# on shortification of "learning"
There are a lot of videos on YouTube/TikTok etc. that give the appearance of education, but if you look closely they are really just entertainment. This is very convenient for everyone involved : the people watching enjoy thinking they are learning (but actually they are just having fun). The people creating this content also enjoy it because fun has a much larger audience, fame and revenue. But as far as learning goes, this is a trap. This content is an epsilon away from watching the Bachelorette. It's like snacking on those "Garden Veggie Straws", which feel like you're eating healthy vegetables until you look at the ingredients.
Learning is not supposed to be fun. It doesn't have to be actively not fun either, but the primary feeling should be that of effort. It should look a lot less like that "10 minute full body" workout from your local digital media creator and a lot more like a serious session at the gym. You want the mental equivalent of sweating. It's not that the quickie doesn't do anything, it's just that it is wildly suboptimal if you actually care to learn.
I find it helpful to explicitly declare your intent up front as a sharp, binary variable in your mind. If you are consuming content: are you trying to be entertained or are you trying to learn? And if you are creating content: are you trying to entertain or are you trying to teach? You'll go down a different path in each case. Attempts to seek the stuff in between actually clamp to zero.
So for those who actually want to learn. Unless you are trying to learn something narrow and specific, close those tabs with quick blog posts. Close those tabs of "Learn XYZ in 10 minutes". Consider the opportunity cost of snacking and seek the meal - the textbooks, docs, papers, manuals, longform. Allocate a 4 hour window. Don't just read, take notes, re-read, re-phrase, process, manipulate, learn.
And for those actually trying to educate, please consider writing/recording longform, designed for someone to get "sweaty", especially in today's era of quantity over quality. Give someone a real workout. This is what I aspire to in my own educational work too. My audience will decrease. The ones that remain might not even like it. But at least we'll learn something.
You can’t outwork the whole world. There’s always going to be someone somewhere willing to work as hard as you. Someone just as hungry. Or hungrier.
Assuming you can work harder and longer than someone else is giving yourself too much credit for your effort and not enough for theirs. Putting in 1,001 hours to someone else’s 1,000 isn’t going to tip the scale in your favor.
What’s worse is when management holds up certain people as having a great “work ethic” because they’re always around, always available, always working. That’s a terrible example of a work ethic and a great example of someone who’s overworked.
A great work ethic isn’t about working whenever you’re called upon. It’s about doing what you say you’re going to do, putting in a fair day’s work, respecting the work, respecting the customer, respecting coworkers, not wasting time, not creating unnecessary work for other people, and not being a bottleneck. Work ethic is about being a fundamentally good person that others can count on and enjoy working with.
So how do people get ahead if it’s not about outworking everyone else?
People make it because they’re talented, they’re lucky, they’re in the right place at the right time, they know how to work with other people, they know how to sell an idea, they know what moves people, they can tell a story, they know which details matter and which don’t, they can see the big and small pictures in every situation, and they know how to do something with an opportunity. And for so many other reasons.
So get the outwork myth out of your head. Stop equating work ethic with excessive work hours. Neither is going to get you ahead or help you find calm.
[The Outwork Myth — It Doesn't Have To Be Crazy At Work, 2018]
Been using DevPod for isolated agent envs, Docker Sandboxes looks really solid. love the built-in git worktree support, Docker availability, custom templates
Two things i'd love or curious if already possible:
1. mounting agent slash-commands/skills/configs into the sandbox so agents don't need manual setup each time
2. path-level write restrictions in the primary workspace e.g. block writes to .git/hooks it's a real security risk
‼️Do not npm install or deploy anything right now
Supply chain attack on axios 1.14.1 - even if you don’t use axios it may be a nested dep.
Pin versions or wait until this is resolved
IBM built a cloud of suits to make sure the CEO never talked to anyone actually doing the work. @elonmusk does the opposite.
"Elon's method is extreme focus on substance. Extreme focus on getting to the truth.
In any organization with multiple layers, there's compounding lies. Each layer wants to look good. Each layer puts a little spin on things.
If one layer lies to the next layer above it, maybe that's okay. When that happens two or three times, the lies compound. If that happens six times, the lies really compound. If that happens 12 times, the CEO has no idea what's happening.
That was IBM.
By the time I got there as an intern, I calculated there were 12 layers of management between me and the CEO.
They even had a term for it: the great cloud. A cloud of men in gray business suits who followed the CEO around and prevented him from ever talking to anybody who was actually doing the work.
When he would come to visit, it was like a visit from the king. A completely impervious bubble.
That's the polar opposite of the Elon approach."
— @pmarca
My conversation with Tobi Lütke (@tobi), co-founder and CEO of Shopify.
