goodthings

@sandeepnailwal Based

LLM based AI is NOT conscious. I co-founded a company literally called Sentient, we're building reasoning systems for AGI, so believe me when I say this. I keep seeing smart people, people I genuinely respect, come out and say that AI has crossed into some kind of awareness. That it feels things, that we should worry about it going rogue. And i think this whole conversation tells us way more about ourselves than it does about AI. These models are wild, i won't pretend otherwise. But feeling human and actually having inner experience are completely different things and we're confusing the two because our brains literally can't help it. We evolved to see minds everywhere and now that wiring is misfiring on language models. I grew up in a philosophical tradition that has thought about consciousness longer than almost any other, and this is the part that really frustrates me about the current conversation. The entire framing of "does AI have consciousness?" assumes consciousness is something you build up to by adding more layers of complexity. In Vedantic philosophy it's the opposite. You don't build toward consciousness. Consciousness is already there, more fundamental than matter or energy. Everything else, including computation, is downstream of it. When someone tells me AI is "waking up" because it generated a paragraph that felt real, what they're telling me is how thin our understanding of consciousness has gotten. We've reduced a question humans have wrestled with for thousands of years to "did the output sound like it had feelings?" It's math that has gotten really good at predicting what a conscious being would say and do next. Calling that consciousness cheapens something that Vedantic, Buddhist, Greek and Sufi thinkers spent millennia actually sitting with. We didn't build something that thinks. We built a mirror and right now a lot of very smart people are mistaking the reflection for something looking back.

@smashleybelle Significantly. Likewise, Ash 🤙

@Goodthings But significantly more important Hope all is well goodthings

When exploration becomes free, judgment becomes scarce.

AI commodifies exploration.

@Tyler_Did_It It always goes wrong. x.com/goodthings/sta…

When vibe coding goes wrong

@ujjwalscript I would submit that it's not technical debt, but cognitive debt that is going to lead to the nightmare. We saw a glimpse of that this week with the internal Amazon meeting around the outages that occurred as a result of AI-generated code.

Unpopular Opinion: We aren't building the future 10x faster with AI. We are just generating legacy code 10x faster. Everyone is currently bragging about developer velocity. "I built this entire backend in a weekend!" "AI wrote 80% of my codebase!" But here is the reality check we are ignoring: Code is a liability, not an asset. If an AI tool spits out 1,000 lines of functional boilerplate in five seconds, that is still 1,000 lines that a human being has to read, review, secure, and maintain when the dependencies inevitably break next year. We are treating code generation like a pure productivity win, but we are optimizing for the wrong metric. The bottleneck in software engineering was never how fast we could type. The bottleneck has always been comprehension, architecture, and maintenance. If we don't shift our focus from "generation speed" to "architectural sanity," the tech debt of the next five years is going to be an absolute, unmaintainable nightmare.

Context Loops is free and open source. Docs and framework: context-loops.vercel.app If you're building with AI agents, this shows how to structure project context so work carries across sessions instead of resetting every time.

A lot of people using AI right now aren't becoming more productive. They're just spending tokens. They open a new chat, re-explain their project, get some output, and start fresh the next time. It feels like progress. It isn't. I know because I did this for months. Most people miss two fundamental constraints of LLMs: they don’t remember anything between sessions, and even within a session their memory is limited by the context window. Every new chat starts from zero. No memory of your decisions. No awareness of what you already tried. No understanding of what your goals are. The result is chaos. The AI contradicts itself. It re-suggests ideas you rejected last week. It feels like onboarding a new hire every morning who never read the docs. After eight months building a production app with AI and getting this wrong more times than I'd like to admit, I stopped blaming the tools and started designing a solution. The result is Context Loops, an open-source framework that structures your project context so AI agents can actually work across sessions. Tickets. Session logs. Sprint records. Decision logs. All living in your repo, all feeding into every future session. Your work carries over instead of disappearing. The shift it creates is simple: you stop being a passive user of AI and start orchestrating it. If you're building with ChatGPT, Cursor, Claude, or Copilot and your sessions feel like they reset every day, this is the fix I wish I had eight months ago. The framework is free and open source. Full docs in the comments if you want to try it.

The Amazon internal engineering review that leaked this week is the first of many signals that the AI narrative is way ahead of reality. Context is all you need (but context ain't cheap).

This is such a great analogy and sage advice from @KiteVC Machines can't replaces humans...yet. And they may never fully be able to. However, they will replace many of the tasks we have to do today. Learning fundamentals allows us to be creative. And creativity is something that AI is going to have a very difficult time beating humans at. Never stop learning ⚡️

If you've ever had to train someone to takeover your job as you leave for a new one you will understand more about the challenges of AI taking over entire industries than any think piece ever could.

Full breakdown of why this is a fundamental constraint of modern AI and is likely to keep happening — and critically, what teams can do about it: context-loops.vercel.app/context-engine…

@Conquistador_86 These people gonna reverse course by Q3 earnings.

@Goodthings 🧠

“Don’t worry about token costs” is the AI bro’s version of “never stop clicking” How’d that work out for the meme coin bros?

@westoque @reidhoffman @NotionHQ @ivanhzhao This.

@reidhoffman @NotionHQ @ivanhzhao i disagree. easy to say to burn tokens when you have resources. i think it's actually more impressive to think of ways to be innovative with LESS tokens.

.@NotionHQ's Founder, @ivanhzhao: Stop trying to save costs when you're implementing AI. It's the easiest way to lose the race. More on how Ivan thinks about staying ahead of the AI curve:

@BryanXBT Send me a link to his work 🙏

@Goodthings lol snooptoshi

@Yura__eth Let me know if you try it out 🤙

@Goodthings yo finally someone built the memory we all needed

@BryanXBT Snooptoshi or Snoop Dogg?

@Goodthings Nice! Sounds like you’re working on the same problem as snoop is right now with imember

@emollick The answer is context. But context is expensive. I created a framework for the individual or small teams. Taking this framework to scale is a very interesting and valuable problem set. Would be curious to know what you've seen out in the wild. context-loops.vercel.app

The "how does AI improve individual productivity" discussion is much less interesting than "how does AI improve organizational efficiency?" We have a lot of answers to the former, but it will always get eaten by the latter if we don't experiment with new approaches to organizing.