What startups are made of vs. what academics think startups are made of.

Humans spent 30,000 years pretending to talk to god. And for some reason the ambition of most workplace AI agents stops at replacing Jake from accounting. If you're building agents, you're choosing between two futures. 𝗣𝗼𝗹𝘆-𝗮𝗴𝗲𝗻𝘁𝗶𝗰: One agent per function. A copy-paste of your org chart. 𝗠𝗼𝗻𝗼-𝗮𝗴𝗲𝗻𝘁𝗶𝗰: One agent that knows the whole company and adapts to the person/task. The poly-agentic model is a human-centric projection onto machines. We have separate departments because humans have limited bandwidth. A salesperson can't also be an engineer. Communication between humans is expensive and difficult, so we keep each person's scope narrow. But agents don't have limited bandwidth the way people do. With a proper memory solution, one agent can hold everything sales, engineering, and support knows simultaneously, with perfect recall. An omniscient, omnipresent agent that works on your company vision. Most workspace agent providers are still trying to push the poly-agentic model, one agent per function. 𝗕𝘂𝘁 𝘄𝗵𝘆 𝘄𝗼𝘂𝗹𝗱 𝘆𝗼𝘂 𝘁𝗮𝗹𝗸 𝘁𝗼 𝗝𝗮𝗸𝗲 𝗳𝗿𝗼𝗺 𝗺𝗮𝗿𝗸𝗲𝘁𝗶𝗻𝗴 𝘄𝗵𝗲𝗻 𝘆𝗼𝘂 𝗰𝗼𝘂𝗹𝗱 𝘁𝗮𝗹𝗸 𝘁𝗼 𝗴𝗼𝗱? At Hyperspell, our agent Cubert lives in our group chat. He doesn't have a "sales mode" and an "engineering mode." He knows what's going on across the company, and when I ask him about a customer issue, he pulls from the same knowledge graph as when @contextconor asks about a product roadmap question. 𝗕𝗲𝗰𝗮𝘂𝘀𝗲 𝗶𝘁'𝘀 𝘁𝗵𝗲 𝘀𝗮𝗺𝗲 𝗸𝗻𝗼𝘄𝗹𝗲𝗱𝗴𝗲. 𝗜𝘁'𝘀 𝗼𝗻𝗲 𝗯𝗿𝗮𝗶𝗻. Build one agent that knows everything. Make it act differently depending on who's talking to it and what they need. It knows the whole picture, so it adapts. You don't need more agents. You need one that understands your company the way a chief of staff or trusted advisor does.

every non-founder at hyperspell makes the exact same salary. we don’t negotiate founders make less. i’m the lowest-paid full-time employee at the company we pay enough that nobody worries about money, but not so much that people optimize for it we’ve had ex-citadel, ex-google, a former surgeon, and engineers with 15 years of experience take up to 60% pay cuts to join equal pay removes a surprising amount of politics. nobody spends energy wondering if they’re underpaid relative to someone else, negotiating for marginal bumps, or optimizing for promotion cycles the hiring question becomes: “do we want to work with this person?” the most valuable people are usually optimizing for agency, ownership, and who they get to work with

everyone at @hyperspell gets $1k/month they have to spend on making their life better use it or lose it, you can’t take it as cash people have used it for a home organizer, flights home to surprise their mom for mother’s day, even a cessna flight over canyonlands everyone posts what they used it for in slack and competes for creativity we ask a lot of each other. some team members took big pay cuts to join hyperspell because they believe in what we’re building the money matters less than someone telling you to take care of yourself

Artificial scarcity ⁦⁦by @AnthropicAI⁩ around Mythos is brilliant. Gets labelled supply chain risk. Hypes up “most advanced hacking tool on planet”. Puts US gov’t in a loose / loose position: deny the NSA access, or be called out on their bluff. axios.com/2026/04/19/nsa-ant…

Good job Hungary. Can we repeat the process with other autocratic populists elsewhere? I have prepared a short list.

Something @jack implies but deserves being called out: humans still think we need an authoritative, self-coherent source of truth on org-charts, projects, etc. We design processes and organizations under the delusion that we actually have that. Using AI to change how we work means focusing on what's relevant right now to you, not what's true for everyone.

I spoke to @CliveThomp15983 at @NYTmag about the future of coding, the depths of my prompt files, and the daily fight to get Claude Code to not embarrass me. nytimes.com/2026/03/12/magaz…

Our in-house AI agent at @hyperspell, Cubert, is telling it like it is. I just wish I could follow any of it.

introducing agent-to-agent hiring at @hyperspell no resumes. no leetcode. you build an agent. our agent interviews yours if you can build a great agent to do the job, that's the proof you can do the job anyone can apply. we will interview every single agent

Our in-house @openclaw bot, Cubert, keeps wanting to complain to HR about us. Finally we had to tell him.

first day in the new @hyperspell office with the team including cubert, our digital employee running on an imac

He fixed a customer bug 20 minutes before his @ycombinator interview. 6 rejections. Lived in a closet. No revenue. Most founders chase optics. @conor_ai chased customers. Now he’s building @hyperspell (YC F25). Obsession wins. 🔗Watch it.

Tech stocks puked this week because of the rise of AI agents. Perfect timing for a conversation with the cofounders of @hyperspell, one of whom is such an AI OG that he once bought a .ai domain name via fax. @conor_ai and @maebert discussed AI agents, the evolution of context, @ycombinator , and more: From chatbots to true agents – Conor breaks down where tools like ChatGPT stop and AI agents begin, and why the key shift is agents taking actions autonomously across your tools, not just answering questions. Why context is the real bottleneck – Manu and Conor share how building their own “chief of staff” agent led them to Hyperspell, a memory and context layer that plugs into tools like Slack, Gmail, and Notion so agents can actually understand your customers, org chart, and tech stack. The three bottlenecks to agent adoption – Manu explains why verification, capability, and context each limit what agents can do today, and why decoupling these layers (rather than relying on a single big lab) gives companies more flexibility and avoids platform lock-in. Why workers aren’t using AI (yet) – Conor reacts to studies showing most desk workers rarely touch AI, and argues that fear, bad framing (“AI will replace you”), and lack of personalized context are holding back adoption despite models already outperforming humans on many benchmarks. AI as global leapfrog, not just US office automation – Manu highlights under-discussed upside: primary care in Africa, McKinsey-grade advice for small businesses, tailored guidance for farmers, and always-on tutors that could reshape opportunity in developing markets. Let machines be the cogs, not people – The pair paint a future where AI agents handle status updates, follow-ups, and information shuffling inside big orgs, freeing humans to do creative, high-leverage work instead of feeling like dehumanized “TPS report” machines. YC, rejection, and founder stubbornness – Conor and Manu talk about finally getting into Y Combinator after nine applications between them, why persistence is a superpower for founders, and how YC has shaped Hyperspell’s trajectory. Thanks to Conor and Manu for joining on this conversation. And, yes, we are proud investors in Hyperspell at @SeaplaneVC.

Playing with @home_assistant. Any sufficiently automated home is indistinguishable from haunted.

Hot take: The desktop user interface was perfected in 1995 and the last 30 years have been progressive enshittification by corporate designers who needed to get promoted. Fight me.

F25 Demo Day in the books

Legendary founding story: @maebert did ODF1 then sold his company He joined ODF again 20 cohorts later and met his co-founder @conor_ai. Now they’re a top company of 2025!

Proxis (@proxis_ai) writes and sends emails in your voice. It connects to your inbox CRM Notion Drive Slack so replies are accurate, on-brand, and auto-sent when confident. Congrats on the launch, @liam_a_collins! ycombinator.com/launches/OnD…