@aiDotEngineer ins & outs for ai engineering
(observation NOT endorsement)
ins: memory, auto-research, knowledge graphs, open models, vertical ai
outs: embeddings/ RAG, mcp, token counts as metric, prompt engineering, code reviews, public benchmarks
evergreen: evals, skills, permissions, governance
@chrislakin@LighthavenPR Most conferences: Way too focused on talks ; hard to meet people organically; app doesn’t prefill your profile so hard to find ppl to talk to; also no food or drink.
Apparently from evolutionary biology humans are biologically evolved to be serial monogamists. My armchair theory is that both in polyamorous and monogamous relationships you keep falling in love over and over, it’s just with polyamory it’s with different people and with monogamy it’s the same person again and again.
When done well, a monogamous relationship can feel like having a polyamorous relationship with one person.
The key to unlocking this is developing a specific type of skill in romantic imagination and creative perception.
When we’re first talking in love with someone, our imagination effortlessly goes into overdrive.
All our fantasy and limerence naturally casts our partner in a romantic light.
There’s a sense that we get to fall in love with them once for free.
But to keep the relationship maximally alive, in my experience, we must fall in love with them over and over again.
This repeated falling in love is a kind of skill.
We can constantly look at our partner anew, notice how they are growing and evolving, and learn how to fall in love with each of these new versions of them as they arrive.
This is how a monogamous relationship can start to take on the flavour of polyamory over time.
There are so many different versions of my partner that I’ve fallen in love with upon meeting them.
There are also subtle aspects of her that were always there but only embolden themselves into visibility as familiarity grows.
Each of these aspects is exciting in a different way, and each is nested within one other.
It’s what for me, keeps the relationship fresh and allows the puppy-dog flavour of love to stick around long after the honeymoon phase is over.
does anyone else find it strange that the US is AI pilled and China isn't?
Is it more likely that in all of China there is no one who thinks deeply enough about implications of self-improving ai, or that we collective are in psychosis about machine that can kill us all?
My take 24 hours after Fable 5:
Your organization will likely not scale with the exponential curve of AI.
I'l just come out to say: This should be a wakeup call for engineering teams.
Set up your cloud software factories. Now.
Models can now fix impossible bugs, UI-test the hardest flows, writing extremely good code, etc. I have't opened Datadog manually as far as I can remember.
AI should be the first-line defense for bugs and feedback. Humans should only look at PRs after an AI has already reviewed it. AI should generate screen recordings of any PR before a human eye even reaches it. The agent should just prompt itself most of the time.
Ex. (pictured) our ui feedback channel manages itself, creates tickets, assigns itself automatically
You might also be worried about cost. Anthropic, OpenAI, and other labs will likely continue to put out bigger and more expensive models. But, we will also continue to get more capable small models. Not everything will need the smartest models. It's about having the organizational harness in place to continue taking advantage of this rising tide.
Moreover, if you use Devin, we've already optimized our harness a bit, and Fable is actually only ~40% more expensive in practice (vs the 2x people assume). I'm honestly pleasantly surprised - it might be higher ROI than you think.
Anyway, if you take anything away, engineers shouldn't be manually picking up tickets, humans shouldn't be digging into logs themselves, rethink what you do with your time that shouldn't just be an AI. We need to rethink what humans spend their time going.
moving to SF and working on AI seems like the obvious best high level career path
I’m kinda surprised more software engineers aren’t doing this
Most of the people I know and most of my coworkers seem completely fine not doing this which seems odd