quinn

@_CallMeMacy @speedrun Applying right now, with my automated legal timekeeping wedge, see ya soon

Need more reasons to apply for @speedrun 007? How about access to enterprise buyers and hands-on sales training? Sound too good to be true? It's not.

A few hours ago @sdianahu shared how to build an AI-Native company in the most clear way I've seen yet Historically companies ran as open loops: ideas go in, outputs come out, feedback is in the wind In an AI-native company it has to be closed loops! Every process feeds back into your company's AI context so you can iterate That's how we're building ours. ground up, closed loops and feedback, and we'll be helping law firms close their loops too What's the next loop you need to close?

UCSB Accelerator, Day 1 Supplies provided by @cursor_ai @ucsbaccelerator @liveplayahouse

@johnplins SBHacks 26! Because I got 1st place with my interactive voice-native podcast companion app :3

What was your fav hackathon you ever participated in and why

Feel great to finally start getting pricing feedback, yc start up school rly has the sauce

@johnplins That’s sick 🔥

Put your landing page in the comments and I'll lyk if I understood what it does within 5 seconds of opening it #StartupGrowth

Last week: 0 pilots. This week: 3. Free or paid trial for B2B SaaS?

Gong grew from $200k ARR to $200M ARR and $7.2B valuation in a 5 year span. Buyers told us our demos were 2nd to none. 9 lessons I learned about SaaS demos I'll never forget:

if you're a performance marketer, here's how I use a custom Claude Cowork plugin to manage Google Ads at @AnthropicAI. it connects to the Google Ads API via MCP, encodes my common paid search workflows into skills, and works on desktop and Dispatch.

amazing

Been playing with remotion pretty sick, exicted to try out the skills ppl are makin

We'll get em next time o7

A perfect example of a company betting on humanity's success and building for the abundance of the future. Genius.

If You're an Entrepreneur: Stop designing businesses for 2024 scarcity. Design for 2030 abundance. Assume intelligence is free, energy is unlimited, and robotic labor costs pennies per hour. What becomes possible that's impossible today?

1 hour of TravisCore to build and accelerate to

🚨Breaking: Someone just open sourced a knowledge graph engine for your codebase and it's terrifying how good it is. It's called GitNexus. And it's not a documentation tool. It's a full code intelligence layer that maps every dependency, call chain, and execution flow in your repo -- then plugs directly into Claude Code, Cursor, and Windsurf via MCP. Here's what this thing does autonomously: → Indexes your entire codebase into a graph with Tree-sitter AST parsing → Maps every function call, import, class inheritance, and interface → Groups related code into functional clusters with cohesion scores → Traces execution flows from entry points through full call chains → Runs blast radius analysis before you change a single line → Detects which processes break when you touch a specific function → Renames symbols across 5+ files in one coordinated operation → Generates a full codebase wiki from the knowledge graph automatically Here's the wildest part: Your AI agent edits UserService.validate(). It doesn't know 47 functions depend on its return type. Breaking changes ship. GitNexus pre-computes the entire dependency structure at index time -- so when Claude Code asks "what depends on this?", it gets a complete answer in 1 query instead of 10. Smaller models get full architectural clarity. Even GPT-4o-mini stops breaking call chains. One command to set it up: `npx gitnexus analyze` That's it. MCP registers automatically. Claude Code hooks install themselves. Your AI agent has been coding blind. This fixes that. 9.4K GitHub stars. 1.2K forks. Already trending. 100% Open Source. (Link in the comments)

Grateful to be invited to such an inspiring event, got to interact with so many bright minds Something that stuck with me is the untapped opportunity of creating new types of data and figuring out how to put it to use Already miss sf can’t wait be back

@mihail_eric This is so cool, wish I could take your class but I'm a UCSB math student, is it available online yet

