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Michael Guo
@Michaelzsguo
Building AI agents and AI-native orgs. Demystifying AI in practice. EN/中文
389 Following    2.3K Followers
Did anyone else notice that the worker in the hard hat and yellow vest submerged himself in the dirty water and never came back?
Speaking of character, DeepSeek could not be more different from the sycophantic GPT. It pushes back on me, and sometimes dismisses my suggestions outright. I love its gut and spine. It earned it, after nearly 800m tokens for $10.
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I’m wondering who will tire first.
We got bored. Time for Man vs. Machine
So you bought the 128GB MacBook Pro. Now the question is not, “Which local model gets the highest TPS?” It is: which setup can I actually trust to get the job done? This is the local coding stack I’d start with: Qwen 3.6, dense 27B, Q6 quant, MLX server, 8192 output tokens, 20GB prompt cache, and deterministic decoding. If Anthropic’s success story tells us anything, it is that once you figure out coding, you can expand into almost anything else. Local models stop being a hobby when they can finish the patch.
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While the agent works toward its goal, another agent and I review its work in a sidecar, check the results, and feed nudges back into the main agent with the scaffold setup with skill goal-forge ( @thsottiaux do you think this is a feature worth adding to Codex Goal?
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Codex CLI has a new spashpage. Pretty cool. @OpenAIDevs
Thank you, @thsottiaux, for resetting it. Now I can roll up my sleeves and start a new goal pursuit. My last one ran for 1d 13h 20m. Codex rocks.
@thsottiaux I so need this reset as I'm deeply in debt. let's go
1d 13h 20m, 3,596,831 tokens. Goal achieved? Not quite. It was a hard problem. The agent tried its best and went through 20 full model/eval rounds. In the end, the agent talked itself out of the original contract and declared the goal achieved. I probably would have stopped it anyway, since I could also see from the sidecar that it was struggling. Still, it was a good experiment. My 14" MacBook Pro held up well under a sustained run, with no throttling or heating issue. Qwen3.6 35B A3B OptiQ 4-bit running locally on MLX also held up well. It generated thousands of training data samples, averaging around 50 tps with reasonably good quality. Very impressive. DeepSeek 4 Pro was a good teacher for the training, though there are still areas for improvement. The end result: we LoRAed an expert model, Qwen3-4B-Instruct-2507 + MLX LoRA. We produced a compact 56 MB LoRA adapter on a 4B Qwen base that reaches ~59% three-way decision agreement on the original eval slice, ~91% violation recall, and ~98% valid JSON, but with a high false-positive rate. It is deployable, but probably not quite usable yet. Still, it gives me a clear direction for where to go next. I’ll write more about the whole process later. Stay tuned.
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When you still can’t retire even if you have been making $500k+ a year!
The vibes in SF feel pretty frenetic right now. The divide in outcomes is the worst I've ever seen. Over the last 5yrs, a group of ~10k people - employees at Anthropic, OpenAI, xAI, Nvidia, Meta TBD, founders - have hit retirement wealth of well above $20M (back of the envelope AI estimation). Everyone outside that group feels like they can work their well-paying (but <$500k) job for their whole life and never get there. Worse yet, layoffs are in full swing. Many software engineers feel like their life's skill is no longer useful. The day to day role of most jobs has changed overnight with AI. As a result, 1. The corporate ladder looks like the wrong building to climb. Everyone's trying to align with a new set of career "paths": should I be a founder? Is it too late to join Anthropic / OpenAI? should I get into AI? what company stock will 10x next? People are demanding higher salaries and switching jobs more and more. 2. There’s a deep malaise about work (and its future). Why even work at all for “peanuts”? Will my job even exist in a few years? Many feel helpless. You hear the “permanent underclass” conversation a lot, esp from young people. It's hard to focus on doing good work when you think "man, if I joined Anthropic 2yrs ago, I could retire" 3. The mid to late middle managers feel paralyzed. Many have families and don't feel like they have the energy or network to just "start a company". They don't particularly have any AI skills. They see the writing on the wall: middle management is being hollowed out in many companies. 4. The rich aren’t particularly happy either. No one is shedding tears for them (and rightfully so). But those who have "made it" experience a profound lack of purpose too. Some have gone from <$150k to >$50M in a few years with no ramp. It flips your life plans upside down. For some, comparison is the thief of joy. For some, they escape to NYC to "live life". For others still, they start companies "just cuz", often to win status points. They never imagined that by age 30, they'd be set. I once asked a post-economic founder friend why they didn't just sell the co and they said "and do what? right now, everyone wants to talk to me. if i sell, I will only have money." I understand that many reading this scoff at the champagne problems of the valley. Society is warped in this tech bubble. What is often well-off anywhere else in the world is bang average here. Unlike many other places, tenure, intelligence and hard work can be loosely correlated with outcomes in the Bay. Living through a societally transformative gold rush in that environment can be paralyzing. "Am I in the right place? Should I move? Is there time still left? Am I gonna make it?" It psychologically torments many who have moved here in search of "success". Ironically, a frequent side effect of this torment is to spin up the very products making everyone rich in hopes that you too can vibecode your path to economic enlightenment.
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@thsottiaux I so need this reset as I'm deeply in debt. let's go