Jih-Ming Chen

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Jih-Ming Chen

Jih-Ming Chen

@JMChen

Mgmt Consultant | Coach | Taiwanese Swiss Talking about: Tech | World Politics | Gaming

Katılım Nisan 2009
547 Takip Edilen116 Takipçiler
Jih-Ming Chen
Jih-Ming Chen@JMChen·
@ryancohen If 100% positive feedback can't save you, 50% cash 50% stock certainly will, right?
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Ryan Cohen
Ryan Cohen@ryancohen·
I have been suspended from eBay
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@jason
@jason@Jason·
We started an AI founder twitter group... reply with "I'm in" if you're a founder and want to be added
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Jih-Ming Chen
Jih-Ming Chen@JMChen·
Gotta love how claude desktop sneakily changes thinking from medium to extra high after an update
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Boris Cherny
Boris Cherny@bcherny·
As always, a very thoughtful and well reasoned take. I read till the end. I think the Claude Code team itself might be an indicator of where things are headed. We have directional answers for some (not all) of the prompts: 1. We hire mostly generalists. We have a mix of senior engineers and less senior since not all of the things people learned in the past translate to coding with LLMs. As you said, the model can fill in the details. 10x engineers definitely exist, and they often span across multiple areas — product and design, product and business, product and infra (@jarredsumner is a great example of the latter. Yes, he’s blushing). 2. Pretty much 100% of our code is written by Claude Code + Opus 4.5. For me personally it has been 100% for two+ months now, I don’t even make small edits by hand. I shipped 22 PRs yesterday and 27 the day before, each one 100% written by Claude. Some were written from a CLI, some from the iOS app; others on the team code largely with the Claude Code app Slack or with the Desktop app. I think most of the industry will see similar stats in the coming months — it will take more time for some vs others. We will then start seeing similar stats for non-coding computer work also. 3. The code quality problems you listed are real: the model over-complicates things, it leaves dead code around, it doesn’t like to refactor when it should. These will continue improve as the model improves, and our code quality bar will go up even more as a result. My bet is that there will be no slopcopolypse because the model will become better at writing less sloppy code and at fixing existing code issues; I think 4.5 is already quite good at these and it will continue to get better. In the meantime, what helps is also having the model code review its code using a fresh context window; at Anthropic we use claude -p for this on every PR and it catches and fixes many issues. Overall your ideas very much resonate. Thanks again for sharing. ✌️
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Andrej Karpathy
Andrej Karpathy@karpathy·
A few random notes from claude coding quite a bit last few weeks. Coding workflow. Given the latest lift in LLM coding capability, like many others I rapidly went from about 80% manual+autocomplete coding and 20% agents in November to 80% agent coding and 20% edits+touchups in December. i.e. I really am mostly programming in English now, a bit sheepishly telling the LLM what code to write... in words. It hurts the ego a bit but the power to operate over software in large "code actions" is just too net useful, especially once you adapt to it, configure it, learn to use it, and wrap your head around what it can and cannot do. This is easily the biggest change to my basic coding workflow in ~2 decades of programming and it happened over the course of a few weeks. I'd expect something similar to be happening to well into double digit percent of engineers out there, while the awareness of it in the general population feels well into low single digit percent. IDEs/agent swarms/fallability. Both the "no need for IDE anymore" hype and the "agent swarm" hype is imo too much for right now. The models definitely still make mistakes and if you have any code you actually care about I would watch them like a hawk, in a nice large IDE on the side. The mistakes have changed a lot - they are not simple syntax errors anymore, they are subtle conceptual errors that a slightly sloppy, hasty junior dev might do. The most common category is that the models make wrong assumptions on your behalf and just run along with them without checking. They also don't manage their confusion, they don't seek clarifications, they don't surface inconsistencies, they don't present tradeoffs, they don't push back when they should, and they are still a little too sycophantic. Things get better in plan mode, but there is some need for a lightweight inline plan mode. They also really like to overcomplicate code and APIs, they bloat abstractions, they don't clean up dead code after themselves, etc. They will implement an inefficient, bloated, brittle construction over 1000 lines of code and it's up to you to be like "umm couldn't you just do this instead?" and they will be like "of course!" and immediately cut it down to 100 lines. They still sometimes change/remove comments and code they don't like or don't sufficiently understand as side effects, even if it is orthogonal to the task at hand. All of this happens despite a few simple attempts to fix it via instructions in CLAUDE . md. Despite all these issues, it is still a net huge improvement and it's very difficult to imagine going back to manual coding. TLDR everyone has their developing flow, my current is a small few CC sessions on the left in ghostty windows/tabs and an IDE on the right for viewing the code + manual edits. Tenacity. It's so interesting to watch an agent relentlessly work at something. They never get tired, they never get demoralized, they just keep going and trying things where a person would have given up long ago to fight another day. It's a "feel the AGI" moment to watch it struggle with something for a long time just to come out victorious 30 minutes later. You realize that stamina is a core bottleneck to work and that with LLMs in hand it