@mtsliveOct 21

SITUATION EXPLAINED: Anthropic just announced Claude Duet, an app where Claude keeps working for you even after you step away. • It’s a proactive agent that comes to you with what needs attention, finishes tasks you hand it, and runs on its own cloud computer • Every morning it checks your email and calendar, flags what matters, and drafts replies for you to approve • Built on Opus 5.5, it connects to 6,000+ apps like Stripe, Notion, QuickBooks, and Ramp, and carries over your Claude memory and skills • It asks first before sending messages, paying, or signing anything • It’s a waitlist-only research preview for Pro and Max subscribers in the US @theojaffee: "It’s like Dots, it’s like Grok Bot. It’s like Muse, it’s like Instinct. It’s actually a little more than Instinct, I think. So it looks really exciting. Can’t wait to use it."

@aakashguptaOct 21

An AI agent got a $250 delay credit out of Delta for one person. Another one cancelled $1,300 a month in subscriptions its owner forgot about. Then I saw the ranking of all nine of these agents built on what users say in public, and the one I use every day came in 6th. Meta’s Muse is #1 with a score of 70.5. @feedbackbench is a new site from Enterpret for comparing AI personal agents on what real users say about them. It read Reddit, X, YouTube and both app stores from August 31 to October 18, kept only the posts where someone described their own use, and scored each agent on popularity and customer love. I’ve been using Instinct the most, so I had a horse in this. Instinct sits 6th at 46, behind OpenClaw and Hark (haven’t tried Hark yet). Hermes is 2nd and Grok Bot 3rd. Now hold the money up against that board. Instinct just raised $1 billion at a $10 billion valuation and sits two points above Google. Nous Research, which builds Hermes, got to 2nd on a $90 million raise at $1.5 billion. Zuckerberg said last week Meta was ready to spend up to $200 billion on AI without knowing if it would work, and its agent is the one at the top. Gemini Spark scores 44 and ChatGPT Dots 39, both below Instinct. That matches what I found when I tested both. The Delta credit and the cancelled subscriptions only happen if you let the thing into your inbox and your card, so trust is the whole product here. For my money this is the most interesting market in AI this year, and this is the first scoreboard for it that somebody other than the vendors wrote. Built by @enterpret_ai, link in the reply.

@alliekmillerOct 21

Instinct and @noahrshinn have shut off my access to the calling feature. Not sure if it's shut off for everyone or just mine because I had and shared a negative experience. If it's the latter, that would be a pretty shortsighted way to handle honest feedback. If others have access to it, let me know.

@alliekmillerOct 20

AI making calls to humans on behalf of other humans is still weird to me. Ex: I wanted to know if Michaels had a unicorn balloon in stock and how long it would take to inflate. I asked Instinct Concierge to handle it. First call went to voicemail. Second call was picked up by a human. Instinct chatted with the human, got the answer, and texted me back. Instinct doesn’t give you the transcript or a recording, so I have zero idea what the process looks like. Was the AI nice? Was it annoying? Did it give my full name? Was it easy to understand? I don’t love the idea of zero transparency on these interactions. Feels like we’re deprioritizing humans or hiding performance under the guise of privacy.

@omarsar0Oct 20

Is harness engineering dead? Absolutely NOT! Like the "prompt engineering is dead" and "RAG is dead" claims, this is just another misinformed claim used for clicks and ragebaiting. Mostly, it stems from a few recently published papers with poor experimental setups that focus only on SWE on already benchmaxxed SWE benchmarks. If we are talking about SWE, of course a lot of the harness stuff is getting absorbed by the model. And that's great. Thanks to better approaches for co-evolving harnesses and models. But in reality, you still need a stable, minimal harness to get high-quality results reliably and affordably. The big issue I see is that we assume SWE won't evolve. It already has, and as a result, teams are finding they need specialized harnesses to improve code review, cybersecurity, and work in more complex environments (multi-agent systems, sandboxes, etc.). The harness isn't just about prompts; it's the scaffolding that makes AI models work in the real world, covering security, safety guardrails, authorization, coordination, memory, scalable and new infra, efficiency, costs, and more. If you have been in computer science for long, none of these stay fixed. So how can anyone claim the scaffold/harness isn't needed? And worse, how can anyone claim these AI models will know all that, much of it proprietary and custom to every problem and domain? It gets more complex when you apply agents beyond SWE; domain-specific harnesses are popping up everywhere. These require entirely new ways to optimize context, memory, guardrails, security, and more. To make my point even clearer, look at the new wave of proactive and personal agents (Muse, Grok Bot, dots, Instinct, etc.). They involve clever, complex harness engineering. I think we will see vertical personal agents too, so the harness will get even more specialized. I can go on and on. I'd love to hear what other serious builders here are seeing.

