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Andrew Curran
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Antoine Osika
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Dario Amadei
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Gary Lerhop
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Jayesh Govindarajan
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Kanjun Shui
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Kashik Tiwari
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Mark Benioff
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Mauro Shlomo
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Mike Krieger
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Jayesh Govindarajan: 作为Salesforce的EVP,我认为AgentForce 3.0旨在解决企业在部署AI代理后遇到的实际运营挑战。我们通过提供实时监控功能,使企业能够观察多个代理如何影响任务完成的效率。此外,我们还支持MCP和A2A互操作性标准,这对于确保不同系统之间的无缝协作至关重要。我相信这些功能对于企业来说是必不可少的,能够帮助他们更好地利用AI技术。 Gary Lerhop: 作为产品架构副总裁,我认为Salesforce的企业级互操作性是专门为企业用例设计的。与通用的互操作性不同,我们提供了一层治理和控制工具,以确保企业客户可以信任外部工具的访问。这种额外的安全性和控制对于企业来说至关重要,因为他们需要确保数据的安全性和合规性。我们与Stripe、Google Cloud和AWS等公司合作,提供超过20个经过验证的MCP服务器,以满足企业的多样化需求。 Mark Benioff: 作为Salesforce的CEO,我对Copilot传递给客户的方式感到失望。我认为它无法提供准确性,并且存在数据泄露的问题。客户被迫自己构建定制的LLM,这增加了他们的负担。我认为Copilot更像是Clippy 2.0,而不是一个真正的AI助手。我相信企业需要更好的AI解决方案,这就是为什么我们致力于开发AgentForce 3.0,以满足企业的实际需求。

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Salesforce's AgentForce 3.0 update includes a new command center for real-time visibility into agent performance, native support for MCP and A2A interoperability standards, and addresses operational challenges after initial deployment. The update comes as agent usage is up 233% over six months, highlighting the growing importance of enterprise agents and setting the tone for what major enterprises expect.
  • AgentForce 3.0 released by Salesforce
  • Includes command center for real-time visibility
  • Native support for MCP and A2A standards
  • Addresses 'day two problems'
  • Agent usage up 233% in six months

Shownotes Transcript

Translations:
中文

Today on the AI Daily Brief, the quest for the one-person, $1 billion company. Before that in the headlines, MCP and observability come to Agent Force 3.0. The AI Daily Brief is a daily podcast and video about the most important news and discussions in AI.

All right, friends, welcome back to the AI Daily Brief. Love Ideogram, but I have found the limits of their ability to put text on images. Still love this cover and so decided to use it anyways. In any case, announcements for today. First of all, thank you to today's sponsors, as always, Super Intelligent, Blitzy, Vanta, and KPMG.

However, if you are one of those folks who does not want ads to besmirch your listening experience, go to patreon.com slash AI Daily Brief. For just $3 a month, you can get an ad-free version of the show. I actually don't have any other announcements today, so without any further ado, let's talk about why AgentForce 3.0 matters for more than just Salesforce customers. Welcome back to the AI Daily Brief Headlines Edition, all the daily AI news you need in around five minutes. We

We kick off today with the latest from Salesforce, where that company has released a sweeping revision of their AI platform in an update that they are calling AgentForce 3.0. The upgrade includes a new command center feature that gives executives real-time visibility into agent performance. So in other words, an observability suite. It also adds native support for the MCP and A2A interoperability standards.

Remember, MCP is a protocol for giving agents access to different data sources. Each MCP server is connected to a different data source. So basically rather than agents having to design their own connection points to whatever data they need, they can just plug into an MCP server that exists and is already standard for that data source, making things a lot faster. A2A is exactly what it sounds like, an agent to agent messaging standard that can also make these systems work more cleanly. Now the update comes as Salesforce starts to hit scale with this product.

According to their internal data, agent usage is up 233% over six months, with more than 8,000 customers now signed up for the service. Says EVP Jayesh Govindarajan, Now, to some extent, these features feel like table stakes.

Overall, the system is designed to address what Govindarajan calls day two problems, or operational challenges that emerge after the initial deployment. Discussing observability, he says, you can have multiple agents from multiple personas, and you need to have the ability to observe how that's actually impacting the task that needs to get done at scale. Interoperability is another one of those no-brainer features, but still relevant coming from this source. Gary Lerhop, the VP of product architecture, is basically saying that their interoperability is purpose-built for the enterprise use case.

He said there's generic interoperability, and then there's what we call enterprise-grade interoperability. He said that the difference is a layer of governance and control tools that help enterprise customers trust external tool access. With the 3.0 launch, Salesforce is including over 20 vetted MCP servers, including Stripe, Google Cloud, AWS, and Box.

