Recent submissions

Comment · 5 months ago
Hope you never want to take diff backups
Comment · 5 months ago
I believe OP is talking about new sessions or after compaction. He’s getting at the fact that LLMs are stateless and have to rediscover your codebase on every new session.
Comment · 5 months ago
For me, the concern about SQLite has never been if the database engine itself is “reliable for real data”, but that storing data on a single node is not “reliable for real data”. Performance aside, what you are positing is no different than dumping everything to a text file on disk. What happens if that VM dies?
Comment · 7 months ago
There’s no better option today because it’s impossible to make it a better experience. That machine at home will need upgrades, it could fail, it costs thousands, it sucks lots of power. There is no mass market appeal.
Comment · 7 months ago
What you’re describing is more likely to manifest as a proprietary product from someone like Samsung or Ring (likely both!) than an open standard AI server that integrates with everything in your home automatically. This is exactly like what we have today with security systems and smart appliances. You have managed services and you have Home Assistant in your homelab.
Comment · 7 months ago
I don’t think there’s anything different between what you’re suggesting and a homelab. Most people do not have a homelab and are happy to offload services like photo storage or security to remote providers.
Comment · 7 months ago
Spend 5 minutes looking up how to make a chat bot and be amazed how Telegram is really the only option. I was dumbfounded when rolling my own agent.

iMessage is proprietary. WhatsApp charges you. Unofficial APIs exist, sure, but not my cup of tea.

Then you have Discord or Slack, which are pretty heavyweight when all you want is a simple chat interface.

Telegram makes it SO easy. Bots are first class resources on Telegram and they make them so easy to use.

Comment · 7 months ago
Bun is a full fledged JavaScript runtime! Think node.js but fast
Comment · 7 months ago
Sounds like OP did some pretty cool engineering to make this run performantly. Definitely not your run of the mill AI slop.
Comment · 8 months ago
Seems like a great fit - kinda surprised it didn’t happen sooner. I think we are deep in the valley of local AI, but I’d be willing to bet it breaks out in the next 2-3 years. Here’s hoping!
Comment · 8 months ago
who knows when Apple decides to enter the game, but they will absolutely crush the personal agent market when they do.
Comment · 8 months ago
My pessimism is mostly rooted in the VC economics of it all. The vision is great, but its a busy space and there's no actual product or business. They basically wrote the guy a check to build the spaceship in space.
Comment · 8 months ago
Ignoring the VC economics and awful name, I won’t be as pessimistic as everyone. I see the vision.

That said, nobody knows what the AI future looks like. Entire’s entire thesis is a solution for something we don’t even know we need. It’s a massive bet and uphill battle. Traditionally, dev tool success stories come from grassroots projects of developers solving their own problems and not massive VC funded efforts that tell you what you need to do.

Comment · 8 months ago
> The initial excitement of LLMs has significantly cooled off, the model releases show rapidly diminishing returns if not outright equilibrium and the only vibe-coded software project I've seen get any actual public use is Claude Code, which is riddled with embarrassing bugs its own developers have publicly given up on fixing. The only thing I see approaching any kind of singularity is the hype.

I am absolutely baffled by this take. I work in an objectively high stakes environment (Big 3 cloud database provider) and we are finally (post Opus 4.5) seeing the models and tools become good enough to drive the vast majority of our coding work. Devops and livesite is a harder problem, but even there we see very promising results.

I was a skeptic too. I was decently vocal about AI working for single devs but could never scale to large, critical enterprise codebases and systems. I was very wrong.

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