📚 Building Expertise in a Niche, Tennis Lessons, Egg Theory of AI Agents, Ema's Engineering Manifesto

Better Video Ads, Unwinding Wordle and more

Pritesh

Jun 17, 2024

Hi, this is post #163.

I’ve nothing smart to put in this introduction today. We straight away go to quick look at today’s lineup:

And now, onto today's finds…

🗒️ Ema's Engineering Manifesto

I love reading beautifully crafted manifestos and user manuals.

Surojit Chatterjee recently shared Ema's Engineering Manifesto in a LinkedIn post. It talks about engineers, teams, their goals, ways of working and definition of success. These are guiding principles suggesting what’s ‘right’ and what’s ‘expected’. They represent the idea and help folks imbibe them. I wish more teams put in effort to build clarity like this and have the vision to articulate it like this.

Sample this:

Impact first.
As engineers, we must always understand how our work is creating customer impact. If you don’t understand the impact of your work, you are likely doing fake work. Don’t get stuck in doing fake work.
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This does not mean…
…that only external-facing work is valuable. Your customer might be another engineer, another Ema employee in another function, or it might be the financial bottom line if you’re working on efficiency work. Regardless of the end goal, shipped impact is what matters.
…that engineering excellence, or thinking through work before doing it, isn’t valuable. Shipping doesn’t count if it’s not shipped well, because eventually it will reduce our long-term impact. Shipping the same thing twice doesn’t count as twice the impact.

If you like this, do check out Stay Curious #90 for another great example - “manifesto for the data-informed.”

🧥 Building Expertise in a Niche

In “How to be like Derek Guy,” Anu Atluru takes a dig at identifying patterns in success of folks like Derek Guy. She talks about why she did this:

I’ve also found it fascinating to ponder what has made Derek Guy so successful.
My curiosity stems in part from my curiosity about the ingredients for success in public arenas, in part from my being a closet fashion appreciator (in my mind a bit of a connoisseur), and in part from my belief that there are universal lessons to be learned from studying such a character.

So, even if you don’t know who Derek Guy is, give this one a good read. Anu’s sharp observations and pattern matching is a good source of ideas worth pondering on.

She has identified 13 standout attributes, I’m sharing a couple of important ones here:

📰 Alex Komoroske’s Bits and Bobs

I am resharing Alex Komoroske’s bits and bobs newsletter. There is more food for thought per line here than any other newsletter I’ve read in recent times.

Alex has an observant mind, he cares about tiny details to note them down and then structure his thoughts around it. His crisp articulation makes it an easy read. I am confident you will pick up an idea or two to munch on.

Some of my favorite bits from the latest post:

🎾 Roger Federer’s Tennis Lessons

Federer delivered a fantastic commencement speech at Dartmouth College. It’s a short one - 25 mins in total, but packs a lot of punch! He seemed home, and enjoying this experience. There are lots of moments worth capturing. Here’s one for you.

“In the 1,526 singles matches I played in my career, I won almost 80% of those matches.
But what percentage of points did I win?
54%!
In other words, even top ranked tennis players win barely more than half the points they play.
When you lose every second point on average, you learn not to dwell on every shot.
You teach yourself to think:
'Okay, I double faulted...it's only a point.'
'Okay, I came to the net and I got passed again...it's only a point.'
Even a great shot, an overhead backhand smash that ends up on ESPN's top 10 playlist—that too is just a point.
Here's why I'm telling you this. When you're playing a point, it has to be the most important thing in the world. And it is.
But when it's behind you, it's behind you.
This mindset is crucial — because it frees you to fully commit to the next point with intensity, clarity, and focus."

If you’re up for more, give a listen to Jerry Sienfield’s speech at Duke as well. This is a year of unexpected guests and lessons at US universities.

(Transcript snippet via Founding Fuel)

📽️ Better Video Ads

Demand Curve newsletter shared a couple of useful posts around Video ads. With more platforms pushing video formats above still ads, it’s become supercritical to make ads that work.

Growth Newsletter #184 covers two frameworks to increase video ads’s efficacy.

Growth Newsletter #187 talks about some great lessons from organic, viral short-form videos. It takes insight from Jenny Hoyos’ line-by-line, second-by-second teardown for one of her videos with 21M+ views - How Many Ice Cream Flavors Can You Get with $1?

🖼️ How AI Image Model Work

Nir Zicherman uses an analogy to a kids’ game to explain how AI image models work. I loved it because it made a potentially boring topic quite fun and explained a complex technical concept in a fairly easy way.

Here’s is the idea of the “story plot game” -

Let's imagine inventing a new game intended to teach children how to unleash their creativity and come up with fictional stories. Left to their own devices, children will typically write about topics that interest them. But our intention is to broaden their horizons and encourage them to think outside the box, to be comfortable ideating and crafting stories about any topic.

Quite an unexpected approach, isn’t it? Give the post a read, and you’re bound to learn something about the AI Image model working.

🥚 Egg Theory of AI Agents

Rex Woodbury posits the "Egg Theory" of AI Agents to find suitable ways to increase acceptance and effectiveness of AI agents.

It’s a short post, I am taking the final bits that summarize his core argument.

Technology is an adjustment; AI will take some getting used to. There’s a reason self-driving cars still have steering wheels: removing the steering wheel would probably make us freak out. Too much change, too fast. The best companies will be savvy in how they embed human decision-making into workflows, rather than removing the need for human input altogether. They’ll also inject moments of familiarity to balance out the discomfort of the new.
Winning products might not be those that show off the full extent of current technology, rendering humans obsolete. Those products will be fancy, but they’ll ultimately fail by missing a key point of user psychology.
Winning products, rather, will be those that offer a bridge from the world of human work to the world of software work, making us feel comfortable and in control along the ride.

If you’re keen to think better about AI Agents, a16z has a good thesis on AI Voice Agents. Can give you a good structure to understand the space and direction of developments in the coming quarters (and if not years)

✨ Everything else