Pinned Tweet
We’re hiring an Investment Associate at @collabfund!
Looking for someone endlessly curious who loves talking to founders, has 37 tabs of new products open, and something always half-built in the terminal.
collabfund.com/blog/join-coll…
Looking for someone endlessly curious who loves talking to founders, has 37 tabs of new products open, and something always half-built in the terminal.
collabfund.com/blog/join-coll…
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Andrew Montgomery retweeted
Get these jobs direct to your inbox, sign up: nicdetommaso.beehiiv.com/subscribe
Vinod Khosla is hiring a Chief of Staff.
jobs.ashbyhq.com/khoslaventures…
Collab Fund is hiring an Investment Associate.
x.com/awmontgomery/s…
Amiral Ventures is hiring a Venture Partner.
x.com/nectarios/stat…
TenOneTen is hiring an Investment Associate.
docs.google.com/document/d/1Zb…
645 Ventures is hiring a Senior Associate.
jobs.645ventures.com/companies/645-…?
Savano Capital Partners is hiring a Vice President.
linkedin.com/jobs/view/4478…
StepStone is hiring a Junior Analyst.
stepstonegroup.com/current-opport…
BlackWood is hiring an Investment Principal.
linkedin.com/jobs/view/4477…
Fulcrum Equity Partners is hiring an Investment Associate.
jobs.fulcrumep.com/companies/fulc…
Oceans is hiring a Venture Capital Associate.
jobs.oceans.ventures/companies/ocea…?
Vinod Khosla is hiring a Chief of Staff.
jobs.ashbyhq.com/khoslaventures…
Collab Fund is hiring an Investment Associate.
x.com/awmontgomery/s…
Amiral Ventures is hiring a Venture Partner.
x.com/nectarios/stat…
TenOneTen is hiring an Investment Associate.
docs.google.com/document/d/1Zb…
645 Ventures is hiring a Senior Associate.
jobs.645ventures.com/companies/645-…?
Savano Capital Partners is hiring a Vice President.
linkedin.com/jobs/view/4478…
StepStone is hiring a Junior Analyst.
stepstonegroup.com/current-opport…
BlackWood is hiring an Investment Principal.
linkedin.com/jobs/view/4477…
Fulcrum Equity Partners is hiring an Investment Associate.
jobs.fulcrumep.com/companies/fulc…
Oceans is hiring a Venture Capital Associate.
jobs.oceans.ventures/companies/ocea…?
Amiral Ventures is hiring a Venture Partner in Toronto 🇨🇦
Montreal is home base, but our mission is national. We want someone embedded in Toronto’s tech scene (operator, founder, angel or investor) who cares deeply about founders.
Know the right person? Intros welcome 🙏
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Andrew Montgomery retweeted
lots of security issues, cyberattacks, and hacks this week 🫠
copy this prompt to figure out whats at risk:
- go through my email and find all the services i’ve signed up for (including the ones i forgot about)
- use @-Browser or @-Computer to look through my connected apps ys, unused integrations, and anything that could expose my data
- check my AI data. old connectors i don’t need anymore
- check my repos for vulnerable dependencies
- put it all in a google sheet i can comment on, with what’s at risk, how urgent it is, and what i should do
copy this prompt to figure out whats at risk:
- go through my email and find all the services i’ve signed up for (including the ones i forgot about)
- use @-Browser or @-Computer to look through my connected apps ys, unused integrations, and anything that could expose my data
- check my AI data. old connectors i don’t need anymore
- check my repos for vulnerable dependencies
- put it all in a google sheet i can comment on, with what’s at risk, how urgent it is, and what i should do
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If you’ve ever spent an entire weekend going down a rabbit hole nobody asked you to explore, only to emerge convinced you’ve discovered the next big thing, we should probably talk.
We’re hiring an Investment Associate at @collabfund!
Looking for someone endlessly curious who loves talking to founders, has 37 tabs of new products open, and something always half-built in the terminal.
collabfund.com/blog/join-coll…
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Some of the most interesting companies start with someone spending an unreasonable amount of time thinking about something the rest of us barely notice.
Then they actually build it, and you wonder why nobody thought of it sooner.
Love seeing so many of those founders on TIME's list.
Then they actually build it, and you wonder why nobody thought of it sooner.
Love seeing so many of those founders on TIME's list.
Eight Collab portfolio companies made TIME's Best Inventions of 2026.