@omooretweetsOct 19

If I was a brand or retailer, AI discoverability / agentic commerce would be my top priority right now. And, there's an extremely easy and free way to get a sense of how you "show up" to agents. 👇 First, create a dummy account on all the agent platforms (Muse, Instinct, Dots, etc.) Sign up with a fresh email that does not have context on your real identity, or even use a VPN to "go" to where your average user is! Then, ask the agent to perform a search that you'd want your product / platform to show up in. As an example, I prompted: "find me a winter coat for SF." Watch the agent go through the evaluation process (you can literally view the browser), and at each stage ask it questions like: - How did you identify the initial set of options for this search? What were your sources? - Were there any failures / blocks you encountered that eliminated any options? - What were the exact variables that your ultimate ranking or recommendation was driven by? Follow the process all the way through to the point of purchase. You will very quickly start to get a sense of how an agent thinks, edge case issues it runs into, etc. As an example, during my winter coat search via Muse I learned the following: - Patagonia bot blocked my agent - so Muse then went to / recommended other retailers that carried the jacket to make my purchase - The agent first searched options from its training data, largely informed by Wirecutter-style roundups, Reddit, and enthusiast forums. Then, it looked at connected merchants via the Meta Catalog. Then, it did live browser searches. It dropped any websites with SEO spam or fake reviews - REI was the ultimate winner as it didn't throw up any bot challenges or traffic blocks, and my agent prioritized verifiable inventory and same-day pickup (which I didn't ask it to!). It found a discount on REI vs. the original retailer so prioritized that as well

@harrystebbingsOct 17

Why the memory layer will become more and more important and how Instinct crushed it “One thing about agents that is rare today but will be incredibly common in the next few years is this memory layer. If you look at Instinct or Muse, one of the things that they have nailed is personalization and learning, making it seem like it is something for you. I think memory is super, super early.” @hwchase17 Love to hear your thoughts @DhravyaShah @taranjeetio @noahrshinn @natfriedman

