Software Lead Weekly

Eight Years of Wanting, Three Months of Building With AI
7 minutes read.

This is one of the most balanced posts about how to use AI effectively, where it shines, and where it will drag with short dopamine boosts just to rewrite the whole thing a month later. A must-read by Lalit Maganti on coding an open-source project while working as a Senior Staff Software Engineer at Google.

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Gauss 🤝🏽 Gymbros
1 minutes read.

My humble effort to help you start the weekend with a smile. Sometimes, it just works.

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From World Model to Domain Intelligence
11 minutes read.

Boaz Katz's take provides a practical way of thinking of Block's post on Org Design in the AI era. Boaz provides a useful framing (org architecture looked at as Monolith vs. Microservices) and triggers the type of learning and experimentation worth following. Leadership will truly own the org design and implementation: "You don’t just own your outcomes anymore. You own the quality of your domain model’s understanding. If your Revenue model has blind spots, they are your blind spots. If your People model is optimizing for the wrong signal, that’s a reflection of the intent you set. The model is a mirror of your strategic thinking — which means you can no longer hide behind complexity, or volume, or the fog of too much information."

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How We Hire AI-native Engineers Now: Our Criteria
9 minutes read.

"We're sharing this early because we expect the framework to change. The tools are changing quickly, and our view of what great AI-native engineering looks like is changing with them." -- The team at Augment Code shared how they evaluate candidates for engineering positions to spot people who can truly leverage technology advancement. What are you looking for? Which type of questions help you identify top talent?

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The Internet Ruined Customer Service. AI Could Save It.
7 minutes read.

Sarah Wang shares how companies should think about their customer support in the era of AI: "AI will make all of this possible at scale for every customer at every business. The “customer service” relationship stops being episodic, reactive, and generic, and becomes continuous, proactive, and deeply personalized. That is the concierge model. And it’s what’s going to define the future of essentially every scale business. And here’s what might be the most underrated part of this shift: when the concierge knows you and is always on, the distinction between “support” and “commerce” dissolves. A great concierge at Hermès isn’t just a fancy customer support rep; he’s a salesman in disguise. They know your taste so well that their recommendations feel not like a sales pitch but like a favor. That’s the model that AI could unlock for every business. Customer service, done well, has always been a revenue opportunity hiding in plain sight; but until now the costs of hiring a capable human have made it feasible only for high-ARPU businesses in the luxury sector. Now AI can make it available for every business. At the limit, “customer service” and “commerce” meld into the same thing."

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I Stopped Needing to Spend Three Hours a Day Finding Things Out
5 minutes read.

Managing context effectively and learning how to reduce the time it takes you to get the context you need is something we all need to explore with the latest technologies. Rafe Hatfield shared his, and it will inspire you to look for ways to invest more of your energy and time in high-leverage activities.

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How to Build Your Second Brain
6 minutes read.

Simple framework to pick up and experiment with for a personal wiki that is smart enough to gather raw content you want to learn or remember, transform it into digestible insights, and be able to iterate on it over time.

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@readswithravi: I'm in love with this sentence: “Forgive yourself for not knowing earlier what only time could teach.”

@rodriscoll: When companies come to me and say we're using AI in GTM or we're using AI in engineering, I say that's great, but no one cares. That’s jacks to open. If you're using AI at the same level as everyone else you won't have an advantage by definition. The only way it counts is if the product you deliver to your customers is meaningfully different because of it or you have a cost advantage nobody else has. If you're a software company today, there is only one question that determines success or failure: how does AI change the end product you deliver to your customers?