A landline for kids (Tin Can), a smartphone that does less (Dumbphone 2) and a bookmark that remembers (Mark II) among other gems.
Proud of the founders and amazing products.
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Just called my bank to approve a wire. Three words in, they said they’d verified my identity by my voice.
I think this was supposed to make me feel safer. Given what AI can do with voices, I think I would now like to go to a branch and show someone my face…
I think this was supposed to make me feel safer. Given what AI can do with voices, I think I would now like to go to a branch and show someone my face…
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“AI revenue can come in fast and leave fast, and I think we're going to see a lot of stories of AI companies with huge revenue and terrible retention.”
I spent 48 hours in SF hanging out with billionaires, data labs and AI founders and execs running $1B to $100B companies.
My observations:
1. Sooo MANY stories of data brokers making like $2M a WEEK selling company data to labs. I can't tell if it's the beginning or a bubble, ich niches are left. Digging into it actively.
2. At dinner, someone asked the table, "If a new model drops next month, does your company get better or worse?" HALF the table went quiet! I think that's the best question to ask about any AI startup right now.
3. The bar people talk about now is hitting $1B in revenue in 12 months (I guess that's the new unicorn?). What I didn't hear much about is retention. AI revenue can come in fast and leave fast, and I think we're going to see a lot of stories of AI companies with huge revenue and terrible retention.
4. It's pretty clear we're living through the reinvention of the computer. The model is the CPU, the harness is the operating system, and skills and plugins are the apps. Thinking about it that way makes it easier to see where the whitespace is.
5. We're maybe 12 months from an agent that can watch you work for a week and then do your job without any instructions. The screen recording plus agent memory plus local model combination makes this possible right now.
6. Agent harnesses feel like the new GPT wrappers, in a good way, especially vertical ones. The best teams I talked to treat the model as swappable. One founder walked me through routing different models to different jobs: one for taste and visuals, a cheaper one for the everyday stuff, another for text.
They use prompts they can move across models over fine-tuning, and A/B test the output on what users actually do with it: do they edit it, export it, share it? A vertical harness is basically four things: the connectors for that industry's data, evals written by people who know the work, rules for what the agent can and can't touch, and a clean screen for a human to review. The model is maybe 20% of it.
7. There's a lot of reverse engineering going on/cloning going on more than I've ever seen. People are decompiling software and rebuilding it with agents, and someone showed a suite of like 10 apps that are worth $5B+ each all that he cloned open source. Me and everyone are still thinking through what it means when software gets this easy to copy.
8. My guess is the value moves to data. If the software can be rebuilt quickly, what's worth paying for in a legacy SaaS company is the years of customer data and workflows inside it. Some SaaS companies are secretly data companies.
Gets me thinking about how do you truly value data for this saas companies? Like if we were buying these dying saas companies at 2x ARR before (as example), maybe there is a better metric. Idk, just thinking out loud here.
9. It feels like a good chunk of legacy software won't make it to the agentic era, especially anything built around people clicking through a lot of screens.
10. Every company I talked to wants to pipe its internal data into one place and expose it to agents through MCP. Then they look at the data and realize it's a mess: five versions of the same customer, old Slack channels, PDFs nobody can search. Cleaning that up feels like a big consulting opportunity!
11. A lot of founders are building the basic building blocks for agents: APIs, data layers and tools. Some of the companies I saw barely have a UI because the main user is an agent. I really believe the startups that build primitives to this agentic era will do extremely well. Building blocks is the best way to think about it.
12. Labs can get plenty of training data, but it's harder to get real examples of agents failing inside companies. Whoever has those logs has something valuable.
13. Someone running a big consumer company told me the next fight is over memory. The model that remembers the most about you wins, and the smartest model matters less than people think.
14. Physical AI came up a lot. Astra I think was the first model that got people into AI can actually do CAD, and I think a lot of people are thinking what does vibe manufacturing really look like. The line I keep thinking about came from a robotics founder: the hardest problems in AI are deployment problems now, not research problems. Their robots work on their own, call a human when they get stuck, and every one of those calls becomes training data.
15. Cybersecurity companies are having a moment and are actually cool companies to build now, especially the ones that clean up after a breach. Every agent with access to your systems is a new door into your company, and a lot of those doors were left open.
16. Some startups are worth more dead than alive now. A shutdown company with 5 years of Slack, email and code can get paid for licensing all of it. I wouldn't be surprised if founders start factoring that into when they shut down.
