jamestimmins

Its reasonable to dislike a bad product experience, but its strange to draw a conclusion of AI altogether based on a tool with limited usage (I've never heard of it).

That's like saying smart watches are useless based on trying out the smart watch made by will.i.am's tech company rather than Apple's.

This is a good point about quality of life. I focused on money in my original comment, but I've heard a lot of people complain that unions have kept them working with their worst coworkers. That alone is a dealbreaker for me.

I've been laid off. It was fine because software is literally the most marketable skill in the world.

Edit: But also, this was a pre-profit VC-backed company. If those companies can't lay people off, it's not like you make good money with more job security. Either the company just has less runway (so I still lose my job, just later and with everyone else) or they adapt by hiring fewer people at lower salaries.

As a California tech worker (where the article is focused), I have zero interest in joining a union and firmly believe that much of what has been possible as a tech employee (high paying, interesting career) is in part because we don't have unions, and instead employees own equity and get valuable skills.

Modern tech workers arguably have the best career deal in the history of humankind. I see no upside in killing the goose with the golden egg.

AI seems to struggle most when it has to make decisions with lots of trade-offs, especially where the context or implications of various decisions are nested, which is presumably why it struggles to write full software systems that are well-designed.

By comparison, financial advice is pretty simple, and there is a universally agreed-upon approach that most people should follow to maximize long-term financial health.

The issue I have with loops is that for truly complex work, where I care about building a generalized solution for a complex problem, the agents frequently reward hack and end up burning indefinitely without finishing until I step in.

Curious how you're addressing this

Telemetry tooling for local Claude/Codex usage so I can analyze old sessions and fill tooling gaps, make sure I'm using the right models for various tasks, update my processes, etc.

I've also replaced Linear with a local sqlite-backed tool, added tooling to speed up code nav, and am building "no-slop", a tool for enforcing architectural guidelines on vibe-coded projects.

This looks awesome. I’m the ideal customer for this and am delighted it exists.

My first thought was my finance professor telling us that companies always raise with equity when they think their equity is overvalued.

The responses to this are wild. I have worked with and built smaller systems like this and it is an incredible speed up.

So much reflexive hate against a genuinely transformative tech. Yes AI has annoying people and grifters, but it is genuinely incredible at some things and finding out how to use it effectively within a company is the most fun I’ve had in my career.

The issue of it burning through tokens grepping around should be fixed with language server integration, but that’s broken in Claude Code and the MCP code nav tools seem to use more tokens than just a home-built code map in markdown files.

Haven’t done robotics, but this approach is also much more feasible now with AI, which I appreciate.

Building a woodworking extension for SketchUp!

I took a course in using it for woodworking, and just kept thinking “this should all be a single extension”, so I’ve been building that.

I keep thinking about two very different cases wrt existing platforms:

1. My cousin who works for an enterprise real estate SaaS company. He said their main product has iirc 10-20,000 database tables.

2. Evernote users had famously little overlap in which features they used. Everyone use a slightly different subset of Evernote tools.

I wonder if you could create a 2x2 grid of these two scenarios to determine a SaaS tool's likelihood of being replaced with AI.

- Complex Data Model + High feature adoption: Low risk of AI

- Complex Data Model + Low feature adoption: Medium risk short term. High long term.

- Simple data model + High feature adoption: High long term risk risk, but limited ability to grow accouts

- Simple data + low feature adoption: Very high risk

1. I was prepared my to roll my eyes, but I actually think the framing is correct. AI hasn't replaced legacy vendors yet, but companies are now in a position to at least assess whether "Cheap External Tool + AI" beats "Expensive Tool", which starts to compress margins for existing tooling.

2. A suspicious number of "It's not X, it's Y" in this piece.

Jonathan Haidt recently made the point on Ezra Klein's podcast that while adults can take a break from phones and reset their attention/hormones in a couple of weeks, we don't know what impact similar addiction has on a developing mind. It's possible the addiction sets in much deeper.

I'm sympathetic to folks who grew up shaped by this. Not for nothing, but The Conversation also has a compelling start/end, but has a long, arguably slow, boring middle. So it's like being forced into withdrawal on hard mode.

Not snack bars, but tiny bars were absolutely one of my favorite things in Japan. The streets of 3-5 seat bars felt incredibly special and distinct from anything I've seen in the US, regardless of the presumably high % of their business that came from tourists.

I think it's pretty unlikely that they visit bars who don't want the tourists.

I often go on food tours in new cities (e.g. Secret Food Tours) and the restaurants they visit seem to like the consistent revenue stream during off-hours.

Yes at some point innovative software and naming are at cross purposes, and if your naming gets too extreme ultimately that will get all of the attention.

I actually love the idea of totally new naming schemes for experimental software.

Certain name types are so normalized (agent, worker, etc) that while they serve their role well, they likely limit our imagination when thinking about software, and it's a worthwhile effort to explore alternatives.

Excellent movie. Worth noting that it was written by Tony Gilroy, who created Andor and cowrote The Bourne Identity, so if you enjoyed those you're likely to enjoy this.

My brother once suggested that there are probably bits of code/algorithms that would be world changing if they were released in academic journals, but instead were written by some unknowing programmer in an afternoon for their job coding embedded systems for refrigerators.

This particular example may be unlikely, but it's a very fun idea.

I've been playing with the hypothesis that if information is controversial/surprising and targeted at laypeople, it is almost guaranteed to be misleading or outright false.

The only way to convincingly make the case for new information is with pretty rigorous technical arguments, which is fundamentally at odds with a lay audience. If someone has those rigorous technical arguments, they'd be making them in journals to a technical audience, and the results would slowly become consensus.

Obvi there are counter-examples, but as a general rule I think this is far more true than not. Which is why if you learn from Forbes that someone is close to cracking AGI, you can almost outright assume this is untrue.

This could be the premise for a fun project based infra learning site.

You get X resources in the cloud and know that a certain request/load profile will run against it. You have to configure things to handle that load, and are scored against other people.

By this point, we should assume that all companies with sensitive data that could theoretically help solve crime will be accessed by the government as a rule.

That's just being a realistic technology user in 2025.

For all the hate that Google (rightly) gets for some of their work in other domains, I appreciate that they continue to put major resources behind using AI to try and save lives in medicine and autonomous driving.

Easy to take for granted, but their peer companies are not doing this type of long term investment.

I agree with the sentiment, but sadly even in its watered down form, SB79 was the result of a brutal legislative battle over the course of years, and even then it barely passed.

Getting Prop 13 overturned is about as likely as California seceding from the US.

Actually, it might even be less likely than that.

I'm working on 1:6 size furniture. There's not much woodworking I can do outside of the shop, so I've been trying to shrink full joinery techniques down to dollhouse size.

To sidestep the partisan side of this, I encourage everyone here to read about other regimes in the past century and how they came to power in order to build up your pattern matching ability.

I think money is the wrong thing to focus on.

I've found that if you want to identify your talents, don't think about what you're good at. Ask yourself what easy thing everyone else is inexplicably bad at.

That's all OP means.