@harrystebbingsOct 17

I have always considered @milesgrimshaw one of the smartest investors in venture. I remember Sept 2023, Miles came to our recording studio in London having just joined the @benchmark partnership. At the time, he had done one deal; a small company called @LangChain. Unknown to many but Miles raved about the founder @hwchase17. His excitement for the company was palpable. Today the company is worth $1.2BN and serves 35% of the Fortune 500. The other day I sat down with Harrison to discuss the big questions of the day and he allowed me to add my notes from the discussion below. -- 1. What Percent of Developer Salary Do You Spend on Coding Tools and How Has It Changed? LangChain spends roughly 30% of its engineering salary on coding tools, a share that has fallen over the last two months even as token usage has gone up. The team tracks coding agent usage in LangSmith, sets budgets the VP of engineering can raise, and controls the harness. Its in-house cloud coding agent uses prompt caching and routing to cut costs. What will this be in 12 months @BrendanFoody? 2. What Will Happen to the Inference Market? Harrison says he underestimated the demand for inference and for coding agents, both far bigger markets than he expected three or four years ago. Echoing Eric Vishria's line that "Everything just works," he believes any inference provider will work, and he does not expect demand to drop anytime soon. What does no one see about the inference market that everyone should see @spdholakia? 3. Why Harnesses Need to Be Neutral Companies want to be able to switch models, but the harness can be tightly tied to a model, and context today is intricately linked to the harness. The harness connects the model to data, APIs and memory. If memory is built in a way that is linked to the harness, and the harness is linked to the model, the company ends up stuck. Love to hear your thoughts on this one man @EnoReyes 4. Why the Memory Layer Will Become More and More Important and How Instinct Crushed It Memory is rare in agents today but will be incredibly common in the next few years. Instinct and Muse have nailed personalization and learning, so the product feels like it is for the individual user, through its tone or proactive follow-ups. Harrison still sees memory as super early. What does no one see that everyone should see about the state of memory and where it goes @noahrshinn @mvernal? 5. Will We Have One Horizontal Agent or Tons of Vertical Agents in the Consumer Realm? Consumers will have both, with horizontal agents interacting with vertical ones. Most apps should have a vertical agent because they can learn more about how a user interacts with them than a general agent can. Wrapping an app's many APIs in a single natural language agent also gives horizontal agents a better experience than raw APIs. Love to hear your thoughts on this @FDavidsonT 6. What Do Large Enterprises Care Most About Today? Cost has risen as a concern for large enterprises, though it still ranks below accuracy and above latency. Security is a bigger concern for large enterprises but still sits below accuracy and cost. 7. Why Is Benchmark the Best Fund? Benchmark invested in LangChain when it was just Harrison and Ankush, and the founders treated the firm as a third co-founder. As the company grew from two people to around 400, Benchmark has been its most consistent partner. @chetanp what does no one know about how Benchmark works with founders that everyone should know?

@alliekmillerOct 16

With Instinct, my Google usage has dropped 90%. And before you all complain in the comments, if you leave the X sphere, you’d hear most people still use Google too. I continued to use traditional search for the last four years since ChatGPT came out, not as much but continued. Why? Tbh I found it annoying to open the Chat app when I could open any browser and just dictate to the url bar. App load had more lag than browser load. The answer took more time. I didn’t want/need everything stored in my Chat memory. And Google AI overview, after the rocks in pizza debacle, really improved. I’m in iMessage all the time. It’s on my computer and phone and faster than an app. And if Dots were on iMessage, I’d use that instead.

@a16zOct 15

VGS's Terry Angelos and a16z's Alex Rampell on the one thing AI agent payments can't afford to break: the right to get your money back. Terry: "I asked Instinct to go and help me find these lights, and it found the lights at Walmart... when it came time to pay, Link [my payment wallet] didn't have a connection to Walmart. It can't just give my card over to the agent and over to Walmart." "If there's a problem... I call up my bank... And they say, 'Well, we don't see a Walmart transaction here... We just see a [Link] transaction.'" Alex: "One of the reasons why Visa and Mastercard have such impregnable positions is because they intermediate everything, and they set the rules, and chargebacks are very important." "It's a trust mechanism. I pay you for lights. You don't deliver the lights... You actually have rules by which I can kind of lodge a complaint." "That's high utility, actually even for the merchant... I'm much more willing to buy with a merchant knowing that if they don't actually deliver a product that works, I can get my money back." @terryangelos @arampell

