MungerWunger

Photo of the 1989 annual meeting (from twitter)

the market believes that customers can vibecode their own customized solutions with AI (HUBS, CSU, CRM)

Software is getting murdered today

The AI revolution is here. Will the economy survive the transition? Michael Burry, Dwarkesh Patel, Patrick McKenzie, and Jack Clark https://post.substack.com/p/the-ai-revolution-is-here-will-the?utm_campaign=post-expanded-share&utm_medium=post viewer&triedRedirect=true

Certainly hope you're right for my family's sake!

Plenty of beaten down software names that could outperform in 2026: Workday, Adobe, Constellation, Salesforce, SAP, Tyler Tech etc.

I wonder how well a basket of beaten down software stocks will do from here (following @E. Nashton's approach from the 2023 thread) Workday, Adobe, Constellation, Salesforce, SAP etc. to name a few

~ +7% CAD terms in 2025. Very high concentration in Constellation Software. Let's see what 2026 brings

Merry Christmas and happy holidays!

Any particular reason why you prefer GE / SAFRAN over TDG / HEI? Thanks!

Not completely related but TD Direct Investing has a special deal going on right now. I believe the maximum reward is $ 5000 CAD: For a limited time only, transfer $10,000 or more to TD Direct Investing and get up to 2% cash back.

https://joincolossus.com/episode/nvidia-v-google-the-economics-of-ai/

Ilya Sutskever – We're moving from the age of scaling to the age of research https://www.dwarkesh.com/p/ilya-sutskever-2

truly a lifelong learner

small add to SGN.WA last week

Ben Evans, AI eats the world slide deck: https://www.ben-evans.com/presentations

"AI has been compared to various historical precedents: electricity, industrial revolution, etc., I think the strongest analogy is that of AI as a new computing paradigm (Software 2.0) because both are fundamentally about the automation of digital information processing. If you were to forecast the impact of computing on the job market in ~1980s, the most predictive feature of a task/job you'd look at is to what extent the algorithm of it is fixed, i.e. are you just mechanically transforming information according to rote, easy to specify rules (e.g. typing, bookkeeping, human calculators, etc.)? Back then, this was the class of programs that the computing capability of that era allowed us to write (by hand, manually). With AI now, we are able to write new programs that we could never hope to write by hand before. We do it by specifying objectives (e.g. classification accuracy, reward functions), and we search the program space via gradient descent to find neural networks that work well against that objective. This is my Software 2.0 blog post from a while ago. In this new programming paradigm then, the new most predictive feature to look at is verifiability. If a task/job is verifiable, then it is optimizable directly or via reinforcement learning, and a neural net can be trained to work extremely well. It's about to what extent an AI can "practice" something. The environment has to be resettable (you can start a new attempt), efficient (a lot attempts can be made), and rewardable (there is some automated process to reward any specific attempt that was made). The more a task/job is verifiable, the more amenable it is to automation in the new programming paradigm. If it is not verifiable, it has to fall out from neural net magic of generalization fingers crossed, or via weaker means like imitation. This is what's driving the "jagged" frontier of progress in LLMs. Tasks that are verifiable progress rapidly, including possibly beyond the ability of top experts (e.g. math, code, amount of time spent watching videos, anything that looks like puzzles with correct answers), while many others lag by comparison (creative, strategic, tasks that combine real-world knowledge, state, context and common sense). Software 1.0 easily automates what you can specify. Software 2.0 easily automates what you can verify."

Probably from Todd or Ted

OP top ticked the market when he made this post. Look at PLTR, it peaked on Nov 3 (for now ...)

My winner is also a falling knife right now at the moment (Constellation)

My bet would be that lawrence continues his +5 purchases

End of an era

If CSU is 100 TOI - 25 SGN - 25 LMN - 8 ^ Not how I'd allocate it if I were starting a portfolio from scratch. Mainly just turned out this way and haven't sold much because of tax implications. Lumine shares are from the spin + slight adds at around 14 dollars. I haven't added to it since. It also seems the most pricey to me. SGN is the more recent purchase. Started adding to it in March of this year. Looking to add more to it at these levels as it seems the most promising.