Ren

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Ren

Ren

@KangQR

building AI-native products in public fintech, agents & thoughtful software founder, designer, developer

Toronto, Ontario Katılım Ocak 2017
180 Takip Edilen35 Takipçiler
Ren
Ren@KangQR·
the biggest lesson ai borrowed from databases: garbage in, garbage out never went away.
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Ren@KangQR·
Can't believe I used two ChatGPT resets yesterday, but now getting three more, what happened??
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Ren
Ren@KangQR·
@benln What’s wrong with Toronto
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Ben Lang
Ben Lang@benln·
Cafe Cursor is coming up in these cities: • LA - 7/15 • Philly - 7/16 • Lisbon - 7/17 • Zambia - 7/18 • Salvador - 7/20 • SF - 7/20 • Medellin - 7/22 • Rosario - 7/24 • Dallas - 7/26 • Cologne - 7/30 • Bali - 8/3 • Bangkok - 8/9 • Casablanca - 8/9 More being added
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Ren@KangQR·
Being using Dyson PH2 for a little over a year now. Decent quality and have it hooked via HA to Apple home app. I personally don’t like the humidifier that much, but given I’m in Toronto where winter is pretty dry, it’s a nice thing to have that when needed occasionally. Awesome customer support from Dyson too
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@levelsio
@levelsio@levelsio·
What's the best air purifier you know that is easily controllable with Home Assistant etc without hacking and hardware add ons? I need something that can react to the Airthings PM1/PM2.5 sensor and start purifying then We have clean air but lots of construction near so we get construction dust
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Ren@KangQR·
Genuinely curious, should I leave my MacBook Pro on 24/7 for codex or I should get a Mac VS env for all the coding projects? Ps I don’t have a Mac mini and not planning to buy one yet
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Saurabh Suri
Saurabh Suri@surim0n·
toronto has a lot of 🇨🇦 founders and no group chat. fixing that. slack/whatsapp group for people building. share progress, and most importantly UNBLOCK each other first happy hour once there's enough of us. what you also get: office hours from a claude & cognition ambassador reply "toronto"
toki@tokifyi

starting a whatsapp group for vancouver founders 🇨🇦 somewhere to chat, share what you're building, help each other out + maybe do a founders happy hour irl 👀 comment “vancouver” if you want in

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Ren
Ren@KangQR·
Satya’s post reminded me that AI isn’t just another software upgrade. It’s changing the economics of company building. Every founder should be asking the same question: If I were starting this company today, with today’s AI, would I build it the same way? I don’t think the answer is yes.
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Ren
Ren@KangQR·
That’s why I’m less interested in benchmark improvements than workflow improvements. A 5% better model is nice. A founder who can ship twice as fast because their entire development process is AI native is much harder to compete with.
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Ren
Ren@KangQR·
I think we’ll see a growing gap between two types of startups. Companies that use AI to reduce costs. Companies that use AI to build products that simply weren’t economically possible before. The second category is where the outsized returns usually come from.
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Ren
Ren@KangQR·
If one founder can build what previously required five people, venture math changes too. Less capital to reach product-market fit. Longer runways. Faster iteration. More experiments. That doesn’t make venture less important. It changes where capital creates leverage.
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Ren
Ren@KangQR·
Historically, startups scaled by hiring. More engineers. More designers. More PMs. More operations. Now every new model release increases the output of the same team. The production function is changing.
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Konrad
Konrad@KonradsKrypto·
If ur not IRL at Wealthsimple wya? (I do not have their card)
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Ren
Ren@KangQR·
It’ll be who builds the best AI operating system for themselves. That means: • repeatable prompts • reusable workflows • documented decisions • MCP servers and internal tools • knowing when not to use AI Models are becoming commodities faster than most people expected. Personal systems are much harder to copy. If you had to keep only one part of your AI workflow tomorrow, what would it be?
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Ren@KangQR·
Hot take: The next competitive advantage in software won’t be who has access to the best AI model.
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Ren
Ren@KangQR·
Genuinely curious, If your team adopted capable AI agents tomorrow, what would slow them down first: permissions, documentation, data quality, or process? Or even anything else I didn’t think of?
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