It uses real-time user corrections to post-train deployed models.
Will Knight#826
New: A group of AI researchers from Google DeepMind, Apple, MSL, and OpenAI are launching a new startup called Trajectory to build a continual learning platform for companies.
They've raised a $15M seed round from Sarah Guo's Conviction, Jeff Dean, Fei-Fei Li, and others.
Many users congratulated the TrajectoryLabs team on its $15M raise for a continual learning platform for AI agents, calling the vision for turning experience into intelligence exciting and forward-looking.
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Today, @MichaelElabd, @QuantumArjun, and I are excited to announce Trajectory.
We are a research lab and product company building the platform for Continual Learning.
Our platform unlocks the signal already sitting in product usage, so companies can continuously post-train large-scale agentic models that outperform the frontier. @trajectorylabs
We’ve raised $15M from @Conviction, @BessemerVP, @radicalvcfund, @jeffdean, @drfeifei and more.
We’re partnering with some of the best AI-native companies: @ClayRunHQ @Harvey, @DecagonAI, @mercor_ai, @RogoAI to power their agentic systems, some of which we are already in production with.
We’ve brought together a world class research team from DeepMind, OpenAI, Apple, Meta Superintelligence, Amazon AGI, Scale AI, and an elite product team from Stripe and Figma.
AI will never again start on day one. Every correction, every retry, every edit will make products smarter. This is Continual Learning.
The most likely way continual learning manifests in the coming few years is through products used directly for knowledge work.
Sort of how cursor can continually train their models with real-world data and RL, Claude, Copilot, and co will see if they can for knowledge work.
I was chatting with Ronak a few weeks ago when this was crystalizing for me, so it's fun to see a startup in that area.
Today, @MichaelElabd, @QuantumArjun, and I are excited to announce Trajectory.
We are a research lab and product company building the platform for Continual Learning.
Our platform unlocks the signal already sitting in product usage, so companies can continuously post-train large-scale agentic models that outperform the frontier. @trajectorylabs
We’ve raised $15M from @Conviction, @BessemerVP, @radicalvcfund, @jeffdean, @drfeifei and more.
We’re partnering with some of the best AI-native companies: @ClayRunHQ @Harvey, @DecagonAI, @mercor_ai, @RogoAI to power their agentic systems, some of which we are already in production with.
We’ve brought together a world class research team from DeepMind, OpenAI, Apple, Meta Superintelligence, Amazon AGI, Scale AI, and an elite product team from Stripe and Figma.
AI will never again start on day one. Every correction, every retry, every edit will make products smarter. This is Continual Learning.
AI is largely frozen after deployment. That has to change.
Excited that my partners at Conviction (@mvernal @igarciacamargo) are backing @TrajectoryLabs as they help companies improve agents based on signals from real world interactions.
Today, @MichaelElabd, @QuantumArjun, and I are excited to announce Trajectory.
We are a research lab and product company building the platform for Continual Learning.
Our platform unlocks the signal already sitting in product usage, so companies can continuously post-train large-scale agentic models that outperform the frontier. @trajectorylabs
We’ve raised $15M from @Conviction, @BessemerVP, @radicalvcfund, @jeffdean, @drfeifei and more.
We’re partnering with some of the best AI-native companies: @ClayRunHQ @Harvey, @DecagonAI, @mercor_ai, @RogoAI to power their agentic systems, some of which we are already in production with.
We’ve brought together a world class research team from DeepMind, OpenAI, Apple, Meta Superintelligence, Amazon AGI, Scale AI, and an elite product team from Stripe and Figma.
AI will never again start on day one. Every correction, every retry, every edit will make products smarter. This is Continual Learning.
We have been exploring new algorithmic frontiers and are excited to share our contributions to Self Distillation Policy Optimization (SDPO) for agentic continual learning, check out our blog post here:
https://trajectory.ai/field-notes/scaling-sdpo
Congrats @rronak_ and team!
Insane cap table, set of design partners, and team.
Today, @MichaelElabd, @QuantumArjun, and I are excited to announce Trajectory.
