Partnering technical founders at first inflection | @factoryAI @elevenlabs @perplexity_AI @bluefish_AI @twelve_labs @entireHQ | AI Apps, Platforms, Frontier AI
San Francisco, CA
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10 themes top of mind heading into 2026
The vibe is... world building in progress. Less sparkly research and more deploy, scale, execute on all fronts type of energy 🏗️
1. Async, always-on agents
2. Personalization gets real
3. Consumer renaissance
4. AI wearables, this time
5. Agentic commerce
6. Enterprise acceleration
7. Operational agents
8. Voice agents
9. Self-learning AI
10. Mega deals
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Something fun!
🚨 side project alert 🚨
Announcing Muse Gadgets, an open source ESP32 firmware and Linux sdk so that you can make hardware devices that work with Muse.
Grab an API token from gadgets.muse.ai and point your favorite coding agent at the github repo to build your own peripherals for Muse.
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May the best model win!
@FactoryAI Analytics is for data driven CFOs & CTOs
See what you spend and where:
- Consumption trends over time
- Cost concentration in your stack & org
- Transparency by model and user
Make the models compete for your engineering work
Announcing our new and improved Analytics, giving engineering leaders transparency into consumption, model efficiency, and adoption, broken down by model and by user across every session in the organization.
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Ann Bordetsky retweeted
One advantage of using a model agnostic platform like Factory is trust and resiliency against vendor lock-in.
Key to that trust is visibility into spend. Now you can jump into the analytics and break down exactly where Droid is working best.
User by user, session by session, model by model.
Announcing our new and improved Analytics, giving engineering leaders transparency into consumption, model efficiency, and adoption, broken down by model and by user across every session in the organization.
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Droid — look through my inbox every week for all the startups wanting to get acquired by Factory and triage which ones I should follow up with ✔️
Custom Automations are now GA in Factory.
Describe a recurring workflow, pick a schedule or event trigger, and Droid runs it to the intended result. You choose the model, the machine, and Connectors for each automation.
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Ann Bordetsky retweeted
Custom Automations are now GA in Factory.
Describe a recurring workflow, pick a schedule or event trigger, and Droid runs it to the intended result. You choose the model, the machine, and Connectors for each automation.
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For Personal Assistants, we're still SO early in the game. It's the era of experimentation, not scaling (yet)
I've backed a few teams super early that are working on personal agents, admire how they are each iterating to hone that human <-> AI interaction
Here's a great example from @ekuyda @henrymodis @wabi reimagining the UI / UX for with a visual messenger rather than limited text / chat UI
techcrunch.com/2026/09/29/ai…
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Ann Bordetsky retweeted
There's a huge opportunity right now in being the deployment layer for AI into the economy. The amount of work it takes to change out workflows in enterprises tends to be far greater than anyone realizes or would prefer. Clearly this is what the applied layer of AI is going to look like in the form of software and agents, but also it opens up new services firms opportunities.
Legacy systems need to be moved to the cloud, data organization and access needs to be updated, software needs to be connected to agents in new ways, workflows need to be reengineered for agents, HITL needs to be figured out for the process, evals need to be generated and maintained, and the entire system needs to be continually updated as new models get released and new capabilities emerge. And the full list may even be longer.
AI is not the same as just deploying software. Software you generally did the implementation of an existing, well understood category of technology, then stepped back and the customer kept running. With AI agents, you're delivering actual work augmentation to the organization, which has a completely different set of complexities associated with it. You're no longer deploying tools that the company is merely enabled by, you're deploying work output in a process. Completely different implementation and enablement process.
As a result, this is going to open up lots of new kinds of firms and plays for existing firms to diffuse AI into organizations. We're going to see approaches by industry, by size of company, and by problem inside of companies. Traditional SIs will modernize and adapt (some will clearly not adapt as well), and new entrants will also be founded in this period that take advantage of this window. Great time to be an FDE or FDE firm.
