mathattack

I used it most key to learn about history. There isn’t much damage if it got 1600s or 1700s detail wrong. My high school teachers got much of it wrong too.

This is consistent with a lot of AI apps. I fell in love with Gamma and haven’t used it in forever. Same with NotebookLM.

I worked at a Lotus shop in the 90s. It was great until everyone moved to the web, and then it got too clunky. Fat clients that stored tons of data locally weren’t the thing anymore.

When that company moved off of Notes despite the massive investment, the writing was on the wall even if the product survived for a few decades under IBM.

Any one loan may be risky, but in aggregate the rates compensate for it.

They pay you 0-4% for the money in your checking account and lend it at 1-3% points higher. As long as they have a big enough uncorrelated portfolio, they make easy money.

And if the whole portfolio tanks all at once, the whole industry gets bailed out.

These are the projects that give us confidence.

40% actually seems reasonable for a flip into maintenance mode. That’s what PE firms do when then buy cash cow businesses. Dramatically cut engineering on new functionality, cut back on sales and marketing, remove all redundancy in operations.

Anyone who has counted on a vendor that went private or was bought by a rollup firm has felt this pain.

Better to do it all at once than repeated declines.

Interesting given the current age discrimination lawsuit:

https://www.cohenmilstein.com/case-study/ibm-age-discriminat...

My assumption is most Science Fairs are based on Dad and Mom’s contribution, and things like this are filler for elite university applications.

The one thing that suggests this might be legit is that Pasadena has an elite Math High School. https://www.mathacademy.us/

If a college senior could pull it off, perhaps a properly educated high school junior could too.

The best books improve with rereading and slower reading. Tolkien fits this. I had an English teacher who reread LOTR every summer. I’m not there, but I am on a 5ish year cycle.

Most books are the other way. Zoom through and you can get most of the value. This is especially true of non-fiction, where most have a message that can be gleaned in 15 minutes. (The exceptions are the great ones)

Podcasts are similar. Most give you 80% of the value at 2X speed. Even my favorites - I’d rather speed listen to get 80% the value rather than get 100% of half the backlog. The best podcasts defy this too.

So in the end it’s a bit of a skill to both choose the right things to slow down on, and then a discipline to force the appropriate speed.

My 2 cents, especially in this tough job market.

1 - There are two phases of the interview process, where you’re selling them and where they are selling you. These questions are best asked in the latter. To get the most accurate answer, ask to talk to a few future peers after you get the offer in hand. Until you have that offer in hand ask softball questions that can’t be answered via the website, like “What motivates you to stay given all the opportunities in the market?”

2 - Be careful in how you ask, as you don’t want to signal you can only work in a high structure environment. So you can rephrase as “At company X I earned a reputation for fixing process Y. What software engineering processes could I help improve?” or “As you plan to grow 10X what aspects of culture and teamwork do you see changing to enable us to scale”

Leaders value engineers who help them improve over ones who require a perfect end state. So go after the answers you need, just be mindful on when and how you ask.

Do you retain the info?

I guess it’s ok for compliance videos but I’m not sure about retention.

I write this as someone who wants online education succeed.

This seemed inevitable, no?

I’d love to see long term usage data on MOOCs. They had so much promise though I don’t know anyone who uses them post-LLM though it could be I live in a bubble.

For hiring managers, does this devalue elite schools?

I’ve had good luck with places like Notre Dame and Cal Poly where the kids are smart, and willing to work very hard. From the Ivy League I’ve had more luck with Cornell hires than the others.

It’s a small sample size so I’m curious what others see.

It’s been a different order of magnitude. IBM repurchased approximately half their outstanding stock. This is consistent with a low growth company that doesn’t know how to grow any more. (And isn’t bad - if you can’t produce a return on retained earnings, give them back to shareholders. Buybacks are the most efficient way to do this.)

I can’t explain why they have a PE ratio of 36 though. That’s too high for a “returning capital” mature company. Their top line revenue growth is single digit %s per year. Operating income and EBITDA are growing faster, but there’s only so much you can cut.

You may be right on the quantum computing bet, though that seems like an extraordinary valuation for a moonshot bet attached to a company that can’t commercialize innovation.

Interesting to hear this from IBM, especially after years of shilling Watson and moving from being a growth business to the technology audit and share buyback model.

If someone feels this is a sham transaction, can't they buy Credit Default Swaps [0] betting that it will default?

[0] https://en.wikipedia.org/wiki/Credit_default_swap

I do get concerned when the solution is to be more strict on the waterfall process.

I used to believe there were some worlds in which waterfalls are better: where requirements are well know in advance and set in stone. I’ve since come to realize neither of those assumptions is ever true.

Seems like a lot of different audiences. My observation is this is trying to cover 2 of the 3 common tracks:

1 - Proof based calculus for math majors

2 - Technique based calculus for hard science majors

3 - Watered down calculus for soft science and business majors (yes, there are a few schools that are exceptions to this)

If he can pull off unifying 1 and 2, good for him!

I’ve seen this happen many times. It looks cheap and easy to spin up, then it grows out of hand and they kill you on the renewals.

Fair enough. I guess my take is more that a CEO of a 100 person company should know who the best person for the role is. The CEO of a 100,000 person company is less likely.

I’ve seen what you’ve seen too though: companies that haven’t grown past everyone thinking they report to the CEO turning into gossip factories.

Shouldn’t be a political play then.

In a good market I’d say you should look around. In this market, keep your head down and get some experience.

How large is the company?

Many times plum resume building assignments at big companies go to the best politicians rather than the biggest experts.

I experienced some cutthroat commercial behavior from MongoDB. It scared us enough to avoid Atlas, and ultimately move to Cosmos on Azure. Massive savings.

I moved to another employer that was using Atlas, and the bill rivaled AWS. Unfortunately it was too complex to untangle.

And now he appears on their podcast.

I’m amazed how many people leave on bad terms. Over any medium and long term time horizon it’s a terrible strategy. You never know who will do a quiet back channel reference, and many times we wind up working for the same people.

The other piece of advice about documentation is important beyond leaving for a new job. Many people lose promotions because “who could possibly backfill them?” Creating a high talent well documented organization is a great signal for promotion readiness, and takes a roadblock away from it too.

Great post. She applies her analytical CS thinking to the angel process.

It’s been a sustained drop. An early canary in the coal mine too.