Hexar AI is your intelligent troubleshooting companion for any machine, from robots to industrial systems to consumer devices. It understands how every component connects and interacts, enabling it to reason through complex problems like an expert engineer and guide you step by step to the solution.
Unlike traditional AI tools that only process text, Hexar AI understands systems along with the interplay between hardware and software. It builds a digital brain of your machine that you can explore, modify, and learn from, turning every troubleshooting session into a smarter, faster, and more insightful experience.
To every student who has been applying for months and hearing nothing back. I see you and I want to share the one thing that has made the biggest difference for me.
Learn to network. Genuinely. Not the performative kind where you send a templated LinkedIn message and wait. The kind where you walk into a room, introduce yourself to a stranger, and have a real conversation.
Here is the truth nobody tells you when you are job hunting right now. Hundreds of people are sending the same AI generated cover letters to the same job postings. Recruiters know it. Hiring managers know it. The applications blur into one another.
What does not blur is a human being who showed up to an event, asked thoughtful questions, and followed up with something personal and genuine.
We are living in an era where AI can write your email, polish your CV, and fill in your application in seconds. Which means the one thing AI cannot replicate is becoming your biggest advantage. Real relationships. Real conversations. Real presence.
Over the last two years I have been doing exactly this. Hackathons in London, robotics workshops in Oxford. Rooms full of strangers from sales, tech, academia, and everything in between. Every single one of those rooms taught me something a job board never could.
I wrote about that experience and what I learned from it. If you are trying to figure out where to start, how to build confidence walking into unfamiliar rooms, and why showing up consistently changes everything. Here is the article on same - https://t.co/ds9IXTRd0x
The job market is hard right now. But the people who stand out are not the ones with the most optimised profiles. They are the ones willing to be in the room.
I have been spending a lot of time recently working with knowledge graphs, and something clicked.
Coding was the first use case where AI really delivered. Not just because of the models, but because code already had something most industries don't: a well-established relational graph. Functions call functions. Dependencies map to dependencies. The structure was already there. The AI just learned to navigate it.
That's the unlock.
LLMs don't struggle with intelligence. They struggle with context. They don't know how your business connects internally, how your data relates across systems, or what your domain-specific relationships actually look like.
Knowledge graphs solve this. They give the model a map.
But here's what I think gets missed: the knowledge graph for a hospital looks nothing like the one for a law firm, a bank, or a manufacturing plant. The relationships, the entities, the hierarchies are all different.
And that's exactly the point.
The industries that build their own domain-specific knowledge graphs will be the ones that extract the most value from LLMs. Not because they got a better model. Because they gave the model something to reason over.
We're still early. But this is the layer that will drive real enterprise AI adoption. I have written a substack article on the same. Do check it out.
https://t.co/efg6UISSHG
Everyone online talks like AI agents are about to replace civilization tomorrow.
Then you walk into a real office and people are still fighting Excel sheets, legacy systems, approvals, and printer issues.
AI is revolutionary and overhyped at the same time.
Beautiful paradox.
As a child, I always thought I should have been born rich. But growing up made me realise the real privilege is experiencing the journey itself.
Happiness comes from going from A to Z. If you are already at Z from the beginning, it becomes hard to find meaning beyond it.
@rcwhiteley For me personally cursor is better. $20 subscription is sufficient. As I am not building things from scratch. Making changes and adding features into our 1 year old repo. So don’t need access to most powerful model all the time.