Box CEO Aaron Levie (@levie) calls out the MASSIVE opportunity for AI deployment services:
"every single one of those companies, whether that's a 50-person firm or a multi-100,000 person firm, is gonna need an army of people to go in and help them with that transformation"
"when you go to that law firm and you go to that pharma company and you go to that bank, they need something that bridges the core technology to their workflow in their business process"
"somebody has to go into that organization and get it set up, and somebody has to go and provide domain expertise to this model so it really understands our particular business process"
Vendor FDEs are incentivized to get you hooked on their platform and to spend more money.
Indie FDEs are incentivized to use the best tool for the job and to save you money.
Hire indie FDEs.
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Ann Bordetsky retweeted
We just closed an employee tender offer which values @ElevenLabs at $22BN, up 2x from our Series D in February. The tender was led by Wellington and T. Rowe Price.
A few words on how we got here ↓
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Ann Bordetsky retweeted
Factory is a launch partner for the OpenAI B2B Marketplace.
Eligible @OpenAI enterprise customers can now apply part of their existing OpenAI commitment toward Factory, driving engineering efficiency and accelerating software development with autonomous AI agents.
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Ann Bordetsky retweeted
A couple of things that make Eleven v4 special:
- Extremely low latency (100 ms p50 TTFB for Turbo)
- By far the best voice similarity
- Outstanding quality (#1 on Artificial Analysis and on our own benchmarks)
It achieves all of this while being extremely reliable. Eleven v4 uses our new post-training stack and a surprising recent research discovery that we hope will greatly accelerate our future model development.
By the end of the year, we expect delivery of new compute that will increase our training capacity almost 10x. Very excited for what's ahead!
Congratulations to the team!
Introducing Eleven v4 and Eleven v4 Turbo, our fastest and most emotive voice models yet.
Ranked #1 by Artificial Analysis.
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Huge congrats to @drfeifei @chlassner and the @theworldlabs team on their @AMD acquisition!
big vision, big outcome
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Ann Bordetsky retweeted
A couple of months ago, I joined @Wabi to help imagine a new kind of product, built around AI’s expanding capabilities and designed for everyone.
We felt it needed to be ambient, proactive, collaborative, and naturally social, making it both useful and fun. Rather than tacking AI features onto something existing, we’ve built Wabi from first principles, combining familiar product features and interactions with everything AI can do to make it easy for everyone to use together.
Wabi is a new messenger app where AI can do things for you and your whole group.
We’re starting our rollout today. I’ll see you in there.
Introducing Wabi 2.0: a new kind of messenger that makes apps and gets things done for you and your friends.
We’re building the OS for the agentic era - software that adapts to your life, gets things done, and makes more room for the people and things that matter.
Invite-only to start. Download Wabi to get on the waitlist. First come, first served.
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The personal assistant that actually gets things done in the REAL world
Let’s go @shivanipod and Fo team!
I led engineering at Google DeepMind.
Today, I'm proud to introduce Fo to give personal AI something no lab ever has... Humans.
Other personal AI's pretend AI can do everything. Fo employs humans to do tasks that AI cannot.
- 2x better at real-world task completion (beats other agents by 69%)
- 94% trust rate (4x less likely to leak private info vs Muse, Instinct)
Sign up for free: wajo.ai/join-wajo
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Solve the problem, rather than create fear
Kudos to @nvidia for laying out clear set of agent safety principles for the ecosystem
Today, with over 100 industry partners, we introduced the NVIDIA Open Agent Safety Platform, bringing together OpenShell and Sentry.
Artificial intelligence is extraordinary technology that will advance discovery, productivity, security, health, and prosperity for generations to come.
But its full promise can only be realized when people have confidence that AI is being built to be safe and deployed with wisdom and responsibility.
This is bigger than a single product. It's the beginning of an open ecosystem to build the trust layer for safe agent systems.
Together, we are building the foundation of the AI economy.
Trust and innovation are not in conflict. Safety is how trust is earned. We must build not only the most capable AI, but the most trusted AI, so that this extraordinary technology can realize its enormous promise for the world. nvda.ws/4hcoq7m
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Velocity comes from finding just the right balance between structure + autonomy
Process feels safe, secure, knowable, auditable but often strips people of a total ownership mentality
Best balance is small, atomic unit teams with extreme ownership and just enough org scaffolding to get them aligned and swimming in the same current
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