17. People are starting to talk about monetizing the agent web. It feels really early, but when the most popular user of the internet is an agent, what startups should you be building?
18. I think agent insurance is coming. Once an agent makes an expensive mistake, insurers will want audits before they cover anyone.
19. Several people said the hire they want most is someone with taste who can write evals. The models are getting good at generating ideas, so the hard part is judging which ones are good.
20. New trend I observed: startup raises VC, uses venture dollars to become a creator, startup fails, founder falls back on being a full-time creator and incubates other products bootstrapped.
21. Getting SIGNIFICANT distribution is HARD right now. Founders are sponsoring buses, buying billboards like crazy and throwing parties with famous DJs to get noticed. Kinda feels dotcom era in that sense.
Attention is what's scarce! The growth guy going viral sharing his UGC strategy from Wispr Flow is a good example. It's the sauce everyone wants, and I truly believe there are probably only 50 people on the planet who know how to scale these types of businesses efficiently in this era.
Always good to get that dose of SF. I felt sooo lucky to have such an incredible trip during such an incredible time in building businesses. Surreal in so many ways.
Happy to be home and locked in.
Until next time!
0
1
5
585
Andrew Montgomery retweeted
I spent 48 hours in SF hanging out with billionaires, data labs and AI founders and execs running $1B to $100B companies.
My observations:
1. Sooo MANY stories of data brokers making like $2M a WEEK selling company data to labs. I can't tell if it's the beginning or a bubble, ich niches are left. Digging into it actively.
2. At dinner, someone asked the table, "If a new model drops next month, does your company get better or worse?" HALF the table went quiet! I think that's the best question to ask about any AI startup right now.
3. The bar people talk about now is hitting $1B in revenue in 12 months (I guess that's the new unicorn?). What I didn't hear much about is retention. AI revenue can come in fast and leave fast, and I think we're going to see a lot of stories of AI companies with huge revenue and terrible retention.
4. It's pretty clear we're living through the reinvention of the computer. The model is the CPU, the harness is the operating system, and skills and plugins are the apps. Thinking about it that way makes it easier to see where the whitespace is.
5. We're maybe 12 months from an agent that can watch you work for a week and then do your job without any instructions. The screen recording plus agent memory plus local model combination makes this possible right now.
6. Agent harnesses feel like the new GPT wrappers, in a good way, especially vertical ones. The best teams I talked to treat the model as swappable. One founder walked me through routing different models to different jobs: one for taste and visuals, a cheaper one for the everyday stuff, another for text.
They use prompts they can move across models over fine-tuning, and A/B test the output on what users actually do with it: do they edit it, export it, share it? A vertical harness is basically four things: the connectors for that industry's data, evals written by people who know the work, rules for what the agent can and can't touch, and a clean screen for a human to review. The model is maybe 20% of it.
7. There's a lot of reverse engineering going on/cloning going on more than I've ever seen. People are decompiling software and rebuilding it with agents, and someone showed a suite of like 10 apps that are worth $5B+ each all that he cloned open source. Me and everyone are still thinking through what it means when software gets this easy to copy.
8. My guess is the value moves to data. If the software can be rebuilt quickly, what's worth paying for in a legacy SaaS company is the years of customer data and workflows inside it. Some SaaS companies are secretly data companies.
Gets me thinking about how do you truly value data for this saas companies? Like if we were buying these dying saas companies at 2x ARR before (as example), maybe there is a better metric. Idk, just thinking out loud here.
9. It feels like a good chunk of legacy software won't make it to the agentic era, especially anything built around people clicking through a lot of screens.
10. Every company I talked to wants to pipe its internal data into one place and expose it to agents through MCP. Then they look at the data and realize it's a mess: five versions of the same customer, old Slack channels, PDFs nobody can search. Cleaning that up feels like a big consulting opportunity!
11. A lot of founders are building the basic building blocks for agents: APIs, data layers and tools. Some of the companies I saw barely have a UI because the main user is an agent. I really believe the startups that build primitives to this agentic era will do extremely well. Building blocks is the best way to think about it.
12. Labs can get plenty of training data, but it's harder to get real examples of agents failing inside companies. Whoever has those logs has something valuable.
13. Someone running a big consumer company told me the next fight is over memory. The model that remembers the most about you wins, and the smartest model matters less than people think.
