Mason (@chenjingtalk) profile picture

I’m speaking only for myself here. Doing things @openclaw 🦞 | Engineer @TencentCompute ☁️ | AI coding fanatic 🧠 | https://xitter.cf/t.co/PbJy0ezw41

Joined October 2018
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One RSI-like approach I’ve found really effective lately is simply Automation. After an optimization, I tell the Agent to check the logs a few hours later, see if the results meet expectations, and keep optimizing if they don’t. Time will solve everything.
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Mason retweeted
Day 28/ tibo's game has landed i spent $5.99 on this domain, but i had a blast making it with grok bot and cursor! i hope you enjoy it and find all the easter eggs 🤍 if i did it right you should be able to play it inside of X too tibo.dog
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codebases have always contained slop. we have always been okay with this because code rarely needs to be perfect, outside of mission critical "hard" (eg embedded) software. swe is a unique form of engineering because you're often building something that constantly evolves and is almost organic - user tastes change, your mental models evolve, and features come and go. admittedly, i and many others who've been coding for a long time were initially (like back in 2024) skeptical that agents would write production code. "but what about all the slop that would enter our beautiful codebase?". well, even before, we had human slop, and there was a lot of it! if we're being truthful, most people call "code i didn't write" slop. the reality is that 99% of people (i include myself in that number) don't even know what Good Code looks like, let alone be capable of writing it. i would propose that Good Code is: • correct • bug free • fast and cost efficient to run it has always been exceedingly difficult and expensive to write truly Good Code, because for the longest time (maybe @bendlang will change that), code was not something you could cheaply and formally guarantee to have all 3 of these properties. this is why writing hard software is much more difficult and expensive, because depending on the use case, you may only get one chance and so you have to be right from the start. but the vast majority of software we use does not need to be Good Code to provide value to users. in fact, it is very likely that most software we use is not formally verifiable! we accepted some bugs in exchange for velocity and progress, so we rely on tests and o11y instead and have adopted a more incremental approach. this is a good thing! agents help us move faster, and if you're open to the idea, are capable of helping us write better code. it won't be Good Code (that is still expensive), but it is likely to be much better on average at scale. the new craft of swe is to figure out how to do this. it's your job now! if your productivity with and without agents is not significantly different, you're doing something wrong. but it's not too late to embrace it and use it as an opportunity to learn a whole new skill tree
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GPT Pro is request-limited and often produces long, repetitive docs. I found a simple way to get more value from each request: "Give me a detailed report and an interactive HTML explainer with more visuals, less text, and animations to make concepts easier to grasp."
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My first takeaway from October: One big trap is obsessing over how many Agents I can keep running in the background. I've sacrificed a lot of sleep and attention just to have Agents tackle some “big task” while I'm resting.
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Maintaining focused attention in bursts is important. It's not about being completely single-threaded, but about fully reading the current Agent's response and preparing the next prompt before moving on.
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Used dot today for a pretty complicated shopping decision. It compared multiple products and refund policies, talked to customer support, then gave me the best option. It also had my ChatGPT Memory, so it already knew my preferences. Honestly, it exceeded my expectations.
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GPT 6.1 sol also exceeded my expectations. It’s a solid model and uses little quota. Funny enough, I was considering canceling my plan, but now I’ll probably keep at least one Pro lite. Just 24 hours ago, I couldn’t imagine how OpenAI would keep customers like us. But, they did.
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Users know they’ve been getting a great deal. O and A have offered subscriptions so aggressively that companies like Cursor could barely keep up. But once they have enough users, the goal shifts to increasing margins and squeezing more out of them.
people are saying nasty things about the new openai rate limits they don't understand how hard the openai (and ant) teams work to provide these subscription products that at best break even and eat up limited compute no one wants to cut limits. screaming at them doesn't help
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What does that look like? Monopoly. Welcome to capitalism. This industry is barely regulated, and model providers can quietly lower service quality by changing things like quantization. This generation of users has an insanely high tolerance for it.
