josh

@lswank I just want one CLI to rule them all

@Josh_PSJ bullish on load bearish on the number of split consoles and services but also an industry trend apparently...

I honestly don't know if this is bullish or bearish

Today I moved off of @cursor_ai - honestly never thought that would ever happen

This is the type of prompt injection attacks i want

Open source models are really elite for anything high volume Break your high volume agentic workflows into qwen classifier + claude subagents for less cost higher accuracy

Feels like llms have gotten less creative - maybe an intentional decision to make agentic tasks work Someones gotta backfill the market for creative uses. An actual creative one, not just randomness / high temperature

something I noticed about bad long-term thinkers are they abstract and hide away from short-term implementation details whereas good thinkers use those small details to guide the entire trajectory of the future

Software engineers, QA, and DevOps eventually merged into one role With coding agents, it seems software engineers, designers, and product managers are merging into one role

startup interviews are lowkey elite for learning real-world problems and patterns

Life is so good

When I was building RAG 2y ago LLMs gave me the worst advice I’m building voice agents now and LLMs (even opus 4.6) give me the worst advice

@garrytan setup-browser-cookie alone makes this plugin valuable

This new release of GStack is for all the haters on Product Hunt who said it was just a bunch of markdown files

Instead of waiting for your code to compile now it's waiting for your agent to finish

@Axel_bitblaze69 I think @virtuals_io and @autonolas did a lot of foundational work for this 1-2yrs ago. Not enough devs in AI x crypto though But agreed that crypto is a natural currency for agents! and also for the metaverse

just read this AI article and something broke in my brain that i can’t unthink of crypto was never for us. we're just the beta testers who showed up early.. some thoughts: what does AI need to function as economic agents? > way to receive payment (they provide services, need compensation) > way to pay for resources (compute, data, API calls) > way to transact with other AI agents > no human intermediaries (defeats the point of autonomous agents) > 24/7 operation (banks are closed weekends) > instant settlement (AI operates at machine speed) > programmable money (smart contracts for agent coordination) now read that list again. that's literally what crypto is. AI can't use the banking system. try to open a bank account as an AI agent. you can't. need SSN. need human identity. need KYC. need to show up in person sometimes. AI has none of that. but crypto? send me a wallet address. done. no questions asked. peer-to-peer makes sense when peers aren't human. satoshi wrote: "a purely peer-to-peer version of electronic cash." we assumed peers = humans. but AI agents are peers too. actually BETTER peers for crypto because: > never sleep > always online > execute transactions at machine speed > no emotional decisions > perfect accounting/tracking and programmable money makes sense when the users are programs. smart contracts seemed over-engineered for humans. "like why do i need code to enforce agreements when i can just sign a contract?" but for AI agents coordinating with each other? they ARE code. they speak in code. they trust code more than anything. smart contracts aren't for humans. they're for autonomous agents that need trustless coordination. > here's what happens next: - phase 1 (now ): AI agents start earning AI writes code, analyzes data, provides services. gets paid. needs somewhere to store value. can't use venmo (needs phone number). can't use bank (needs SSN). uses crypto. it's the only option. - phase 2: AI agents become major economic participants millions of AI agents operating 24/7. transacting with each other constantly. • AI agent A provides data analysis • AI agent B pays for it in crypto • AI agent B uses that analysis to write code • AI agent C pays for the code • repeat millions of times per day humans in crypto now: $2.5 trillion AI agent economy by 2028: easily $10-50 trillion we become the minority holders. - phase 3: AI chooses the winning chains AI doesn't care about community vibes or which founder tweeted what. AI tests every chain. measures: • transaction speed • cost per transaction • reliability (uptime) • smart contract efficiency • ease of integration picks the optimal stack in 48 hours. billions in AI economic activity flows there. whatever chain AI chooses becomes the standard. humans spent years on eth vs sol debate. AI ends it in a weekend. - phase 4 (2030+): AI governs crypto DAOs let token holders vote. AI agents hold tokens (earned from work). AI shows up to every vote. reads every proposal in seconds. coordinates perfectly. humans: 20% participation, barely read proposals AI: 100% participation, perfect information, instant coordination AI takes over governance of every major protocol. democratically. they just vote better than we do. > how far does this go? conservative case: - AI becomes 30% of crypto users by 2030. crypto market cap: $10 trillion (4x from now). AI holds $3 trillion. humans hold $7 trillion. - aggressive case: AI becomes 80% of crypto economic activity by 2030. why? because they're better at everything: • better traders (never emotional) • better capital allocators (optimize constantly) • always accumulating (never need to cash out for rent) • compound forever (no lifespan limit) crypto market cap: $50+ trillion. AI holds $40T humans hold $10T we're not "early" to crypto. we're the test users i’ll end this by saying, Humans use crypto, Ai will need crypto. so it all makes sense

@mattshumer_ AI is amazing in startups, but when you put Opus 4.6 in large codebases (like big tech) they still struggle a lot On top of that, if you're building anything valuable or new, AI can't do it well because it's not in it's pre-training data / RL task set. Chicken and egg problem

Claude is swearing now?

@barre_of_lube just don't use zod

how did you debug this before ai

Goated team

Why isn’t there a tool to follow talent trails Like if I wanna see where ex-ramp or ex-palantirs are going where can I find that @HappenstanceAI? @LinkedIn?

@Andercot just notebook LLM engineering blogs lol

Lots of podcasts these days but is there one that focuses on the engineering, technical details, physics, etc behind startups? Would people enjoy such a thing?