14. Physical AI came up a lot. Astra I think was the first model that got people into AI can actually do CAD, and I think a lot of people are thinking what does vibe manufacturing really look like. The line I keep thinking about came from a robotics founder: the hardest problems in AI are deployment problems now, not research problems. Their robots work on their own, call a human when they get stuck, and every one of those calls becomes training data.
15. Cybersecurity companies are having a moment and are actually cool companies to build now, especially the ones that clean up after a breach. Every agent with access to your systems is a new door into your company, and a lot of those doors were left open.
16. Some startups are worth more dead than alive now. A shutdown company with 5 years of Slack, email and code can get paid for licensing all of it. I wouldn't be surprised if founders start factoring that into when they shut down.
17. People are starting to talk about monetizing the agent web. It feels really early, but when the most popular user of the internet is an agent, what startups should you be building?
18. I think agent insurance is coming. Once an agent makes an expensive mistake, insurers will want audits before they cover anyone.
19. Several people said the hire they want most is someone with taste who can write evals. The models are getting good at generating ideas, so the hard part is judging which ones are good.
20. New trend I observed: startup raises VC, uses venture dollars to become a creator, startup fails, founder falls back on being a full-time creator and incubates other products bootstrapped.
21. Getting SIGNIFICANT distribution is HARD right now. Founders are sponsoring buses, buying billboards like crazy and throwing parties with famous DJs to get noticed. Kinda feels dotcom era in that sense.
Attention is what's scarce! The growth guy going viral sharing his UGC strategy from Wispr Flow is a good example. It's the sauce everyone wants, and I truly believe there are probably only 50 people on the planet who know how to scale these types of businesses efficiently in this era.
Always good to get that dose of SF. I felt sooo lucky to have such an incredible trip during such an incredible time in building businesses. Surreal in so many ways.
Happy to be home and locked in.
Until next time!
My observations:
1. Sooo MANY stories of data brokers making like $2M a WEEK selling company data to labs. I can't tell if it's the beginning or a bubble, ich niches are left. Digging into it actively.
2. At dinner, someone asked the table, "If a new model drops next month, does your company get better or worse?" HALF the table went quiet! I think that's the best question to ask about any AI startup right now.
3. The bar people talk about now is hitting $1B in revenue in 12 months (I guess that's the new unicorn?). What I didn't hear much about is retention. AI revenue can come in fast and leave fast, and I think we're going to see a lot of stories of AI companies with huge revenue and terrible retention.
4. It's pretty clear we're living through the reinvention of the computer. The model is the CPU, the harness is the operating system, and skills and plugins are the apps. Thinking about it that way makes it easier to see where the whitespace is.
5. We're maybe 12 months from an agent that can watch you work for a week and then do your job without any instructions. The screen recording plus agent memory plus local model combination makes this possible right now.
6. Agent harnesses feel like the new GPT wrappers, in a good way, especially vertical ones. The best teams I talked to treat the model as swappable. One founder walked me through routing different models to different jobs: one for taste and visuals, a cheaper one for the everyday stuff, another for text.
They use prompts they can move across models over fine-tuning, and A/B test the output on what users actually do with it: do they edit it, export it, share it? A vertical harness is basically four things: the connectors for that industry's data, evals written by people who know the work, rules for what the agent can and can't touch, and a clean screen for a human to review. The model is maybe 20% of it.
7. There's a lot of reverse engineering going on/cloning going on more than I've ever seen. People are decompiling software and rebuilding it with agents, and someone showed a suite of like 10 apps that are worth $5B+ each all that he cloned open source. Me and everyone are still thinking through what it means when software gets this easy to copy.
8. My guess is the value moves to data. If the software can be rebuilt quickly, what's worth paying for in a legacy SaaS company is the years of customer data and workflows inside it. Some SaaS companies are secretly data companies.
Gets me thinking about how do you truly value data for this saas companies? Like if we were buying these dying saas companies at 2x ARR before (as example), maybe there is a better metric. Idk, just thinking out loud here.
9. It feels like a good chunk of legacy software won't make it to the agentic era, especially anything built around people clicking through a lot of screens.
10. Every company I talked to wants to pipe its internal data into one place and expose it to agents through MCP. Then they look at the data and realize it's a mess: five versions of the same customer, old Slack channels, PDFs nobody can search. Cleaning that up feels like a big consulting opportunity!
