It’s a good point. Going over each item is what works for us. But I still extract from the bank and into a spreadsheet so we have full control. The only thing spreadsheets lack is double entry.
interesting. without an account, from my browser, I can see it in the fifth place. are you searching from your phone, iPad, laptop...?
but this checks out with my experience: extremely low visibility on the stores, I think I need to improve description/keywords and get more reviews. thanks for sharing!
> when [sending AI generated content to teammates], I take care to clearly label what is AI generated
Reading AI-generated text for hours every day, it's obvious to me.
I take care to make my messages easily readable. I don't care if they're AI-made, as long as they're short.
I'm a very verbose person, and if I don't make an effort at being concise, I'm just as annoying as the average AI.
Being flooded with AI text every day has made me appreciate brevity because I'm exposed to so little of it.
With half a dozen people who don't read or listen to half of what the others do, slop + cognitive drift is a bad cocktail.
It's just not as big of a problem on my own projects, because the ideas that get fed to the slop-machine are not that different from one day to the next.
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> For human code review requests, I always review my AI-generated code first.
For human code review requests, I always review ANY code I submit first.
This is partly because it's the agreed-upon culture where I work now.
And partly because the codebase is not robust enough for slop.
I have hobby projects where this does not apply. I spend half of my time in those projects building hard guardrails.
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> Keeping AI generated content clearly labeled and demonstrating human effort helps show consideration for teammates
I actually like the shamelessness, because it's honest.
So often this year when I ask "why did you do X?" pointing at a line, my colleague doesn't know.
Because they didn't really write that line, and they didn't really internalise the choices made.
When my colleague sends me a text dump from Claude, I know that my role is just being a sub-agent.
Demonstrating human effort: I'd like to see more of it.
One way is to spend more time owning "cognitive debt" as part of the daily cycle.
Brevity is the big disaster of human-generated text since the rise of the phone as default device and the appearance of Twitter. To discuss matters with sufficient depth and nuance, one often has to write a few solid paragraphs.
If people are now wincing at longform text because they automatically assume it was LLM-generated, then that bodes ill.
To add to this, there seems to be an inability to process metaphor and simile in the younger generations. Likely as a result of the same deficit. They've become very literal, and often mistake anything that's well written for AI slop.
There's a sweet spot between AI slop and 144 characters. I can tell within a few sentences whether there's a human on the other end getting to the point, or an AI dancing around the point and finding 3 different ways to say the same thing.
I'm with you on the first one and that's the closest reason why you could call Firefox payment "ad money". But the rest are not too strong. Google makes a lot of non-ad money too, even if it's a smaller portion than ads. You don't call airlines "banks" just because they make all of their money from currency-like "miles", and even fly at a loss [0].
What I want to say is that calling it "ad money" makes Firefox look bad when it shouldn't.
As in my reply further below, Q1 2026 you can see Google makes 70% of revenue from Ads, the non-ad money you refer to is only 1/3. But if you look at net income, 85% of the net income from Google comes from Services (including Ads).
The Airlines story is taken out of context and different from Google, Delta for example in the Q1 2026 filing you can see they have a revenue of $15.8bn, of which ticket sales is $10.7bn ! Loyalty program income is just $1bn. However the net income supports the story The Atlantic ran, which just means that out of the $1bn, they are getting more net income from their mileage programs, than income from out of $10.7bn ticket sales, because the operating expense of flying airplane is quite high from fuel, etc.
So on one side, Google has 70% revenue from Ads, and even more % if you count net income. On the other side, Airlines - like Delta - have 70% of their revenue from passenger, but relatively speaking less net income from ticket sales if you consider net income.
You are not comparing the same thing. If you just compare revenue, Airlines cannot be called Banks because they still make 70% of their revenue from passenger ticket sales, just as how Google is an Ad company because their main revenue is 70% ads!
If you compare net income, the airlines story can have an angle, but the Google story doesn't, because their net income from Ads is way higher!
When someone says that all money a company pays is "money from their main segment", that's intentionally misrepresenting. In this case what's important is what the money is for, not from. Calling it "Firefox had ad-money coming in" can only be bad faith, the usual social media rage bait.
Now everyone comes out of the woodwork with "well akshully" because there's an interpretation where they can plausibly claim "technically I'm right" despite knowing they are sending the wrong message.
Basketball player LeBron James made more money from endorsements than sports, gas stations make more money from selling coffee and food than gas, and fast-food giant McDonald's makes more money from rent than from fast-food. If you called a gas station "a grocery store" you'd be technically right but also practically and pointlessly wrong.
To answer your question: It depends on your claim. All claims of mass unemployment thus far are evidently not true. All claims of mass unemployment in the near future: We'll have to wait and see.
The prediction that AI will lead to mass unemployment is largely a widespread fear more than an observation.
AI washing: On the one hand, you have periodic mass layoffs that could be related, but also could be "AI washing", with the companies citing AI to sound progressive when, in fact, they just over-hired.
> I would love to hear from someone who actually played with all the FOMO harnesses
I tried claude, opencode, pi, hermes, openclaw.
Specifically, I tried Claude with Sonnet/Opus and GLM-5.1, and OpenCode with Sonnet/Opus (briefly, since it's a violation of services) and much more with GLM-5.1.
I'll say: Claude is the best overall. OpenCode has the best UI. Pi has something going for it (I embed it in my agents on my Multica kanban), being that it's programmable and extensible by design, it's also a CLI.
Hermes: Sluggish, very slow to start, a lot is going on in the background, didn't like it. Seems over-engineered, didn't use it long enough to evaluate its memory functions. I'd rather have full session logs rather than these MEMORY.md summaries of what a session did.
OpenClaw: Amazing in its novelty, hellish in its implementation. I tried to make an OpenClaw on a VPS capable of editing its own Nix config, and it sucked. Tried a few variations like NanoClaw. Much less fluid; not the same, which is probably a good thing, but what OpenClaw tries to deliver is this autonomous agent with full ability to edit itself as crazy as that is. If it were just less sluggish and capable of more self-modification off the bat. I mostly blame JavaScript/NPM here.
I gave my brother an OpenClaw and he tried to make it do things on his behalf. His final feedback before abandoning it: It feels like I need to know programming. I ask it for the daily weather report.
I had bought some Anthropic credit and waited a year to use it. The week before their expiration I fired up Code and spent $3 the first day and the remaining $22 the next day.
Putting a ReAct loop with tool calls in my terminal wad and is the biggest a-ha since I learned to make compilers, and before that, how to code.
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