@gregisenbergOct 15

More SF observations: 1. Seeing the word "inference" on billboards in SF still blows my mind. 99.9% of america has no idea what inference is and I wonder how many know what an agent is. Will Muse, Instinct, Dots etc will change that over the next 12 months? 2. You know who doesn't get enough credit? Manus. In March 2025 they shipped the blueprint for AI agents: every task gets its own computer in the cloud, you can watch it work, it writes a todo list and checks it off, and you walk away while it finishes. So much of what we use today runs on those ideas! 3. Your product now has to sell itself twice. First the agent has to pick it, then the human has to trust that pick enough to say yes. 4. I was talking to a guy who told me we should just destroy all the data centers. I think that sentiment is more common than people in SF realize. You can already see some of the big AI companies adjusting positioning their AI as something that helps people and gives them more time/cures for cancers etc. 5. AI is making people work 5x faster (at least), so for freelancers/agencies that charge per hour you're earning 5x less per unit of work. But your rate is the same? I think a lot of freelancers and agencies are about to have to rethink how they price. 6. Running a company now feels kinda dystopian sometimes, especially with a small team of a few humans and a lot of agents. Some days the Slack channel is mostly bots reporting to each other, and you're the only one in the room with a pulse. 7. Every product company is turning into a product studio. I see it firsthand as a co-founder of @meetLCA , which is basically a Labs as a Service company incubating new products for companies. (DM me if you want to work together in 2027). 8. Personal software is exploding. People at every company are building their own little tools for their own jobs. It's amazing for productivity and a nightmare for IT, because nobody knows what's running or who owns it. 9. Revenue per human is the new flex. Founders used to brag about headcount. Now they brag about how much they're doing with how few people. 11. More founders are using agents for customer research. Agents run the interviews, read every support ticket and summarize what people are begging for. Synthetic market research is the new thing. 12. Shipping technology that actually takes 3-6 months with unique partnerships that are hard to replicate. So, partnerships are sooo back! 13. Insane amount of young people (22 or younger) making absurds amounts of money. At least it feels that way. Never seen anything like that, even during mobile era. 14. Only 2% of the US is paying for AI products, but it feels like 110% SF is. 15. Advice for college grads used to be “follow your passion” and now it’s follow careers that are not document- driven, rules-bound and verifiable 16. Seeing the word inference on billboards in SF still blows my mind. 17. Agents paying for things feels futuristic. I think its coming, only a matter of time, but I’m wondering when it becomes mainstream. 2027? 18. Lots of talk about proactive agents being the next phase of personal agents. Right now you ask your agent to do something. In 2027, it’s all going to be about noticing things (context/memory) and acting first. "Your flight got delayed, I already rebooked you." 19. The quote "what the smartest people do on the weekend is what everyone else will do during the week in 10 years." by Chris Dixon. It feels like that length of time isnt 10 years anymore, its 12 months. 20. This is the most asymmetric window I've ever seen in business. My DMs are open. Respond to the most interesting ones. Loved my trip to SF. Until next time. Maybe NYC next? Thank you for everything. I'm rooting for you.

@mtsliveOct 14

Tempo CBO @dwr predicts AI agents will soon have their own financial accounts, allowing them to negotiate bills, collect refunds, and manage money on your behalf: "In terms of the actual numbers of agentic transactions, those are still small. That’s across the board, not just stablecoins." "In the last 6 to 8 weeks, we’ve seen a lot of excitement around personal agents. Instinct, Meta’s Muse product, ChatGPT just released Dots. 6 months from now, virtually every consumer platform with some level of scale in AI is going to have some type of personal agent product, and those personal agents are going to be doing transactions for people." "There is a real opportunity for agents with wallets, because agents are not creatures of habit like humans, so they’re able to simultaneously use both cards and stablecoins." "There’s a lot of focus on how can I spend money, but there’s a version of the world where, how can I actually receive money? Receiving a refund, or negotiating your bill down and those funds coming back to a stablecoin wallet that your agent is managing. A lot of these personal agents with wallets are gonna start to resemble proto-financial accounts." @tempo

@awilkinsonOct 14

I love how people keep dunking on OpenAI Dots saying agents like Instinct or Muse are vastly superior. Software product differentiation used to be a sustainable competitive advantage. If you didn't have the right designers + engineering talent, you couldn't keep up. Those days are over. OpenAI can literally just tell their (now vastly superior private model which nobody else has access to) "go and figure out what everyone loves about Instinct and then copy it + evolve its features + add things only we can do". In a few weeks, they can leapfrog the competition. Add an always-on hardware device designed by Joni Ive (that is fully baked, unlike Mark Zuckeberg's rushed Muse keychain device), plus the most cutting edge models, plus all of your knowledge graph/data and that is a pretty profound moat.

