Building Teddy Chat, an AI front door for pediatric clinics and Pace, an AI companion for families. Dad. Vancouver. NFT creator @mintedteddy
Vancouver, BC
Joined September 2010
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zoran retweeted
The biggest misread of anyone predicting the end of software engineering was imagining that the world only needed a certain amount of software, and bringing automation to the field would reduce the need for labor.
Exactly the opposite is happening where essentially most things are actually turning into software. Because agents can use tools, work with computers, write software on the fly, and process data like humans (but far faster), we can now throw “software” at problems that never could reasonably be digitized before.
What that leads to is the role of engineering taking on greater importance in the economy, because we can now engineer far more systems and processes than were possible before.
If you’re a bank trying to do new forms of trading, engineers are often your first bet. If you are in life sciences, you expect more and more research and lab work to be engineering centric. If you’re in manufacturing, you’re trying to automate more of the supply chain, all that is engineering. More and more work is shaped like software problems.
Yes we’re not going to be coding manually in the future. But almost everything will be code, which means those that understand it are in a fantastic position.
Some observations about the "total" automation of software engineering:
1. There are more software engineers now than in 2025, and demand is growing.
2. Software engineers have never worked harder than they do now.
3. They largely don't write code anymore, agents write ~100% of the code.
4. The bottom line of the companies that employs these engineers and agents (i.e. the terminal purpose of all this code) is typically not budging as a result of AI adoption.
This is why you have to think in terms of systems. Automating one aspect of a system creates its own friction and moves the bottlenecks elsewhere.
zoran retweeted
I've never seen an exceptional product that was designed by committee.
Too many cooks in the kitchen make products that are complicated and diluted. Every compromise feels small in the meeting, and together they water down the whole thing!
zoran retweeted
The thing I’m most grateful to Elon for is bringing back an age of wonder and excitement to humanity. That was jaw-dropping awesome! Screams and mouths wide open in the audience. Nuts.
zoran retweeted
Agents spawning other agents, agents operating in the background on every task, and agent swarms will consume 1,000X more tokens than people prompting agents 1 at a time.
The usage of AI as a chat system that can only work for you at the pace that you can prompt it will seem like a relic within a year or two. The vast, vast majority of tokens will be consumed by agents that are just doing continuous work for us in the background and in our workflows.
This is why we’re still so early in the curve of AI agent adoption right now, and how much more compute and infrastructure build out will be needed to sustain this.
zoran retweeted
Alexandr Wang 在谈到“如何拉开与 99% 人的差距”时，给出了极其朴素甚至残酷的答案：
顶层竞争根本不拼智商，拼的是极端执行力的非对称倾斜。
他的三条核心准则：
1. 绝对聚焦，压榨认知带宽： 绝大多数人的忙碌只是“低密度伪勤奋”。真正的专注是把全部精力砸在唯一的核心支点上，拒绝任何无关干扰。
2. 把“过度交付”做成护城河： 行业标准要求走 1 英里，你就走完 10 英里。当所有人都按合同完成 100% 时，常态化交付 200% 的人会直接卷走全部声誉与溢价。
3. 带靶向的超额输出，拒绝无目的内耗： 努力不是盲目自我感动，而是针对具体目标的持续过载测试。把每一次交付都当成生死决战来打。
商业世界最公平的一点在于：
聪明人到处都是，但能忍受极度枯燥并长期超额交付的人凤毛麟角。
执行力溢出，就是最暴力的护城河。
zoran retweeted
Introducing EmbeddingGemma 2, a new open multimodal model that sets the standard for on-device efficiency.
- our first open, natively multimodal embedding model
- handles text, code, image, video, and audio tasks within a lightweight, modular 740M parameter form factor
- ideal for offline, privacy-first RAG when paired with Gemma 4
- outperforms some specialist models more than twice its size
Weights available now on Hugging Face.
zoran retweeted
To help revive fireflies: turn off outdoor lights at night (use red LEDs or motion sensors if needed), avoid all pesticides and lawn chemicals, leave leaf litter and rotting logs for larvae, let some grass grow longer, plant native plants, and keep soil moist with mulch or a small water feature. A wild corner of your yard creates habitat. Report sightings to projects like Firefly Atlas.
zoran retweeted
Earth is just one of about 100 billion planets in our galaxy, which is just one of about two trillion galaxies in the universe. And our lifetimes are only about 1/3,000 of humanity's existence, which itself is only 1/20,000 of the Earth's existence.
In other words, we are unbelievably tiny and short-lived and no matter what we accomplish, our impact will be insignificant.
At the same time, we instinctually want to matter and to evolve, and we can matter a tiny bit--and it's all those tiny bits that add up to drive the evolution of the universe. #principleoftheday
I find this mildly entertaining, but I’m also a little saddened by the growing drift between Canada and the U.S. To me, we’re family, with so much shared history, friendship, and love between our two countries.
zoran retweeted
The most useful thing I've learned about food mastery is that eating bad things is never, ever worth it. You never feel good after. Only regret. Once you fully internalize this, you can simulate the experience and then muster the power to overcome the primal desire.
The AI front door for a clinic won’t be one chatbot.
It will be one intelligence layer across the website, phone, and text - the places families already try to get help.
That’s what we’re building with Teddy Chat for pediatric practices.
Hypergrowth comes from subtraction before multiplication.
Most companies respond to a problem by adding people, meetings, approvals, software, features, and automation. Jon McNeill argues that exceptional companies reverse that instinct. They first remove everything that does not need to exist, then make what remains faster and scalable.
The five-step Algorithm
Question every requirement
Ask who created the rule and why. Is it truly required by law, safety, or physics, or is it simply inherited convention?
Delete every possible step or part
Remove approvals, features, product variants, meetings, handoffs, and process steps that do not directly create value.
Simplify and optimize what remains
Only improve the process after unnecessary elements have been eliminated.
Accelerate cycle time
Compress the time between idea, action, feedback, and correction. Speed exposes bottlenecks and weak assumptions.
Automate last
Do not encode a broken process into software. First prove the workflow manually, simplify it, and only then automate it.
The sequence is the real lesson.
If you optimize before deleting, you make unnecessary work more efficient.
If you accelerate before simplifying, you create chaos faster.
If you automate too early, you permanently scale complexity.
Tesla's over-automated Model 3 production line is presented as a major cautionary example. The company eventually removed automation and temporarily assembled cars more manually. The book also describes attacking a 64-click Tesla purchasing journey by deleting steps and radically simplifying financing documents.
The deeper management philosophy
The book is not really about Elon Musk's personality. It is an operating system for challenging bureaucracy:
Treat the entire customer experience as your product, not just the item you sell.
Create a weekly cadence of urgency, ownership, and accountability around the few issues that could materially change the business.
Have leaders personally use the product so they experience the same friction customers experience.
McNeill's distinction is that traditional lean management often improves an existing system incrementally, while the Algorithm asks whether the existing system, requirement, or component should exist at all. It is less about making the current machine 10 percent better and more about redesigning or deleting half the machine.