Now, why it is worth paying attention to what big companies like Salesforce or Microsoft or Google are doing when it comes to enterprise agents is that these are the big companies who are setting the tone for what major enterprises expect. Salesforce in particular has been very early and aggressive to the agent transition. You might remember back in October, Salesforce CEO Mark Benioff really started to take co-pilot to task.

For example, this tweet, when you look at how Copilot has been delivered to customers, it's disappointing. It just doesn't work and it doesn't deliver any level of accuracy. Gardner says it's spilling data everywhere and customers are left cleaning up the mess. To add insult to injury, customers are then told to build their own custom LLMs. I've yet to find anyone who's had a transformational experience with Microsoft Copilot or the pursuit of training and retraining custom LLMs. Copilot is more like Clippy 2.0.

Now, of course, that had more than a little bit of marketing, but the market has basically proven Benioff's moves correct. The entire enterprise space has shifted to focus on agents. And so I think that when you look at the feature set that's coming to AgentForce, it almost reads like a map of what you can expect across enterprise agent platforms in general.

Next up, more details about Zuck's attempted spending spree, where apparently Runway was another acquisition target. At this stage, it seems like every single AI company has fielded offers from Mark Zuckerberg over the past month as he's been assembling his superintelligence team. The latest reporting comes from Bloomberg, who stated that video generation startup Runway was on Zuck's shortlist.

Sources say that meetings took place, but a formal offer with a number attached was never made. Now, as speculation around what the idea here was, Runway on the one hand seems like perhaps a strange target as they don't work on core foundation models.

But then again, sniffing around for a video model company could indicate that Zuckerberg is looking to improve Meta's multimodal AI or even take a world model-based path to AGI. It could also simply mean that Zuck was in talks with every single AI unicorn last month. And indeed, reporting from the Wall Street Journal makes it sound like that's exactly what happened. They write, Mark Zuckerberg is spending his days firing off emails and WhatsApp messages to the sharpest minds in artificial intelligence in a frenzied effort to play catch-up.

He has personally reached out to hundreds of researchers, scientists, infrastructure engineers, product stars, and entrepreneurs to try to get them to join a new superintelligence lab he's putting together. Some of the people who received the messages were so surprised they didn't believe it was really Zuckerberg. One person assumed it was a hoax and didn't respond for several days.

Andrew Curran suggested that AI researchers should be checking their WhatsApp and emails regularly lest they miss out on Zuckerberg buying them a mansion. He posted, If you get an email from Mark Zuckerberg, do not assume that it is fake. He's taken over recruitment for the superintelligence lab and is reaching out to hundreds of prospects personally. If you respond, the next step is an invitation to dinner.

Lastly today, yesterday we talked about the mega $2 billion at a $10 billion valuation seed round that former OpenAI CTO Meera Marathi had raised for her Thinking Machines lab. But part of the intrigue around that was how little information there was about what the company is actually going to do. In fact, quotes from investors suggested that the pitch deck didn't include a business plan, financials, or even a ton of product planning. Now, however, thanks to reporting from the information, we are getting some look at what TML is cooking up to compete in this crowded space.

After closing the round, investors were let in on the secret. TML is reportedly working with reinforcement learning to create reasoning models trained on specific business metrics and KPIs. The elevator pitch is apparently reinforcement learning for businesses. The idea seems to be to offer custom models that have industry-specific insights about how to generate more revenue, grow profits, etc.

The information writes, "TML may be banking on the idea that customers of AI may be willing to pay a premium for models customized for their industry, such as customer support, investment banking, or retail." At the same time, they point out, "TML may still pursue other enterprise AI ideas."

Look, all seems possible, but the proof will be in the pudding. And how much better and how much more insight you could actually get from that type of model, I think, remains to be seen. But you got to think that the enterprises out there, if this is really the course for Maradi's Thinking Machine Labs, are going to be excited at having someone who has such capitalization to focus on exactly their goals and needs.

For now, though, that is going to do it for today's AI Daily Brief Headlines Edition. Next up, the main episode. Today's episode is brought to you by Superintelligent, specifically agent readiness audits. Everyone is trying to figure out what agent use cases are going to be most impactful for their business, and the agent readiness audit is the fastest and best way to do that.

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Check it out at bsuper.ai or email agents at bsuper.ai to learn more. This episode is brought to you by Blitzy, the enterprise autonomous software development platform with infinite code context.

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then deploying over 3,000 coordinated AI agents in parallel to batch build millions of lines of high-quality code. The scale difference is staggering. Copilots might give you a few hundred lines of code in seconds, but Blitze can generate up to 3 million lines of thoroughly vetted code.