0:00 Companies as Social Technology
5:27 The Value of Reading Books: Cheat Codes for Life
7:28 Post-IPO Crisis: Cosplaying as a CEO
7:54 Competition vs Rivalry: The Power of Healthy Competition
16:02 COVID as a Turning Point: Rebuilding the Executive Team
18:21 Hiring Founders: Building a Team of High-Agency People
26:49 Shopify OS: Engineering the Company from First Principles
36:48 Compensation Innovation: Giving Employees Full Agency
40:41 The Psychology of Identity and Affirmations
48:43 Differentiation Over Perfection: Making It Your Own
50:31 Context Podcast: Documenting Decision-Making
1:26:36 The IPO Decision: Going Against Silicon Valley Orthodoxy
1:35:08 Building a Company Worth Working For
1:41:50 Hiring for Spikiness: Finding Non-Conformists
1:48:28 Office Design Philosophy: Creating Space for Excellence
1:58:54 Video Games as Business Training: StarCraft Lessons
2:07:06 AI Revolution: 2026 and Beyond
2:11:44 Focus on Craft: The Unquantifiable Elements of Excellence
2:21:08 Survivorship Bias: The Importance of Entrepreneurial Exposure
2:23:22 Closing
Includes paid partnerships.
@bruvimtired@tan_stack@tannerlinsley This is more of a route design issue. /:username is too generic and will swallow future routes. a scoped structure like /users/{username}/repos/{repo} is much safer
I'm trying something new with my blog, making it interactive
first article is about something I care deeply about: logs
logging sucks so much
https://t.co/mdFhxEvpjB
Microservices is the software industry’s most successful confidence scam. It convinces small teams that they are “thinking big” while systematically destroying their ability to move at all. It flatters ambition by weaponizing insecurity: if you’re not running a constellation of services, are you even a real company? Never mind that this architecture was invented to cope with organizational dysfunction at planetary scale. Now it’s being prescribed to teams that still share a Slack channel and a lunch table.
Small teams run on shared context. That is their superpower. Everyone can reason end-to-end. Everyone can change anything. Microservices vaporize that advantage on contact. They replace shared understanding with distributed ignorance. No one owns the whole anymore. Everyone owns a shard. The system becomes something that merely happens to the team, rather than something the team actively understands. This isn’t sophistication. It’s abdication.
Then comes the operational farce. Each service demands its own pipeline, secrets, alerts, metrics, dashboards, permissions, backups, and rituals of appeasement. You don’t “deploy” anymore—you synchronize a fleet. One bug now requires a multi-service autopsy. A feature release becomes a coordination exercise across artificial borders you invented for no reason. You didn’t simplify your system. You shattered it and called the debris “architecture.”
Microservices also lock incompetence in amber. You are forced to define APIs before you understand your own business. Guesses become contracts. Bad ideas become permanent dependencies. Every early mistake metastasizes through the network. In a monolith, wrong thinking is corrected with a refactor. In microservices, wrong thinking becomes infrastructure. You don’t just regret it—you host it, version it, and monitor it.
The claim that monoliths don’t scale is one of the dumbest lies in modern engineering folklore. What doesn’t scale is chaos. What doesn’t scale is process cosplay. What doesn’t scale is pretending you’re Netflix while shipping a glorified CRUD app. Monoliths scale just fine when teams have discipline, tests, and restraint. But restraint isn’t fashionable, and boring doesn’t make conference talks.
Microservices for small teams is not a technical mistake—it is a philosophical failure. It announces, loudly, that the team does not trust itself to understand its own system. It replaces accountability with protocol and momentum with middleware. You don’t get “future proofing.” You get permanent drag. And by the time you finally earn the scale that might justify this circus, your speed, your clarity, and your product instincts will already be gone.
The most-used @cursor_ai command is "Remove AI code slop."
That's the actual insight. Developers are spending more time cleaning up AI-generated code than anything else.
What AI adds that devs don't want:
> Extra comments humans wouldn't write
> Defensive try/catch blocks everywhere (even in trusted code paths)
> Type casts to bypass issues instead of fixing them
> Style that's inconsistent with the rest of the file
The problem isn't that AI writes bad code. It's that even the state of the art AI doesn't understand context completely.
Teams are comfortable letting AI do the heavy lifting. They're not comfortable with code that sounds AI-generated.
It adds error handling because "error handling is good" - not because this specific function needs it. It writes comments because "comments help" - not because this line is actually confusing.
Developers don't want "good" code. They want locally consistent code, which varies by subsystem.
This is why AI PRs are cognitively expensive. Even when the code works, reviewers have to translate foreign patterns back into the codebase's style.
It compiles, sure, but it doesn't read right.
AI optimizes for "seems like a good idea." Developers need "correct for this context."
Until AI gets better at context-awareness, the most valuable Cursor command will keep being "remove the slop."
We’re launching Anthropic Interviewer, a new tool to help us understand people’s perspectives on AI.
It’s now available at https://t.co/W8P36sPQBy for a week-long pilot.
"Using AI as a crutch means our fundamental critical thinking skills are being eroded."
@addyosmani on the hidden cost of AI coding and the 70% problem:
https://t.co/5Dgfw8LpVj