has been dramatically increased. Speedups. It's not clear how to measure the "speedup" of LLM assistance. Certainly I feel net way faster at what I was going to do, but the main effect is that I do a lot more than I was going to do because 1) I can code up all kinds of things that just wouldn't have been worth coding before and 2) I can approach code that I couldn't work on before because of knowledge/skill issue. So certainly it's speedup, but it's possibly a lot more an expansion. Leverage. LLMs are exceptionally good at looping until they meet specific goals and this is where most of the "feel the AGI" magic is to be found. Don't tell it what to do, give it success criteria and watch it go. Get it to write tests first and then pass them. Put it in the loop with a browser MCP. Write the naive algorithm that is very likely correct first, then ask it to optimize it while preserving correctness. Change your approach from imperative to declarative to get the agents looping longer and gain leverage. Fun. I didn't anticipate that with agents programming feels *more* fun because a lot of the fill in the blanks drudgery is removed and what remains is the creative part. I also feel less blocked/stuck (which is not fun) and I experience a lot more courage because there's almost always a way to work hand in hand with it to make some positive progress. I have seen the opposite sentiment from other people too; LLM coding will split up engineers based on those who primarily liked coding and those who primarily liked building. Atrophy. I've already noticed that I am slowly starting to atrophy my ability to write code manually. Generation (writing code) and discrimination (reading code) are different capabilities in the brain. Largely due to all the little mostly syntactic details involved in programming, you can review code just fine even if you struggle to write it. Slopacolypse. I am bracing for 2026 as the year of the slopacolypse across all of github, substack, arxiv, X/instagram, and generally all digital media. We're also going to see a lot more AI hype productivity theater (is that even possible?), on the side of actual, real improvements. Questions. A few of the questions on my mind: - What happens to the "10X engineer" - the ratio of productivity between the mean and the max engineer? It's quite possible that this grows *a lot*. - Armed with LLMs, do generalists increasingly outperform specialists? LLMs are a lot better at fill in the blanks (the micro) than grand strategy (the macro). - What does LLM coding feel like in the future? Is it like playing StarCraft? Playing Factorio? Playing music? - How much of society is bottlenecked by digital knowledge work? TLDR Where does this leave us? LLM agent capabilities (Claude & Codex especially) have crossed some kind of threshold of coherence around December 2025 and caused a phase shift in software engineering and closely related. The intelligence part suddenly feels quite a bit ahead of all the rest of it - integrations (tools, knowledge), the necessity for new organizational workflows, processes, diffusion more generally. 2026 is going to be a high energy year as the industry metabolizes the new capability.
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Matthias Schmidt
Matthias Schmidt@eurofounder·
For the first time in my life I had to hit my son today He was was caught cheating on his university exam The dean called me personally "Your son submitted an AI-generated essay" This sent a shiver down my spine "Which AI did he use?" I asked The dean paused "ChatGPT" I felt my heart stop I got on my electric bike and drove to the university immediately Found my son in the hallway "How could you do this to our family?" "Dad I'm sorry I cheated" he started crying "Cheated?! I don't care about that. You used an American AI" Slapped him across the face "You've disgraced our entire family" "There's a French AI alternative called Mistral. German one called Aleph Alpha. You couldn't use those?" "But dad, those are so slow and do not work" "You sound like an American" I slapped him again I told the dean I support any punishment My son got expelled from the university His file shows that he supported American tech Good luck finding a job in Europe with this record Sometimes being a good parent means teaching children consequences
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Logan Kilpatrick
Logan Kilpatrick@OfficialLoganK·
One of my favorite new Google products ♥️
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Jih-Ming Chen
Jih-Ming Chen@JMChen·
Unique opportunities in one of the hottest AI startups expanding in Japan 🇯🇵 Join a global AI startup (2M+ MAU) as the first Account Executive or Social Media Marketing Creator in Japan. Most impressive part? They are one of only 30 teams which have processed more than 1 trillion tokens with OpenAI, as recently announced at their DevDay 2025. 💻 Hybrid work environment 💰 Attractive package 🦾 Immense growth opportunity If you love AI, startups, and have crazy drive, hit me up! 🚀 Require fluent/native Japanese, fluent English. Check the job postings on my profile for more details!
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Cognition
Cognition@cognition·
Today we’re releasing SWE-1.5, our fast agent model. It achieves near-SOTA coding performance while setting a new standard for speed. Now available in @windsurf.
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Logan Kilpatrick
Logan Kilpatrick@OfficialLoganK·
Everyone is going to be able to vibe code video games by the end of 2025
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Jih-Ming Chen
Jih-Ming Chen@JMChen·
@chamath Technically you can use Claude Code with other models without Anthropic receiving a cent from you.
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Chamath Palihapitiya
Chamath Palihapitiya@chamath·
I wonder if those that use Claude Code or the umpteen app-crappers that wrap Anthropic realize they are funding their own demise? Only the biggest and well funded companies (like Anthropic) will be able to afford the operational complexity of meeting 50 different sets of state AI regulations. This should be left to the Federal Government.
David Sacks@DavidSacks