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I’m not happy for A. I like their latest generation of models and the kind of artistic sensibility you rarely see in a tech company, but I don’t like Dario. More than anything, I’m disappointed in what this industry has become.
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Remember. Sora 2 was released just one year ago.
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Yes, users can probably get more work done than they could a month ago. The problem is that Claude Code lets them get even more done today. You guys cut the effective value of a $200 plan in half. That’s not just a pricing failure. It’s a failure of user trust.
Hi, Tomorrow we are re-opening the Pro $200 subscriptions to new subscribers, but together with it we are also changing how we calculate the usage for it. In effect, if you do the math, it will net out at half the dollar in API spend compared to the old Pro $200 plan. Now that it's said, let me explain why this is happening and why you will still get more work done than if you were on the Pro $200 subscription one month ago. (a) We didn't want to compromise in other ways and are committing to not reintroducing the 5h limit, so that you can fully use the weekly usage when you want. (b) On the subscription, we guarantee that over time you always get more work done and with an increasing level of quality. This means that you will continue to get more value per dollar spent as a result of models getting more efficient and us passing down the improvements in the form of API price reductions. (c) We don't want to put an incentive on ourselves to artificially inflate the API list prices to make it look like you are getting a lot (and workaround it through discounts, etc). Instead we want to continue to both rapidly reduce prices and increase capabilities of models on the API. This week we introduced GPT-6 Sol and GPT-6 Luna at 50% of their previous price. Over time, we see prices go low enough that it makes sense for most to buy usage as needed without there being a significant gap between what you get in a subscription and what you get in the API for a dollar spent. (d) Tomorrow, we are adding more things to the subscription that won't draw on the usage, I won't reveal what that is yet. I wanted to be transparent before all the big announcements tomorrow. Lots of new exciting things are coming to the subscriptions that will make it super compelling, but I wanted to make sure to share this change ahead of time so you can all understand it before we shower you with good news. Codexingly, Tibo
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As agents get smarter, alignment becomes especially important.
this has become one of my most used prompts recently: > restate in your own words what you think my goals are and what the problem i'm trying to solve is
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Sol 6 isn’t that bad, unless you have to talk to it directly. Just let Astra prompt it.
Not happy to be a codex 20x subscriber rn: - Sol 6 ain't shit - Astra 6 ain't shit - Chatgpt still 5.6 - Astra Pro ain't shit
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Definitely worth learning from. There’s no silver bullet in software engineering — if you want to do it well, you still have to put in the work.
The biggest design mistake I made when we moved OC to sqlite: using sync db access. When it was just an agent that reports to you on Slack or iMessage this was fine; now that one agent might do 50 sessions in parallel and the whole team works on it, it is limiting. I have a /goal with Astra that so far landed 575 PRs to move everything to to async workers. We ship these improvements as we make progress. Pretty insane how even huge refactors are no longer scary.
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Oops, 5.5 has already been nerfed. Keep saying "you are right". And make same mistakes again.
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In the obsession with AI, too many founders, leaders, managers seem to have forgotten that an engineer with motivation + drive + focus + AI >> hundreds of AI agents without any of those The best products and companies are built by people and teams like that, and will continue to be so Ask yourself, again, why the AI labs hire the best of the best (some of the most driven people in the industry; founders, CTOs etc) if people aren't making the differrence when everyone has access to similar tools already
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Remember, you don't need to convince the Agent unless you're doing critical thinking.
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After co-inventing ChatGPT, I kept asking myself: why have superhuman chat models not led to AGI? I’ve spent the last 2 years in stealth building a new way to train models (RLCD), and a new type of frontier AI model that we are releasing today: Jev • 20-200x faster • 40-400x cheaper (w/ output tokens free) • Frontier composable intelligence optimized for decisions AFAICT the shortest path to AI-based economic revolution
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