I've spent 10 months developing the syllabus for our new Stanford CS course: 𝗧𝗵𝗲 𝗠𝗼𝗱𝗲𝗿𝗻 𝗦𝗼𝗳𝘁𝘄𝗮𝗿𝗲 𝗗𝗲𝘃𝗲𝗹𝗼𝗽𝗲𝗿. The most important question I asked myself about AI software: in an age when the ground is shifting under you all the time, what principles won't go out-of-date next week? Here's what I came up with: 𝗪𝗲𝗲𝗸 𝟭: 𝗜𝗻𝘁𝗿𝗼𝗱𝘂𝗰𝘁𝗶𝗼𝗻 𝘁𝗼 𝗖𝗼𝗱𝗶𝗻𝗴 𝗟𝗟𝗠𝘀 𝗮𝗻𝗱 𝗔𝗜 𝗗𝗲𝘃𝗲𝗹𝗼𝗽𝗺𝗲𝗻𝘁 Topics: what is an LLM actually, how to prompt effectively 𝗪𝗲𝗲𝗸 𝟮: 𝗧𝗵𝗲 𝗔𝗻𝗮𝘁𝗼𝗺𝘆 𝗼𝗳 𝗖𝗼𝗱𝗶𝗻𝗴 𝗔𝗴𝗲𝗻𝘁𝘀 Topics: agent architecture, tool use, MCP 𝗪𝗲𝗲𝗸 𝟯: 𝗧𝗵𝗲 𝗔𝗜 𝗜𝗗𝗘 Topics: context management and code understanding, PRDs for agents, IDE integrations 𝗪𝗲𝗲𝗸 𝟰: 𝗖𝗼𝗱𝗶𝗻𝗴 𝗔𝗴𝗲𝗻𝘁 𝗣𝗮𝘁𝘁𝗲𝗿𝗻𝘀 Topics: Managing agent autonomy levels, human-agent collaboration patterns 𝗪𝗲𝗲𝗸 𝟱: 𝗧𝗵𝗲 𝗠𝗼𝗱𝗲𝗿𝗻 𝗧𝗲𝗿𝗺𝗶𝗻𝗮𝗹 Topics: AI-enhanced command line interfaces, sandboxed execution environments 𝗪𝗲𝗲𝗸 𝟲: 𝗔𝗜 𝗧𝗲𝘀𝘁𝗶𝗻𝗴 𝗮𝗻𝗱 𝗦𝗲𝗰𝘂𝗿𝗶𝘁𝘆 Topics: Secure vibe coding, history of vulnerability detection, AI-generated test suites 𝗪𝗲𝗲𝗸 𝟳: 𝗠𝗼𝗱𝗲𝗿𝗻 𝗦𝗼𝗳𝘁𝘄𝗮𝗿𝗲 𝗦𝘂𝗽𝗽𝗼𝗿𝘁 Topics: what AI code systems can we trust, debugging and diagnostics, intelligent documentation generation 𝗪𝗲𝗲𝗸 𝟴: 𝗔𝘂𝘁𝗼𝗺𝗮𝘁𝗲𝗱 𝗨𝗜 𝗮𝗻𝗱 𝗔𝗽𝗽 𝗕𝘂𝗶𝗹𝗱𝗶𝗻𝗴 Topics: design and frontend for everyone, rapid UI/UX prototyping and iteration 𝗪𝗲𝗲𝗸 𝟵: 𝗔𝗴𝗲𝗻𝘁𝘀 𝗣𝗼𝘀𝘁-𝗗𝗲𝗽𝗹𝗼𝘆𝗺𝗲𝗻𝘁 Topics: monitoring and observability for AI systems, automated incident response, triaging and debugging 𝗪𝗲𝗲𝗸 𝟭𝟬: 𝗪𝗵𝗮𝘁'𝘀 𝗡𝗲𝘅𝘁 𝗳𝗼𝗿 𝗔𝗜 𝗦𝗼𝗳𝘁𝘄𝗮𝗿𝗲 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝗶𝗻𝗴 Topics: future of software development roles, emerging AI coding paradigms, industry trends and predictions

@chadwahl missed opportunity to not make cs degrees thicker

The only thing this is good for is raising my monitor up