paying attention to their lessons, but the truth is many never were. Now instead of sitting at desks like zombies, they're happily engaged in their phones because they have access to something that really interests them.

    But disruptive memes are spreading among children! Well why shouldn't children be allowed to create and disseminate knowledge among their peers? Isn't that the essence of education? Or do we think children should be passive, empty vessels into which we pour our approved ideas? If you disagree with the memes children are sharing, you should make an argument for your position, not shut down the debate.

    Children are using ChatGPT to write their essays! I'm sorry to tell you, but adults are using ChatGPT to write their emails and reports. Education needs to adapt to the reality that social media is a better way to discover new interests and YouTube is simply a better way to learn basically anything.

    There's another sinister undercurrent to the "ban social media and AI" platform. In the case of AI, big tech companies (Google, Facebook, Apple etc.) thought at first that AI would be a "sustaining technology" - that is, because of their ability to invest billions and hire the best engineers, mastery in AI would help to cement their monopolies. But recently, the CEOs have woken up to a growing realisation that AI might well be a "disruptive technology" - as a commodity, AI gives startup companies the ability to challenge Google in search, Facebook in social media and Apple with the idea that maybe we don't all need to use their phones. Their playbook is the same as any other industry cartel's: lobby the government to regulate their industries, because regulation raises the table stakes to enter the industry so effectively that startups become non-starters. Facebook will happily pay the governments tax to censor their social networks, as the enormous cost of doing so serves to prevent any challengers to their business.

    Note that, this isn't an argument against allowing the Chinese ownership of TikTok. I see real geopolitical reasons why we might not want our media companies in foreign hands. We have had similar legislation against foreign ownership of newspapers, for example.

    While I may not agree, it's wrong to say that there's no argument for some regulation of AI. First we should admit that most of the scare stories and scenarios presented are already illegal. Why should it be more illegal for a judge to be racially biased if the judge is using AI, for example? The call for regulations over issues already covered by existing legislation is a tell-tale sign of a monopoly campaigning for cartel protection. I'm told that, out of all AI scenarios, politicians are most worried about deepfakes, and that is a genuinely new capability that perhaps needs oversight. However, lawmakers should be aware that it may not be technically possible to ban video or audio that "sounds like Rishi Sunak". More likely, we need to adapt to a world in which all media is suspect, and learn to use technologies for proving provenance of video and audio.

    Lawmakers should be very careful of any regulation governing such a fast moving and potentially fruitful technology as AI. If we regulate it out of existence, or make it so that only Google can afford to play, we will never know what possible good we have lost: badly needed medical, educational, military and productivity gains are all to play for.

    Ban children from social media and we stultify them, lock them out of the most exciting new technological spaces and prevent them from educating themselves.

  2. The new acqui-hire

    Satya Nadella is a fearsome operator.

    VCs Mus Sat dilemmas
    Satya Nadella
    Acquire Inflection ⨉ ✓ ⨉ VCs T wrt Sat
    Mus P wrt Sat
    Hire Mustafa Suleyman to head a new division at Microsoft. - ✓ ✓c Mus t wrt Sat
    Mustafa Suleyman
    Bring most of Inflection's 70 staff with him. ⨉ ✓ ✓ VCs P wrt Mus
    Sat T wrt Mus

    Satya Nadella 's adoption is conditional (promise) on Mustafa Suleyman bringing most of Inflection's 70 staff with him.

    Tuesday’s hiring was “basically an acquisition of Inflection without having to go through regulatory approval”, wrote Tony Wang, managing partner at venture capital firm 500 Global.

    Steven Weber, a professor and expert on technology and intellectual property at the University of California, Berkeley, noted the deal was similar to the offer Microsoft made to OpenAI employees after chief executive Sam Altman was temporarily sacked last year.

    Microsoft and Inflection have stressed that the agreement is not an acquisition and that Inflection remains an independent company. FT

  3. Interface to human language

    One approach to making use of LLMs is to see it as an oracle: we can say "solve this problem for me", or at least "give me a choice of solutions". As all the answers to our problems can theoretically be generated, we can go ahead and retire all the human theorists and engineers. Science is solved.

    This approach assumes that creative problem solving is a matter of rearranging existing knowledge. Or, if more knowledge is needed, that knowledge acquisition is a process of mechanically recording the universe. Both are mistaken. We don't know the algorithms for creative problem solving or knowledge acquisition. While the "LLM as oracle" approach will certainly produce advancements in knowledge retrieval, it won't create new knowledge.

    Another approach, one that we're following at Deep Drama, is to use the LLM primarily as an interface for human language. The potential of "LLM as language API" is greater than it seems. There is the obvious path of building more powerful User Interfaces far beyond chatbots. But there is also the potential to expand the scope of our software, beyond solving transactional problems to encompass as-yet-untapped social frameworks. Our software has blind spots. Large areas of human knowledge and experience have been overlooked by engineers because of the messiness of their interfaces.

    As an example, I used Deep Drama's LLM-powered Source tool to generate this Drama Theoretic model of a random news article:

    Don Joe Nip Uni dilemmas
    Donald Trump
    Block the deal immediately if winning the 2024 election ✓
    Joe Biden
    Express opposition to the merger ✓ ✓ ✓ Don T wrt Joe
    Uni T wrt Joe
    United Steelworkers labour union
    Oppose the merger ⨉ ✓ ✓ Joe P wrt Uni
    Nip T wrt Uni
    Nippon Steel
    Acquire US Steel in a non-hostile deal worth $14.1 billion ⨉ ⨉ ✓ ⨉ Don P wrt Nip
    Joe P wrt Nip
    Uni P wrt Nip
    Introduce new technology and capital to US Steel ⨉ ✓ ⨉ Joe P wrt Nip
    Uni P wrt Nip

    The model's format is explainable and programmable. By using the LLM as an interface to language, Deep Drama can then use this model as the basis for further analysis and interaction, both with LLMs and with traditional interfaces. Deep Drama keeps the knowledge, and the opportunity for creativity, in the hands of the human users.

  4. Service politics

    Microservice architectures are a solution to scaling systems. Startups who start with a micro service architecture before they have scaling problems, sometimes before they even launch, attract ridicule.

    But microservices are also a solution to an engineering management problem. Startup codebases are usually a mess. Proof of concepts, abandoned features, quick hacks are what it takes to find the product.

    Developers keep returning to service architectures because the separation of concerns enforced by the network makes it easier to maintain the codebase, onboard new developers and adopt and abandon features. Maybe your startup has a loyal team of focused developers, and you can do all of that within a monolith. But many don’t. In Yegge’s Platform Rant, he showed how service contracts are necessary for managing multiple engineering teams, but individual developers can benefit from them too.

    Serverless functions, LLM-scaffolding, cloud IDEs and bounties for features are all on the rise. Increasingly, systems are built from loose federations of distributed functionality. Like all engineering solutions, it’s a tradeoff. Abstracting problems at the network layer gives you network problems. But it can solve for spaghetti-monoliths.

  5. SEO at the end of days

    Google’s announced a GPT-4 killer, Gemini, for release by December. There’s no question that OpenAI have a massive lead, but from the outside, it doesn’t look unassailable. LLMs may have presented Google with the first real threat to their search business.

    LLMs hint at a new interface to computing. Microsoft’s strength isn’t interfaces, but sales. They can add LLM features to their software as customers need them. Apple can fall back on their hardware — and may see an increasing demand in consumer compute even as they slowly come around to updating iOS. But Google is only an interface. A single UI paradigm — search. They’ll need to move fast.

    I was talking SEO today, and the paradigm already feels outdated. People out there still discovering software through search engines like boomers with cable subscriptions.