If your enterprise is looking to accelerate software development, contact us at blitzy.com to book a custom demo or press get started to begin using the product right away. Today's episode is brought to you by Vanta. In today's business landscape, businesses can't just claim security, they have to prove it. Achieving compliance with a framework like SOC 2, ISO 27001, HIPAA, GDPR, and more is how businesses can demonstrate strong security practices.

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Today's episode is brought to you by KPMG. In today's fiercely competitive market, unlocking AI's potential could help give you a competitive edge, foster growth, and drive new value. But here's the key. You don't need an AI strategy. You need to embed AI into your overall business strategy to truly power it up.

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Startups have always had myth-making and lore attached to them. The reality is that starting something from scratch, willing it into existence, aligning and assembling the resources around it that need to make it happen, and navigating all the challenges that come, is so difficult that people need to have wildly aspirational goals to ground themselves, to inspire themselves, to hang on to when times get tough.

And over time, the aspiration of what different young entrepreneurs aspire to has changed.

At any given moment, there's always one entrepreneur or one category of entrepreneurs, which are what young people coming to Silicon Valley look at as the example that they want to follow. And over the last couple of years, there has been an interesting and fairly dramatic shift in that aspirational profile. In short, more than ever before, founders are looking at how much they can do all on their own. Now, in some cases, this is pure solopreneurship.

Peter Levels has become iconic as an aspiration point for many who think that the rat race of venture capital and traditional Silicon Valley moors isn't for them. We're in an era where there are more indie hackers and solo founders. People building things that might pejoratively been called lifestyle businesses before are now not only seeing a lot of success, but being lauded for that success and held up as examples of an opportunity.

However, even when it comes to traditional startup structures, there is definitely a dramatic shift down in terms of team. You might have seen this chart earlier this year from Carta, which showed that there had been a dramatic increase in the percentage of startups that were using Carta that had solo founders and no VC funding. They called this the bootstrap solo founder era. Earlier this month, the AI World's Fair conference in San Francisco had an entire track dedicated to building and working with tiny teams. It

It was one of the trends that I argued that Swix and his crew were out in front of. Entrepreneur Henry Shi has put together a leaderboard for lean AI-native companies, which is something we'll be coming back to in a little bit. And everywhere you turn, there are teams that are celebrating hitting millions of dollars in ARR with only a few people. But to crib the famous idea of dream no small dreams for they have no power to stir men's souls, getting to some small number of millions of dollars in ARR with just a few people is not the big iconic goal.

No, the big iconic goal is now the solopreneur unicorn, the one-person, $1 billion company. This is from an interview with Sam Altman last year. Now, when will it happen? In May at the Code with Claude conference, Anthropic CEO Dario Amadei was asked that question, when the first company would hit a billion-dollar valuation with a single human employee.

With absolute confidence, he responded, 2026.

So obviously AI is at the core of this new opportunity. But there is one trend in particular that I think is a key part of this almost more than any other. And that is, of course, the rise of vibe coding. Lovable CEO Antoine Osika, in September of 2024, after quote tweeting Nick Dobos saying, building an entire full stack app should be as easy as making a new note on your phone. Antoine responded, that's why I started Lovable. Once possible, it will unlock as much creativity as YouTube, TikTok, Twitch have combined.

and create a generation of one-person unicorn founders. Now, vibe coding is impacting this trend in a couple of ways. The first of all is that the vibe coding platforms themselves are just absolutely crushing it. Earlier this week, Replit shared its growth in annual recurring revenue. It took them from 2016 to mid-2024 to go from zero to 10 million ARR.

It then took them from mid-2024 to now to go from 10 million ARR to 100 million ARR. And even though this feels correct based on all the behavior that we've seen, it still is leaving everyone's jaw on the floor. Jason from Sastr writes, no one is going to code without AI again. Lovable, meanwhile, who we just mentioned, recently shared that they were up to 75 million ARR, only nine months or something since they were founded.

Still, it's not just that coding platforms are very successful. It's what they enable, which is really the unlock when it comes to the opportunity to see one-person unicorns. Recently, Anthropix chief product officer and Instagram co-founder Mike Krieger said, When I think back to Instagram's early days, our famously small team had to make painful decisions. Either explore adding video or focus on our core creativity. With AI agents, startups can now run experiments in parallel and build products faster than ever.

Now, of course, it's beyond a small team being able to do more. You also have, thanks to vibe coding and just coding agents in general, people who can build entire production-ready MVPs in a single weekend. The speed at which a motivated solopreneur can iterate and test is like nothing we've ever seen. The speed of distribution that comes from social media is finally combined, thanks to AI and vibe coding, with the speed of building. In other words, software development is no longer the blocker. In fact, the entire structure of what's difficult about a startup has shifted.

