Nick Manning ⌨️

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Nick Manning ⌨️

Nick Manning ⌨️

@seenickcode

Solopreneur, author, mentor, proud father of two. Building https://t.co/XgY4W2H814. 🤘 Prev: Google, 3x startup CTO. 👨‍💻 Sharing my findings along the way.

EU 🇪🇺 Se unió Eylül 2008
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Nick Manning ⌨️
Nick Manning ⌨️@seenickcode·
So I'm crafting content for a small book and course over this winter break - heck why not? Topic not yet public! Yesterday was day 0. I’ll be documenting my naive shot at this - because again, why not? Maybe it can cajole others to give a go? At minimum I can get some helpful feedback along the way from others. Here’s what I did yesterday starting from absolute 0: 1. I recorded a brain dump video, talking about who, what, why, how etc about my idea. Somehow video recording myself "put me on the spot" and I was able to focus more on conciseness. 2. I generated a book/course outline from this. I uploaded the video to otter.ai to transcribe it. I refined it into a tentative chapter outline and dumped it into Notion. Side note: I typically like the otter.ai iOS app to quickly record my thoughts so that's why I went with that. And for some reason I'm not a huge fan of writing like this in Markdown (i.e. via Obsidian) so I'm trying Notion. I like the writing experience in Notion especially with the prospect of later collaborating with an editor later. 3. Then I recorded a brain dump video on "topic A”. So this time not a video, just for convenience. I used willowvoice.com's macOS app to just talk away for 30 minutes directly into Notion. Talking for about 30 minutes gave me roughly 2000 words. Calculating how much I need to do this gave me a lot of motivation. For example, I want to craft a book and course where someone can choose to read or consume video. For video, I want to keep it to max 2-3 hours so I'm going for 10k words per hour. Therefore I whittle it down 2000 words with heavy editing. I think that after a few weeks of repeating this process I can achieve this goal, then heavily edit the content down further. Notes for the engineers reading this (warning, needless geeking out here). I may consider just self publishing later later + host the video version on a microsite served by a simple web-app that pulls the content straight from Notion (cached of course when served up). I can later host multiple publications courses using that same web app as it could support multi-tenant (extract domain from HTTP header -> determine tenant to serve up, host on same VPS for dollars a month). @seenickcode" target="_blank" rel="nofollow noopener">substack.com/@seenickcode if anyone wants to keep tabs on my progress and gain some insights. Definitely not an expert on this entire process but I think the conversations will be interesting along the way.
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Nick Manning ⌨️ retuiteado
sarah guo
sarah guo@saranormous·
Caught up with @karpathy for a new @NoPriorsPod: on the phase shift in engineering, AI psychosis, claws, AutoResearch, the opportunity for a SETI-at-Home like movement in AI, the model landscape, and second order effects 02:55 - What Capability Limits Remain? 06:15 - What Mastery of Coding Agents Looks Like 11:16 - Second Order Effects of Coding Agents 15:51 - Why AutoResearch 22:45 - Relevant Skills in the AI Era 28:25 - Model Speciation 32:30 - Collaboration Surfaces for Humans and AI 37:28 - Analysis of Jobs Market Data 48:25 - Open vs. Closed Source Models 53:51 - Autonomous Robotics and Atoms 1:00:59 - MicroGPT and Agentic Education 1:05:40 - End Thoughts
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Thariq
Thariq@trq212·
We just released Claude Code channels, which allows you to control your Claude Code session through select MCPs, starting with Telegram and Discord. Use this to message Claude Code directly from your phone.
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Stitch by Google
Stitch by Google@stitchbygoogle·
Meet the new Stitch, your vibe design partner. Here are 5 major upgrades to help you create, iterate and collaborate: 🎨 AI-Native Canvas 🧠 Smarter Design Agent 🎙️ Voice ⚡️ Instant Prototypes 📐 Design Systems and DESIGN.md Rolling out now. Details and product walkthrough video in 🧵
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B Singh 🐝
B Singh 🐝@bissuusingh·
Plumbers are not safe
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Tuki
Tuki@TukiFromKL·
🚨 Do you understand what just happened? A guy in Florida asked ChatGPT to sell his house. Not help him sell it. SELL IT. Pricing, Marketing, Showings, Contract.. Everything. Sold in 5 days. The average real estate agent takes 6% commission. On a $400K house that's $24,000. For what? Putting it on Zillow and sending you emails? This man paid $20 a month for ChatGPT and did the whole thing from his couch. Real estate agents spent 20 years telling you the process is too complicated for normal people. That you need a professional. That the paperwork is too risky without them. It was gatekept. And a chatbot just kicked the gate open.. Lawyers are next, Accountants are next, Financial advisors are next.. Every profession that made you feel stupid so you'd pay them is about to get the same treatment. The middleman economy is dying. And it's not dying because AI is smarter than them.. It's dying because AI proved you were always smart enough to do it yourself. You just weren't allowed to..
Dexerto@Dexerto

