James Dyson is 79 and still finding ways to apply hardcore engineering to random consumer products.
He was in fine form pitching Dyson’s new $499 CameraJet toothbrush:
“The first toothbrush with a camera. The first toothbrush with a jet. The first toothbrush to find the space between the teeth and floss while you brush.”
Dyson says it created an ML algorithm trained on 470,000 mouth images to recognize the gaps to clean with water flossing.
a skill people at Anthropic have been using a lot recently: ELI5
/eli5 <what you want explained>
"explain like I'm someone who knows nothing about this topic, using a HTML artifact with big pictures and few words"
this is actually insane
> be tech guy in australia
> adopt cancer riddled rescue dog, months to live
> not_going_to_give_you_up.mp4
> pay $3,000 to sequence her tumor DNA
> feed it to ChatGPT and AlphaFold
> zero background in biology
> identify mutated proteins, match them to drug targets
> design a custom mRNA cancer vaccine from scratch
> genomics professor is “gobsmacked” that some puppy lover did this on his own
> need ethics approval to administer it
> red tape takes longer than designing the vaccine
> 3 months, finally approved
> drive 10 hours to get rosie her first injection
> tumor halves
> coat gets glossy again
> dog is alive and happy
> professor: “if we can do this for a dog, why aren’t we rolling this out to humans?”
one man with a chatbot, and $3,000 just outperformed the entire pharmaceutical discovery pipeline.
we are going to cure so many diseases.
I dont think people realize how good things are going to get
When a team fully activates on agents and each engineer is shipping 10+ PRs a day minimum, the entire traditional SDLC collapses.
Code review backlog, keeping up with docs, keeping CI and the merge queue fast, planning, visibility, etc.
You end up redesigning the whole SDLC.
Little hack I’ve discovered for myself, which should have been very obvious tbh, is offloading tasks on my todos to agents. If you’re in a meeting or attending to something else, an agent should be working on something for you in parallel 👌🏽
Unpopular opinion:
Unless you’re just prototyping, you should aim to understand as close to 100% of production code generated by LLMs.
Yes, all of it.
Effective mental models are still important for humans to sustainably maintain and evolve a codebase via prompting alone.
Google’s killing right now with all the AI tools they’re releasing. I have a google 1 sub and honestly I’m beginning to question the need for my chatgpt sub. Looks like I might cancel that this year 🤔 Claude code still killing it for pure coding tasks 👌🏽👌🏽
Treat AI-generated code as a draft.
It can write the first version, but never outsource the reading. No human review means no reliable trace from behavior back to intent.
When you stop reviewing AI drafts, you stop knowing why the code works at all.
Now I really know the importance of marketing. I don’t know what temu is or much about the business but with all I’ve seen on insta, I want to patronize them