We are a research lab and product company building the platform for Continual Learning.
Our platform unlocks the signal already sitting in product usage, so companies can continuously post-train large-scale agentic models that outperform the frontier. @trajectorylabs
We’ve raised $15M from @Conviction, @BessemerVP, @radicalvcfund, @jeffdean, @drfeifei and more.
We’re partnering with some of the best AI-native companies: @ClayRunHQ @Harvey, @DecagonAI, @mercor_ai, @RogoAI to power their agentic systems, some of which we are already in production with.
We’ve brought together a world class research team from DeepMind, OpenAI, Apple, Meta Superintelligence, Amazon AGI, Scale AI, and an elite product team from Stripe and Figma.
AI will never again start on day one. Every correction, every retry, every edit will make products smarter. This is Continual Learning.
Trajectory is on a mission to enable Continually Learning systems for every company. Learn more about our plan to do so:
https://trajectory.ai/field-notes/manifesto
@rronak_ @MichaelElabd @QuantumArjun Congrats! The potential of systems that learn continuously from observations and their own mistakes (and successes!) is high, and these systems are likely to be more robust and adaptable than systems that don't learn continuously.
We’d like to thank everyone who has backed us and helped get to where we are today: @Conviction, @BessemerVP, @radicalvcfund, @svangel, @_geniusventures, @ExceptionalCap, @Antifund, @EssenceVenture, along with angels @JeffDean, @drfeifei, @akothari, @stanine, Kareem Amin, @nikitabase, @arashf @Thom_Wolf, @ankrgyl, @OfficialLoganK, @cjc, @l2k, @KyleHParrish, @bernhardsson
We are also grateful for the amazing companies who have helped us scale Trajectory: @Baseten, @thinkymachines, @anyscalecompute, @NovaSkyAI, @googlecloud, @GoogleStartups, @daytonaio, @togethercompute and @OpenRouter.
New trend: continual learning.
I first showed you this with Levangie Labs from @blevlabs.
You "grow" an agent by teaching it. It gets better over time.
It works because it has a better memory, so can try things, and learn, and remembers what it learned, so it gets better over time.
Which makes it hard to get. Starts out like a brilliant 16 year old, then you gotta take it to university.
I spent some time last week with Ronak learning about his tech and company. Quite excellent, which explains why he got funded.
I'm not compensated by Ronak, just trying to feature great new AI startups.
Today, @MichaelElabd, @QuantumArjun, and I are excited to announce Trajectory.
We are a research lab and product company building the platform for Continual Learning.
Our platform unlocks the signal already sitting in product usage, so companies can continuously post-train large-scale agentic models that outperform the frontier. @trajectorylabs
We’ve raised $15M from @Conviction, @BessemerVP, @radicalvcfund, @jeffdean, @drfeifei and more.
We’re partnering with some of the best AI-native companies: @ClayRunHQ @Harvey, @DecagonAI, @mercor_ai, @RogoAI to power their agentic systems, some of which we are already in production with.
We’ve brought together a world class research team from DeepMind, OpenAI, Apple, Meta Superintelligence, Amazon AGI, Scale AI, and an elite product team from Stripe and Figma.
AI will never again start on day one. Every correction, every retry, every edit will make products smarter. This is Continual Learning.
If building for the new frontiers of continual learning excites you, let’s chat:
https://jobs.ashbyhq.com/trajectory
Thank you @ZeffMax for covering of our team and company on @WIRED:
https://www.wired.com/story/ex-google-apple-ai-researchers-want-to-make-ai-that-gets-smarter-as-you-use-it/
Cracking continual learning would make AI far more capable, because models could improve from real usage after deployment.
Trajectory just launched a continual learning platform, backed by a $15M round, to turn every agent trace and user correction into a system that keeps improving after deployment.
A neolab with ex-DeepMind, OpenAI, and Meta Superintelligence researchers that also has paying customers, totally normal.
AI products are still frozen software, because users correct them every day but those corrections rarely update the model, the prompts, or the surrounding agent workflow.
