Beyond Automation: How to use First Principles to Find AI's Next Big Disruptions?
Hey PH Fam!
We're all seeing AI transform industries, but are we looking deep enough? I've been thinking about applying first-principle thinking to identify areas truly ripe for AI disruption – going beyond automating existing tasks to fundamentally reimagining solutions.
Instead of asking 'How can AI make X better?', what if we ask:
What is the core human need X is trying to solve?
What are the fundamental limitations of current solutions, pre-AI?
If we were to solve this need from scratch today, with current AI capabilities (LLMs, generative models, etc.) as a core building block, what would it look like?
To get the ball rolling, here are a couple of 'first-principle' observations that point to potentially massive opportunities:
First-Principle Observation: Many crucial human needs for guidance, support, or specialized knowledge are constrained by the 24/7 availability and linear scalability of human experts. While the need can arise anytime, access to the right expert in the moment of need is often impractical.
Use-Case Example that highlights this: Think about a person needing a critical, unexpected medical emergency at 2 AM and needing immediate, high-level specialized healthcare-service. Or consider someone needing instant, personalized support to process a difficult emotional situation as it happens, rather than waiting for a scheduled appointment.
The idea here isn't to jump to AI solutions yet, but to use these kinds of fundamental observations to pinpoint areas where current limitations create significant unmet needs or inefficiencies.
What other core human needs, or fundamental limitations in how things are currently done, can we identify that might be completely re-architected if AI capabilities were a foundational assumption?
Replies
Really enjoyed this — especially the emphasis on using first principles to rethink what AI should be helping us build, not just how fast we can automate existing workflows.
As a team building an AI tool aimed at helping non-coders turn ideas into actual products, we’ve found that the real bottlenecks aren’t just in writing code — they’re in connecting the pieces that make a product work: user data flows, payment logic, real-time content, meaningful state.
In that sense, AI isn’t just a code generator — it's a systems thinker (or should be). The question isn’t “Can it build a UI?” — it’s “Can it assemble all the moving parts of a business into something functional and coherent?”
This post made me realize how often I still fall into the trap of “automating the known” instead of asking what the outcome really requires 🤔.
@yeedoong88 So glad the 'first principles' thinking resonated.
You've perfectly articulated the shift: AI not just as a task-doer, but a 'systems thinker.' Your experience with 'connecting the pieces' for non-coders is a prime example of that deeper challenge.
It's fascinating how this applies broadly – whether it's assembling business logic, or as I touched on in my post, understanding the 'system' of human emotion for providing meaningful support. I'm finding this particularly true in my work on AI for workplace well-being.
Really appreciate you sharing that it prompted a pause on 'automating the known' – that's a win for first-principle thinking right there! 👍
Since we are talking first pricncipls, there are a few ways we can go about this.
First, we can start with Maslow's Hierarchy of Needs... The most obvious uses cases are at the top, starting with self actualisation, e.g. AI tutors that will help anyone become at expert at something at lighning speed, or at least to achiev something that was very complex (vide coding for example).
As we go down in the hierarchy, we will see other needs covered. For example, social media has paradoxically created a lot more looniness and less sense of connection with others. A.I could potentially help us here by covering tasks that don't require human to human interaction, while the humans get real social time.
Even further down, we can ask ourselves, how can AI help us feel safer?
etc...
Another way of looking a first principles is the communication tech waves. Major advances in tech have shifted the way we communicate with each other. For example the invention of the written word, then the papyrus, then the press, then the radio, telephone, internet, etc... How can AI help us be more effective at communicating with each other? Translation apps? Brain to brain communication? Something else?
What are your thoughts?
@dg_ I really like how you've mapped this to Maslow's Hierarchy – it’s a perfect way to think from first principles. Your question, 'how can AI help us feel safer?' particularly resonates with me.
Beyond physical safety, there's a huge opportunity for AI in fostering psychological safety. I'm exploring similar themes in how AI can help manage emotional states and reduce interpersonal friction, especially in professional settings. It's fascinating to think about AI not just for task automation at the top of the pyramid, but for these foundational human needs too.
Thanks for adding these valuable perspectives to the discussion!
@hanselh I'd love to hear more about what you are planning to do around "managing emotional states and reduce interpersonal friction"... Loneliness is becoming a trus social problem is the Western world, and I am afraid AI might actually increase it.
What do you have in mind?
@dg_ Thanks for the follow-up! You've hit on a really important point about loneliness and the potential downsides of AI if not implemented thoughtfully.
My thinking around "managing emotional states and reducing interpersonal friction" is currently centered on providing a private, AI-powered space where individuals can first process and vent their raw emotions without judgment. This is where the idea for Venting Space (CurhatPal) comes in – it acts as a sort of digital confidant. The initial phase is about that crucial emotional release and gaining clarity in a safe environment.
However, to your point about human connection, the aim isn't to replace it but to better equip individuals for it. So, after the venting or processing phase, the idea is to explore a 'resolution mode.' Here, the AI could help the user strategize on how to approach a difficult conversation, draft a more constructive message, or brainstorm ways to resolve the underlying issue that caused the friction. It's about using AI for that discreet initial processing, then gently nudging towards constructive engagement or resolution in their human-to-human interactions, if and when they feel ready.
It's definitely an evolving concept! Finding the right balance is delicate, and AI capabilities are constantly improving, which opens up new possibilities for how this interaction can be nuanced and genuinely helpful. The goal is to empower individuals, not isolate them further.
Kalyxa
Love this first-principles thinking. That 24/7 expert access example really stands out—so many moments happen outside normal hours.
For me, personalized learning feels ripe for this too—AI that adapts to how you learn and even your motivation.
What do you see as the biggest challenges in rethinking these problems with AI?
@parth_ahir Thanks, Parth! I'm glad the '24/7 expert access' idea resonated, and you're spot on – personalized learning is definitely another prime candidate for a first-principles AI rethink.
To your question about challenges: One of the biggest I see is the fascinating tension where AI could get so effective at certain tasks that it inadvertently replaces the human learning process itself.
For example, imagine real-time AI translation becoming so seamless that the motivation or necessity for deep language learning diminishes significantly for many. It's that balance between AI as an enabler versus a complete substitute for skill acquisition that we'll need to navigate carefully.
What are your thoughts on striking that balance?