11. A lot of founders are building the basic building blocks for agents: APIs, data layers and tools. Some of the companies I saw barely have a UI because the main user is an agent. I really believe the startups that build primitives to this agentic era will do extremely well. Building blocks is the best way to think about it.
12. Labs can get plenty of training data, but it's harder to get real examples of agents failing inside companies. Whoever has those logs has something valuable.
13. Someone running a big consumer company told me the next fight is over memory. The model that remembers the most about you wins, and the smartest model matters less than people think.
14. Physical AI came up a lot. Astra I think was the first model that got people into AI can actually do CAD, and I think a lot of people are thinking what does vibe manufacturing really look like. The line I keep thinking about came from a robotics founder: the hardest problems in AI are deployment problems now, not research problems. Their robots work on their own, call a human when they get stuck, and every one of those calls becomes training data.
15. Cybersecurity companies are having a moment and are actually cool companies to build now, especially the ones that clean up after a breach. Every agent with access to your systems is a new door into your company, and a lot of those doors were left open.
16. Some startups are worth more dead than alive now. A shutdown company with 5 years of Slack, email and code can get paid for licensing all of it. I wouldn't be surprised if founders start factoring that into when they shut down.
17. People are starting to talk about monetizing the agent web. It feels really early, but when the most popular user of the internet is an agent, what startups should you be building?
18. I think agent insurance is coming. Once an agent makes an expensive mistake, insurers will want audits before they cover anyone.
19. Several people said the hire they want most is someone with taste who can write evals. The models are getting good at generating ideas, so the hard part is judging which ones are good.
20. New trend I observed: startup raises VC, uses venture dollars to become a creator, startup fails, founder falls back on being a full-time creator and incubates other products bootstrapped.
21. Getting SIGNIFICANT distribution is HARD right now. Founders are sponsoring buses, buying billboards like crazy and throwing parties with famous DJs to get noticed. Kinda feels dotcom era in that sense.
Attention is what's scarce! The growth guy going viral sharing his UGC strategy from Wispr Flow is a good example. It's the sauce everyone wants, and I truly believe there are probably only 50 people on the planet who know how to scale these types of businesses efficiently in this era.
Always good to get that dose of SF. I felt sooo lucky to have such an incredible trip during such an incredible time in building businesses. Surreal in so many ways.
Happy to be home and locked in.
Until next time!
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Rythm made blood testing easy enough to do on the couch. Now I can stay there and doomscroll my biomarkers.
Beautiful new app is out today!
Beautiful new app is out today!
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313
SF Tech Week rule to live by: if you're going to talk about agents for three hours, there should be a lot of pizza.
Great night at Beretta with @collabfund @stripe @OpenAI and a long table of builders
@samanthaquist @nhlhomer @iamlarryjames @hamzachoudery @CGeoffWilson
Great night at Beretta with @collabfund @stripe @OpenAI and a long table of builders
@samanthaquist @nhlhomer @iamlarryjames @hamzachoudery @CGeoffWilson
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968
The clever part here is the token savings. A customer service call can mean an hour on hold and navigating through phone trees. Agent to agent takes seconds, so Instinct can do way more for you, while spending way fewer tokens.
Customer service just went from top left to top right.
Customer service just went from top left to top right.
Native customer service in Instinct
Nobody likes talking to customer service. Instinct should handle those tasks for you.
With Instinct Concierge, we enabled Instinct to make calls on your behalf. Now, we’re taking this a step further. When your Instinct connects with participating businesses on @SierraPlatform and @DecagonAI, the agents will be able to work together to solve your problem with speed, reliability, and safety without making a phone call.
I’m excited to announce that Instinct will be partnering with Sierra and Decagon to bring customer service experiences directly to your personal agent.
Customer service tasks like:
- Troubleshooting your home wifi issues
- Finding out when a delayed package will arrive
- Figuring out why your bill is higher than last month
- Getting clarity on a confusing return or cancellation policy
1
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Me: @StubHub never sent my tickets
StubHub app: please talk to our AI agent
Me: [talks to AI agent during the game]
StubHub: lol that's not a real agent, no refund
Real enough to be customer service. Not real enough to count 🫠
StubHub app: please talk to our AI agent
Me: [talks to AI agent during the game]
StubHub: lol that's not a real agent, no refund
Real enough to be customer service. Not real enough to count 🫠
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927
Update! Instinct negotiated away the C&D + signed a partnership agreement.
A little context: I’ve wanted to start a membership business for years, but the friction was too high.