Trajectory’s core unit is the trajectory, which combines what the agent did with what the user accepted, rejected, edited, retried, or fixed later, so companies can train on full failure chains and improve model weights, harness, and prompts together.
The next major AI leap almost certainly will come from models that keep learning after they are shipped.
Today, @MichaelElabd, @QuantumArjun, and I are excited to announce Trajectory.
We are a research lab and product company building the platform for Continual Learning.
Our platform unlocks the signal already sitting in product usage, so companies can continuously post-train large-scale agentic models that outperform the frontier. @trajectorylabs
We’ve raised $15M from @Conviction, @BessemerVP, @radicalvcfund, @jeffdean, @drfeifei and more.
We’re partnering with some of the best AI-native companies: @ClayRunHQ @Harvey, @DecagonAI, @mercor_ai, @RogoAI to power their agentic systems, some of which we are already in production with.
We’ve brought together a world class research team from DeepMind, OpenAI, Apple, Meta Superintelligence, Amazon AGI, Scale AI, and an elite product team from Stripe and Figma.
AI will never again start on day one. Every correction, every retry, every edit will make products smarter. This is Continual Learning.
@rronak_ @MichaelElabd @QuantumArjun Huge congrats :) very excited to see people take a real shot at continual learning!
@rronak_ @MichaelElabd @QuantumArjun I need someone to write a prompt for my printer
@rronak_ @MichaelElabd @QuantumArjun AI startups now drafting researchers like NBA free agency
Congrats @rronak_, @MichaelElabd, @jennzhaii, and the rest of the Trajectory team on the launch! Excited to see more real world problems solved via customized AI.
Today, @MichaelElabd, @QuantumArjun, and I are excited to announce Trajectory.
We are a research lab and product company building the platform for Continual Learning.
Our platform unlocks the signal already sitting in product usage, so companies can continuously post-train large-scale agentic models that outperform the frontier. @trajectorylabs
We’ve raised $15M from @Conviction, @BessemerVP, @radicalvcfund, @jeffdean, @drfeifei and more.
We’re partnering with some of the best AI-native companies: @ClayRunHQ @Harvey, @DecagonAI, @mercor_ai, @RogoAI to power their agentic systems, some of which we are already in production with.
We’ve brought together a world class research team from DeepMind, OpenAI, Apple, Meta Superintelligence, Amazon AGI, Scale AI, and an elite product team from Stripe and Figma.
AI will never again start on day one. Every correction, every retry, every edit will make products smarter. This is Continual Learning.
@rronak_ @MichaelElabd @QuantumArjun Great up until now the only advantage I had left over AI was that I could actually learn from my mistakes (not that I usually would)
@MichaelElabd @QuantumArjun Finally, shoutout to @metalab for our incredible website design at https://trajectory.ai/!
.@rronak_ and his team at @trajectorylabs are phenomenal. I've always enjoyed spending time with him. They super genuine, smart, down to earth and great people to work with. Super excited for the work they are doing:
Today, @MichaelElabd, @QuantumArjun, and I are excited to announce Trajectory.
We are a research lab and product company building the platform for Continual Learning.
Our platform unlocks the signal already sitting in product usage, so companies can continuously post-train large-scale agentic models that outperform the frontier. @trajectorylabs
We’ve raised $15M from @Conviction, @BessemerVP, @radicalvcfund, @jeffdean, @drfeifei and more.
We’re partnering with some of the best AI-native companies: @ClayRunHQ @Harvey, @DecagonAI, @mercor_ai, @RogoAI to power their agentic systems, some of which we are already in production with.
We’ve brought together a world class research team from DeepMind, OpenAI, Apple, Meta Superintelligence, Amazon AGI, Scale AI, and an elite product team from Stripe and Figma.
AI will never again start on day one. Every correction, every retry, every edit will make products smarter. This is Continual Learning.
Trajectory is trying to take a product feedback loop that has supercharged AI coding products like Claude Code and Cursor, and apply it to a broader set of AI products.
It's a big bet around post-training on real-world interaction data.