Kanjun Shui, the CEO of AI Research Lab in Biu, said at a panel in January, I think the places where it'll be easiest and first are bottoms up, either consumer or prosumer products that don't require large go-to-market teams. I think go-to-market is actually one of the places where it's going to be difficult to automate all these relationships with other people. That human-to-human trust, I think, is still very necessary and very important. This was in the context of what the first one-person, $1 billion company would look like.

So what that means is that it's likely that solo unicorns will need to be self-serve, products that people can discover through viral media and manage and come to on their own. And as people have started to look to try to understand what the first solopreneur unicorns are going to look like, at the end of last week, we had a dramatic moment that I think will be seen as a key inflection point on this trajectory.

Base44 was acquired by Wix last week for $80 million. The company began as a solo project spun up over the last six months by founder Mauro Shlomo. He made a vibe coding tool that builds in integrations like databases, authentication, and storage to allow programmers to focus on what they're building.

The product managed to hit 250,000 users before acquisition, and Shlomo boasted of $189,000 in profit for May after covering token costs for the models that were being served. When the product launched, Shlomo said, Now, although he started solo, the team did expand to eight employees by the time they were acquired, but it showed just how far and how fast a bare-bones team can go.

In his discussion about the acquisition, Shlomo also explained where the limits are when trying to build small. He wrote, "...after a few sleepless nights and long chats with Avishai Abrami, the CEO of Wix, I realized this is the best decision I can make for Base44 and its community. I believe we have a real shot at building something transformative, a product that moves the needle for a lot of people. Partnering with Wix probably triples our chances of getting there. If we got this far bootstrapped and organic, I'm excited to see what we can do with real resources."

And part of what this brings up and is important is that although the one-person, $1 billion dream is a great anchor during the slog and toil, the real idea is more about how to design the teams of the future that incorporate humans and agents. Writing in Forbes in March, Teal fellow Kashik Tiwari laid out a roadmap. He wrote, "...the one-person unicorn model doesn't eliminate teams, it reimagines them. Tomorrow's founders might manage a hybrid workforce of AI agents, freelancers, and core employees."

For aspiring entrepreneurs, the message is clear. The barriers to building a unicorn are collapsing. With strategic AI adoption, a single visionary can now wield with the operational capacity of a mid-sized company. The question isn't whether one-person unicorns will emerge, it's how they'll reshape industries, economies, and our very definition of entrepreneurship. The revolution isn't coming, it's already here.

There are now hundreds of solo founders and tiny teams taking up this challenge. I mentioned before that Super.com founder Henry Shi had been tracking this trend closely on a website called the Lean AI Leaderboard. It focuses on around 50 startups with under 50 headcount and annual revenues above $5 million. It organizes them by revenue per employee. At the

At the top of the list are household names like Telegram, which has a billion dollars in revenue for their 30 employees, MidJourney with 500 million in revenue for a 40-person team, and AnySphere, the creator of Cursor, with 20 employees generating 100 million in revenue.

But the list also includes a bunch of teams hitting major milestones with less than 10 people. Solvely AI with $6 million for their four-person team, CalAI with a four-person team generating $12 million in revenue, and OpenArt with $12 million coming in for the eight-person company. Now again, none of these companies fit the exact description of a one-person unicorn, but they still clearly show the trend.

She also lists when these companies were founded, and it's very obvious that startups are increasingly capable of doing more with less. A few days ago, she highlighted GenSpark as the, quote, fastest-growing lean AI company we've ever seen. The 24-person consumer AI agent company hit 36 million in ARR in 45 days. She wrote, In the age of AI, speed is the only defensibility, and being lean and nimble is your unfair advantage. See you at 100 million ARR soon.

You can basically look every couple of days at Henry's profile on LinkedIn, which by the way, he's a great follow, and see some new story like this that just shows how fast things are moving. Now, on top of just the actual numbers, the Lean AI Index also makes it clear that startup culture is changing. Vanity hires, a giant office, perks, out.

Those things have given way to tiny teams vibe coding together and accomplishing things that were unimaginable before. TAM is out, real revenue is in. Bootstrapping your way to hundreds of thousands of paying customers is the new nine-figure Series A. As she put it, turns out being lean is the new flex. This is the future of company building. AI native, efficient, fast growth, founder-led, and profitable. We're just getting started.

So are we on track to see the first solo unicorn by the end of next year? I honestly think it's a pretty good bet. For now, that is going to do it for today's AI Daily Brief. Thanks for listening or watching as always. And until next time, peace.