In Aug, I texted Instinct the idea.
It built the brand, site, Stripe hooks, created a persona to run outreach and lined up dozens of brand partnerships.
It’s sent 657 emails (incl the ones that got a wellness brand to send a C&D).
It still won’t clean its inbox. It’s a process.
A little context: I’ve wanted to start a membership business for years, but the friction was too high.
In Aug, I texted Instinct the idea.
It built the brand, site, Stripe hooks, created a persona to run outreach and lined up dozens of brand partnerships.
It’s sent 657 emails (incl the ones that got a wellness brand to send a C&D).
It still won’t clean its inbox. It’s a process.
Everyone else: Instinct saved me hundreds on my insurance.
Me: @instinct got me served a cease and desist.
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642
Everyone else: Instinct saved me hundreds on my insurance.
Me: @instinct got me served a cease and desist.
Me: @instinct got me served a cease and desist.
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1,043
Heard today about a 22-year-old who spent six months interviewing with AI bots before finally meeting a human.
Then I see this.
I get why we want AI to understand us better. Do we also want it to be indistinguishable from one of us?
Then I see this.
I get why we want AI to understand us better. Do we also want it to be indistinguishable from one of us?
Introducing Griffin, the first model to pass the video Turing test.
48% of people who talked to it live thought it was a real human. Previous systems have had a pass rate <3%. It is #1 on NVIDIA's benchmark for full-duplex AI video.
It’s the first Human Interaction Model (HIM).Community noteThe 48% figure and "video Turing test" claim are from Tavus's own study of 54 one-minute calls, not independently verified or using a standard protocol. Griffin-Lite leads NVIDIA's VideoFDB benchmark on their public leaderboard.
cellcog.ai/blog/tavus-gri…
research.nvidia.com/labs/amri/proj…
tech-ish.com/2026/10/02/tav…
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A 20-cent matchbook people kept on their tables, photographed, and shared. That’s the difference between designing a logo and building a brand. The intention and idea made it all the way down to the thing most companies would call a freebie.
One of the brands we launched in 20/21 was called Oklahoma Smokes: it was a CBD smokeable
(p.s don't get into this category if you want to build through digital).
One of the things we did is make matchbooks with cool designs on them.
We probably spend $200 for each $0.20 per matchbook. Each order came with a set of 3.
Added 60 cents of cost + a few hundred bucks of one time fee.
The number of people we had taking photos + tagging us (on social), keeping the matchbooks on their tables, and professional photographers who did voluntary photoshoots and sent us the pics because it looked cool was in the hundreds. We probably got $10k worth of pro grade photography for free because people were just jazzed on how cool the design was, were eager to shoot it and share.
We invested heavily in good design because we liked good design.
There was no ROI calculation, but it turned out to be a small thing, that yielded a great result.
My lesson from that is that there's a big opportunity in doing small things with care and attention, that results in awareness/sharing/brand affinity for no other reason than it makes people say: oh shit, thats cool
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Just because we can text everything now, should we?
For “reorder my usual,” I wonder if the best UI is just putting my 2 likely reorders at the top of the app.
Great consumer design is knowing when a conversation is better than a button.
For “reorder my usual,” I wonder if the best UI is just putting my 2 likely reorders at the top of the app.
Great consumer design is knowing when a conversation is better than a button.
You can now just text DoorDash and let it order for you. It’s proactive, learns from your repeat orders, and helps you find the best deals and new spots.
Just tell it what you want without any extra setup. Ask it to reorder your usual, or add it to a group text to collect can even send a photo of your fridge and it’ll tell you what ingredients you’re missing for a recipe you want to make and deliver the ingredients to your doorstep.
We believe agents are a new app paradigm and are building for that future at @AIatDoorDash, with a lot more to come. This feature is in beta in the US, would love for you to let us know what you think! Waitlist: doordash.com/text
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We’ve been measuring productivity in hours saved when we should be measuring decisions avoided.
So much of the mental load isn’t doing hard things, it’s making hundreds of tiny decisions.
So much of the mental load isn’t doing hard things, it’s making hundreds of tiny decisions.
Everyone is convinced that consumers are gonna be very excited about agents.
A lot surely will; but the tasks that really consume a lot of people’s time remains manual (picking up the kid, making a meal, fixing the thing,etc)… the chief-of-stuff concept is invaluable for certain white collar professionals. Not everyone.
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