Florida man sold his house in just 5 days after letting ChatGPT handle the entire process instead of a real estate agent The AI handled pricing, marketing, showings, and even helped draft the contract

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Claude
Claude@claudeai·
A small thank you to everyone using Claude: We’re doubling usage outside our peak hours for the next two weeks.
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Nishkarsh
Nishkarsh@contextkingceo·
We've raised $6.5M to kill vector databases. Every system today retrieves context the same way: vector search that stores everything as flat embeddings and returns whatever "feels" closest. Similar, sure. Relevant? Almost never. Embeddings can’t tell a Q3 renewal clause from a Q1 termination notice if the language is close enough. A friend of mine asked his AI about a contract last week, and it returned a detailed, perfectly crafted answer pulled from a completely different client’s file. Once you’re dealing with 10M+ documents, these mix-ups happen all the time. VectorDB accuracy goes to shit. We built @hydra_db for exactly this. HydraDB builds an ontology-first context graph over your data, maps relationships between entities, understands the 'why' behind documents, and tracks how information evolves over time. So when you ask about 'Apple,' it knows you mean the company you're serving as a customer. Not the fruit. Even when a vector DB's similarity score says 0.94. More below ⬇️
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Natia Kurdadze - SEO
Natia Kurdadze - SEO@seonatia·
If you are a startup founder and want to boost your website's SEO, submit it to these high DA sites: 1. Crunchbase 2. Weebly 3. Gthub 4. Pixabay 5. Foursquare 6. Blogger 7. About me 8. Pexels 9. Flickr 10. Hackernoon 11. AuthorSTREAM 12. Strikingly 13. Site123 14. BookLikes 15. Devpost 16. Gifyu 17. Gab 18. Imgur
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Boris Cherny
Boris Cherny@bcherny·
Released today: /loop /loop is a powerful new way to schedule recurring tasks, for up to 3 days at a time eg. “/loop babysit all my PRs. Auto-fix build issues and when comments come in, use a worktree agent to fix them” eg. “/loop every morning use the Slack MCP to give me a summary of top posts I was tagged in” Let us know what you think!
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Nick Manning ⌨️
Nick Manning ⌨️@seenickcode·
I asked Claude about an idea that ChatGPT wrote and it bad-mouths ChatGPT 😂. “Alright, the ChatGPT analysis is directionally correct but it's doing that thing where it hypes everything up with emoji and formatting to make you feel great rather than pressure-testing the idea.”
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Marc Lou
Marc Lou@marclou·
I’ve met hundreds of people with great ideas who never made it. But I’ve never met anyone who launched 20 startups and failed.
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Alex Finn
Alex Finn@AlexFinn·
Do you understand what this means? Are you aware how much the world just changed? You can now run frontier intelligence on a potato Your $600 Mac Mini can now run unlimited super intelligence for free. No authoritarian AI companies can cut you off Do this immediately, no matter what device you’re on: 1. Download LMstudio 2. Find these models in the search 3. Look for the MLX ones if you’re on Mac 4. Download and load them 5. Ask your OpenClaw to use them for most tasks I thought the future was a year away. Nah. It’s today
Qwen@Alibaba_Qwen

🚀 Introducing the Qwen 3.5 Small Model Series Qwen3.5-0.8B · Qwen3.5-2B · Qwen3.5-4B · Qwen3.5-9B ✨ More intelligence, less compute. These small models are built on the same Qwen3.5 foundation — native multimodal, improved architecture, scaled RL: • 0.8B / 2B → tiny, fast, great for edge device • 4B → a surprisingly strong multimodal base for lightweight agents • 9B → compact, but already closing the gap with much larger models And yes — we’re also releasing the Base models as well. We hope this better supports research, experimentation, and real-world industrial innovation. Hugging Face: huggingface.co/collections/Qw… ModelScope: modelscope.cn/collections/Qw…

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