@alliekmillerOct 13

After much testing and talking to actual users across all three proactive AI agents: Muse - best one for your parents, heavy IG/FB users, people who like or need easy setups, people who don’t want to build anything, best use case idea generator by a mile (aka great if you don’t know what you want to use it for but you have to click the idea tab!), best for people who still say “wtf can AI do for me” Dots - best for OpenAI users, people who might need to build/code, people who deal with slack a lot, people who love voice features Instinct - people who live in their iMessage/don’t want to open another app, people who don’t need crazy fancy visualizations, people who want internet watchdogs (like “next time AJ Jacobs writes an article, send it to me”), easiest setup (tied with Muse) I am a very heavy Instinct user and light Muse/Dots user, largely because it's in iMessage. Muse also made several basic mistakes when I was chatting with it and forgot things after awhile. Didn’t feel like a state of the art model, despite somewhat equal benchmarks to Astra on GDPval-AA, but that might change with today's new model news, so I'm excited to test. And my honest take: still feels just very early across the space. We're going to see more. Note: answers subject to change, literally day by day.

@rrhooverOct 13

Every AI cold email: Hi, Ryan! I saw your podcast interview from 2016—you talked about your morning routine at Philz Coffee and investments in Deel, Mindbloom, and Passport. Well, we're building Instinct for cats.

@aakashguptaOct 13

Americans lose about 2.5 days a year looking for stuff they just had. Keys, wallet, remote, the other AirPod. Your phone has an AI in it now and it’s useless for this, because the question is “where did I leave this” and the phone has never once seen “this.” That one word is the whole pitch behind NewEyes AI, and I think they’re right about it. Agents got very good this year at working inside your accounts. Email, calendar, cards, carts. Give one a job that lives on a screen and it’ll finish it. Hold up two nearly identical jars and ask “is this the right one?” and it has nothing to go on. Linguists have a name for words like this, that, here: deictic. They carry no meaning on their own. All of it comes from what the speaker is looking at, which is the one thing a chat box can’t see. Babies figure this out early. Pointing shows up around nine to twelve months. Two-word sentences take another year. We learned to point before we learned to talk. Once you see “this” as the problem, the hardware makes sense. Glasses with a camera, open-ear earphones, one agent running both. Nothing in your hand, nothing on a screen. The camera fills in “this,” the earphone answers while your hands stay busy, and it remembers where you left off. Their example is a book: “Good morning. Continue on page 212.” The bit I’d read twice is the trust part. Eyes raise the stakes, so they started there. You set the boundary, the runtime enforces it, credentials stay outside the model context. A camera on your face all day only works if the limits sit below the model, where a clever prompt can’t talk its way around them. Agents learned to talk first. A personal agent with eyes is them finally learning to point.

@david__boothOct 13

some things I believe: - personal agents will become the front door to professional life. 500m+ people will have a Muse, Instinct, GrokBot, and/or whatever comes next <2 years from now - because they’ll have so much context & autonomy .. the “cold start problem” for new social networks is substantially diminished. Your agent will build your profile for you, build your connection graph, take the prescribed activation “actions” on your behalf. - what a time to be alive!!

@omarsar0Oct 13

Richer context is what makes personal agents personal. Today, they see your email, calendar, and accounts, and miss everything happening in front of you. NewEyes AI from @CollovLabs is built as a personal agent with eyes. Camera glasses see what you see, and open-ear earphones answer in your ear. The more of your day an agent can see, the more it can tailor its help to you.

@notionhqOct 12

We’ve seen you use Notion alongside Grok Bot, Claude, Instinct, Muse, and more. Here are 7 setups worth stealing 🧵

@kiwicoppleOct 9

i have growing conviction in Personal Agents. I also think they are going to be incredibly sticky the one I'm using has started to learn my work rules/patterns & it has built up a CRM of all my contacts it won't be so easy to shift these from one tool to another unless the industry standardizes on a way to manage handle each of these (which i doubt will happen) i'm also surprised at how useful it has been to "call" the agent while I'm working from my computer. It's like pair-coding (for work tasks), we are both working at the same time on a kanban board to clean up a backlog of tasks