Shawn Simister

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Shawn Simister

Shawn Simister

@narphorium

Building AI powered tools to augment human creativity and problem solving. Previously @GitHub and @Google 🇨🇦

San Francisco Katılım Nisan 2007
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Shawn Simister
Shawn Simister@narphorium·
I've been thinking about why verifying AI agent output feels so much harder than writing the spec that produced it. That question led me to rethink where my attention actually belongs in the process, and eventually to build atelier.dev narphorium.com/blog/decision-…
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ruperts.world
ruperts.world@rupertmanfredi·
when you ask your agent to make a loading spinner
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Dan Shipper 📧
Dan Shipper 📧@danshipper·
as ai makes imitation cheaper and cheaper the value of using AI and your brain to make totally new things goes up
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Shawn Simister
Shawn Simister@narphorium·
So now AI has made the high-fidelity artifacts cheaper and easier to create but that doesn't change the rest of the equation. If anything, it makes it easier to fall into the trap of confusing high fidelity with high confidence.
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Shawn Simister
Shawn Simister@narphorium·
I sketched this out a few years ago. The HTML vs Markdown debate is conflating substrate with information density. The real question is what kind of feedback an artifact actually invites. Hi-fi invites parameter critique. Lo-fi invites paradigm critique.
Shawn Simister tweet media
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geoff
geoff@GeoffreyHuntley·
extending trip in SF for a couple days; now depart tuesday morning.
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Shawn Simister
Shawn Simister@narphorium·
Prototyping and experimentation is not slop. Slop is when you don't care how it works. The whole point of prototyping is that you care deeply about finding what works narphorium.com/blog/top-down-…
Mitchell Hashimoto@mitchellh

AI slop is good, actually. Slop is what enables fast parallel experimentation. The etiquette and skill is understanding the boundaries of where slop exists and the extent to which it should be cleaned up and how. A few examples: I’m working on the internals of some system right now. The API and GUI of this thing is fully zero shame slop. It’s horrible. But it lets me focus on the core quality while shipping a usable piece of alpha quality software to testers (transparent about the slop frontend). Similarly, this system has plugins. We sent agents in Ralph loops overnight to generate dozens of plugins. The plugins are slop. The quality is bad. The plugin API/SDK is absolutely not done. But we can test a full GUI with a full plugin ecosystem. When we change the API, we can regenerate them all. The cost of change is just tokens, the velocity is incomparable to before. I built Terraform. We tested and shipped TF 0.1 with about 3 very weak providers. Because we ran out of time. Building was slow. And when we changed our SDK the cost was immense. Totally different today, 10 years later. Today, I would’ve slop generated 100 providers (again, with transparency and cleanup later, but just to prove it out). As an anti example, I would not PR this (without prior warning) to another project. I would not throw this onto customers without full review or transparency (as I’m already doing). I would not accept first pass slop. It’s almost never right. Slop is a tool. And like anything else it’s not blanket bad or good. The context is everything.