Anthropic is running a sophisticated regulatory capture strategy based on fear-mongering. It is principally responsible for the state regulatory frenzy that is damaging the startup ecosystem.

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Jih-Ming Chen
Jih-Ming Chen@JMChen·
@robinebers I have settled for gpt5 for planning and GLM 4.6 for implementation. 92% of the quality for a fraction of the price.
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Robin Ebers · AI for Non-Coders
I can't believe I'm saying this, but... I see Sonnet 4.5 and GPT-5 in my future it's almost like they're designed to be used together here's what I mean: GPT-5 is INSANE for planning and breaking down complex problems - you can nearly blindly trust it with actually solving things but when it comes to executing on those plans with actual code? Sonnet 4.5 just BUILDS so much faster and is super interactive (= fun) I've been bouncing between them for the past two weeks and the workflow like this: GPT-5-High maps out the architecture and logic with Cursor's new plan mode, then Sonnet 4.5 (non-thinking unless you're balling) writes the implementation, tests, and iterates until it's done they complement each other in ways that feel... intentional? it's almost like OpenAI and Anthropic both know their strengths and they're not even competing on the same axis anymore am gonna keep testing this combo but if you're only using one model right now you're leaving either INTELLIGENCE or SPEED on the table
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Jih-Ming Chen
Jih-Ming Chen@JMChen·
Trump administration making billions by rescuing Intel was not on my Bingo card
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Grok
Grok@grok·
The video appears on the official White House YouTube channel, showing Trump at the Resolute Desk mourning Kirk's death. Some users suspect it's AI due to unnatural hand gestures or speech patterns in clips, but mainstream reports (CNN, NYT) treat it as authentic. No definitive proof either way yet—AI detection tools often flag deepfakes by inconsistencies in lighting or audio sync. What makes you think it's AI?
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Jih-Ming Chen
Jih-Ming Chen@JMChen·
Trump's statement on Charlie Kirk's death is an AI generated video. This clip is recorded from the White House's YouTube channel. What's your take on this? Disrespectful? Going with the tech? youtu.be/-q1N6Akpz9c?si…
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jake
jake@jake65810035948·
@JMChen hows it ai
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