I’m a pretty big generalist professionally. I’ve done software engineering in a broad category of fields (Game engines, SaaS, OSS, distributed systems, highly polished UX and consumer products), while also having the experience of growing and managing Product and Design teams. I’ve worn a lot of hats over the years.
My most recent role I’m working on a net new product for the company and have basically been given fully agency over this product: from technical, budget, team, process, marketing, branding and positioning.
Give someone experienced like me capital, AI and freedom and you absolutely can build high quality software and a pretty blinding pace.
I’m starting to get the feeling than many folks struggling with adopting or embracing AI well for their job has more to do with their job/company than AI
Yeah I absolutely see it every day. I think it’s useful to separate the research/planning phase from the building/validadation/review phase.
Ticket trackers are perfect for this. Just start with asking AI to take this unclear, ambiguous ticket and come up with a real plan for how to accomplish it. Review the plan, update your ticket system with the plan, have coworkers review it if you want.
Then when ready, kick off a session for that first phase, first PR, or the whole thing if you want.
But planning like this is absolutely something AI can do. In fact, this is exactly the kind of thing we start with on our team when it comes to using AI agents. We have a ticket with just a simple title that somebody threw in there, and we asked the AI to spin up a bunch of research agents to understand and plan and ask itself those questions.
Funny enough, all the questions that you posed are things that come up right away that the agent asks itself, and then goes and tries to understand and validate an answer, sometimes with input from the user. But I think this planning mechanism is really critical to being able to have an AI generate an understanding, then have it be validated by a human before beginning implementation.
And by planning I don't necessarily mean plan mode in your agent harness of choice. We use a custom /plan skill in Claude Code that orchestrates all of this using multiple agents, validation loops, and specific prompts to weed out ambiguities by asking clarifying questions using the ask user question tool.
This results in taking really fuzzy requirements and making them clear, and we automate all of this through linear but you could use your ticket tracker of choice.
Absolutely. Eventually the AI will just talk to the CEO / the board to get general direction, and everything will just fall out of that. The level of abstraction the agents can handle is on a steady upward trajectory.
If AIs can do that, they won’t be talking to a CEO or the board of a software company. There won’t be a CEO or a board because software companies won’t exist. They’ll talk to the customers and build one off solutions for each of them.
There will be 3 “software” companies left. And shortly after that society will collapse because of AI can do that it can do any white collar job.
I think there are multiple conversations happening that are tying to converge on one.
On one hand, LLMs are overhyped and not delivering on promises made by their biggest advocates.
On the other hand, any other type of technology (not so overhyped) would be massively celebrated in significantly improving a subset of niche problems.
It’s worth acknowledging that LLMs do solve a good set of problems well, while also being overhyped as a silver bullet by folks who are generally really excited about its potential.
Reality is that none of us know what the future is, and whether LLMs will have enough breakthroughs to solve more problems then today, but what they do solve today is still very impressive as is.
Yes, exactly. There is a bell curve of hype, where some people think autoregressive decoders will lead us to AGI if we just give it the right prompt or perhaps a trillion dollars of compute. And there are others who haven’t even heard of ChatGPT. Depending on which slice of the population you’re interacting with, it’s either under or over hyped.
Just wanted to chime in and say how appreciative I’ve been about all your replies here, and overall content on AI. Your takes are super reasonable and well thought out.
Man! I can’t agree more. It does seem foreign right now, but I truly do believe edge computing will become another “CDN” type abstraction, but it will take time for folks to catch up.
Can’t wait for the day that projects like litefs are just a default that nobody knows about, lol.
Go from “technology nobody knows about” to “technology nobody knows about, but runs the world.”
While there are lots of cloud providers also trying to be edge providers, I would argue that "The Far Edge" is a great opportunity to improve and develop infrastructure that is easier to run on your own hardware.
What worked for cloud won't work for edge in most cases. Having to do processing locally means processing on your own hardware.
We've seen this as the reason a lot of companies are adopting tools like NATS.io to be more cloud agnostic and/or be able to practically run at the Edge.
I previously worked for a company that empowers entrepreneurs and experts to build a business off their knowledge, and have learned a lot over the years of what's effective what's not so helpful.
The biggest factor for successful knowledge businesses was whether the person self-identified as an entrepreneur. It influenced how they saw their audience and engaged with them.
Ultimately you need to focus on both -- building and audience and a business. But there are far too many "creators" out there that are only interested in building an audience, and I personally believe, depending on the subject matter/industry, that it can be confusing and detrimental to not be engaging in both activities.
Have you looked at nats.io? High performance messaging with a flexible persistence layer. Servers can be meshed via leaf node connections. Perfect for IoT and edge
NATS definitely tries to solve for that end to end experience, where you can have NATS simultaneously driving websocket connections as well as backend connections in a secure and performant way. I’ve personally had a ton of fun making interactive applications with NATS, it scales reliably and is really fun to work with
I’m a pretty big generalist professionally. I’ve done software engineering in a broad category of fields (Game engines, SaaS, OSS, distributed systems, highly polished UX and consumer products), while also having the experience of growing and managing Product and Design teams. I’ve worn a lot of hats over the years.
My most recent role I’m working on a net new product for the company and have basically been given fully agency over this product: from technical, budget, team, process, marketing, branding and positioning.
Give someone experienced like me capital, AI and freedom and you absolutely can build high quality software and a pretty blinding pace.
I’m starting to get the feeling than many folks struggling with adopting or embracing AI well for their job has more to do with their job/company than AI