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Sophia Xu
Sophia Xu@thesophiaxu·
Sharing a preview of an experimental tool I've been working on: A canvas-based IPython-compatible computational notebook exploring how "human-in-the-loop" looks like in an age of autonomous AI agents. More updates coming soon!
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Shawn Simister
Shawn Simister@narphorium·
@andy_matuschak I think if they accept lower $/sqft it lowers the overall appraisal value of the property so it’s more profitable to keep them empty
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Andy Matuschak
Andy Matuschak@andy_matuschak·
In SF, many ground floor commercial spaces in new condo / apt buildings near me have been empty for 5-10+ years. Naively: why doesn't the market clear? If the asking rent is too high for any tenant, wouldn't a building owner prefer to accept a lower rent over decadal vacancy?
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Shawn Simister
Shawn Simister@narphorium·
One of the most famous power-user tools in the world is switching to an AI chat interface 😬 "This will be the new Terminal. This will be the primary way most interactions are happening..." wired.com/story/the-bloo…
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Eiso Kant
Eiso Kant@eisokant·
Today we’re shipping Laguna M.1 and Laguna XS.2 – our first public models. We’re also shipping our agent harness and a preview product experience. Both models were trained from scratch on our own stack: data pipelines, training infrastructure, and agent RL.
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Shawn Simister
Shawn Simister@narphorium·
Really great discussion with @ryolu_ at Cursor HQ last night "...how much of your own eyes do you want to put in there? How much do you want to delegate? Because the agents default is slop"
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Dan Shipper 📧
Dan Shipper 📧@danshipper·
im writing an essay in proof using codex's in-app browser. i type directly in the document, and codex loops in parallel on the left, collaborating with me in realtime. this is obviously the future:
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Shawn Simister
Shawn Simister@narphorium·
@iScienceLuvr I actually remember telling colleagues that I wished the models would spend more time thinking before they answered 2 years and 10 months ago
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Tanishq Mathew Abraham, Ph.D.
Tanishq Mathew Abraham, Ph.D.@iScienceLuvr·
If you told me three years ago that my ChatGPT queries usually take several minutes to get a response and I would be HAPPY that it takes longer, I would think you're insane.
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Peter Petrash
Peter Petrash@petekp·
i'd recommend to any designer to just go all-in on claude code and skip the VC-backed GUI churn. the meta is is to stay close to the models and to work with the raw 'intelligence' material without an intermediary in the way. to develop transferrable fluency. to build an intuition for what today's models are good and bad at, and how they're evolving; what each new model iteration unlocks that wasn't quite feasible before. to viscerally feel the rising incline in capabilities. you will incrementally ratchet up your AI instinct. your leverage will increase. you'll find yourself capable of taking on more ambitious projects and *thinking* more ambitiously, more "agentically". you'll realize you can just build your own tool for that task. you'll have periodic epiphanies that unlock a new levels of abstraction and leverage, like when you realize you can have claude use claude, or write its own evals, or you develop workflows to have it run overnight and present you with lots of options. don't throttle your growth.
Shashi (シャシ)@shashpicious_

we’re not really “designing” right now, we’re just constantly switching contexts trying to not get left behind every week there’s a new tool claiming to be the future → paper, pencil, magicpatterns, magicpath… now noon shows up with $44M and changes the narrative again so instead of going deep, everyone’s just sampling everything trying prompts here, generating screens there, tweaking in figma, jumping to code, back to AI again half the industry is already inside code editors the other half is still figuring out which tool is even worth committing to fomo is doing more damage than we realise because depth needs stability and right now the stack itself is unstable so no one is mastering anything everyone is just trying to be early eventually this will settle and a default will emerge till then, we’re all just beta testers pretending to have a workflow 👀

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Shawn Simister
Shawn Simister@narphorium·
@geoffreylitt I just add everything to "Things to Try.md" and then wait a week. Once the hype recedes its easier to pick a few
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Geoffrey Litt
Geoffrey Litt@geoffreylitt·
Pretty sure the only way to keep up with all the new AI tools is to not have a job
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lauren
lauren@poteto·
i'm increasingly convinced that the value of orchestrating many agents in parallel comes from going deep, not broad. you want to go deeper on a single or a few problems, so you can maximize your chances of getting great results: - best of N style races to find the best solution - adversarial review - multiple agents trying to repro a reported issue - use different models for different types of workloads to quote @mattpocockuk, "code is not cheap". this beats trying to context switch across many agents working on 10 different problems. the bottleneck is still me trying to remember and keep in my own context window what my agents work on. i think there will be ways to solve this with better ui. there's also the element of trust. the more trust you have, the higher up the perspective ladder you can go. when you have little trust, you must micromanage each and every agent. when you can let go, you can delegate more. this is exactly like managing people!
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Shawn Simister
Shawn Simister@narphorium·
Someone should build DumbDetector. Like DownDetector but for crowdsourcing which AI models are being dumb today
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Kath Korevec
Kath Korevec@simpsoka·
What genuine humans. Enjoyed this talk from @soleio with @rsms. Got to ask Rasmus, “what kinds of attributes do you look for in candidates that reassure you they’ll be a good hire, that they care, that they dig into the details, sweat the pain, etc.” He said, “sometimes you have to hire the people who are borderline annoying to work with.” And that resonated so much. Many thanks to both of you!
Soleio@soleio

Optimism is infectious. Thanks for the great stories and insights, @rsms

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