Kolento Hou (@KolentoH)

Exciting work from @fangchangma and @nuance_ai.

The real breakthrough won't be AI that feels more human. It'll be AI that helps us become more fully human.

AI that feels human is a milestone, not the destination.

The real promise of human foundation models is not just understanding how we think, feel, and connect, but expanding what we're capable of becoming.

Fangchang Ma Verified account @fangchangma 2d

The first AI persona you’ll actually want to meet face-to-face.

Most AI personas stare blankly while you talk. Emma reacts while you’re still speaking.

After 18 months of research at @nuance_ai, this is Emma, built on Nuplex, our full-duplex audiovisual foundation model.

View quoted post on X

Kolento Hou @KolentoH Nov 3

As a recent @nyuniversity grad, I keep wondering: if AI takes over entry-level work, where do we get our experience?
1. We rewrite our resumes with AI to get through an ATS.
2. We rehearse interviews with AI, then sometimes get interviewed by it.
3. We open AI recruiting emails, hoping a real conversation will follow.
4. We build a working demo, then hit “experience required.”

AI makes it easier to do the work. Getting a chance to prove ourselves still feels hard.

And I don’t think that feeling belongs only to new grads. Changing careers, returning to work, or watching your job change around you can bring back the same uncertainty.

I’d want someone to give me a real problem, let me work through it, and talk to me about the choices I made. So we tried to create that opportunity.

At @EmergencesLabs, we brought candidates and 10 companies together for our SF Tech Week AI-Native Talent Hunt around a simple idea: Do the Job to Get the Job.

We asked candidates to tackle real problems set by our Hiring Partners like:
- Protect a browser agent from malicious instructions on a webpage.
- Turn design guidelines into checks that catch real UI issues.
- Build a support agent that follows policy and knows when to bring in a human.

Hiring managers could see the process/thinking behind the result: what people checked, questioned, and changed.

Thank you @darijan___ , Evelyn Yang, Yaxuan (Scarlett) Mao, Charlie Lin, Duo Ding, Sky Zhang, Yiling Zhou, Ash Bao, Daniel Tian, Yuxuan Liu, and all our hiring partners for bringing real problems and taking people’s work seriously. And @Tiny_Fish, @OpenAI, and our team for making it happen.

We want that practice and feedback to help people build judgment sooner, including instincts that can take years, even decades, to develop.

This event is a start. At @EmergencesLabs, we want to make learning by doing accessible to everyone: a safe place where newcomers can work through hundreds of real business tasks contributed by companies, make mistakes, get feedback, and try again.

I’ve been lucky to have people take my unfinished ideas seriously and help me figure out what to try next. I want more people to have that support as they grow into the work they want to do.

This November, we’re bringing the Talent Hunt to @UCBerkeley and @Stanford, with a bigger focus on juniors and new grads.

Follow our calendar and come work on a real problem:
lnkd.in/gZfT3kPG

lnkd.in LinkedIn This link will take you to a page that’s not on LinkedIn

Emergences Labs Verified account @EmergencesLabs Nov 2

“The coding interview is dead!” We have turned the idea by @felixrieseberg at @AnthropicAI into a huge AI-Native Talent Hunt at SF Tech Week.

Don’t interview people about the work. Watch them do the work.

We believe hiring needs a better signal than LeetCode: Proof of Work with your PROCESS, a new credential in the AI era.

We made it happen with early believers in changing how AI-native talent is assessed and hired. Thank you to our amazing co-host @Tiny_Fish, agent partner @OpenAI Codex, and hiring partners @GenDigitalInc, @ZingageAI, @Gruve_ai, @cresta, @CreaoAI, @SmithfieldFoods, @dify_ai, @OpusClip, and @openart_ai.

Together with the enthusiasm of our candidates, we got:

• 1,600+ signups
• 300+ attendees
• 200+ submissions
• 10,000+ minutes working videos

How it works:
1. Companies turn internal business problems into real work sample tasks on NeoWork (neo-work.ai).
2. Candidates tackle them on NeoHuman (neo-human.ai) using Codex and other AI tools.
3. NeoWork evaluates the deliverable and recorded process. We highlight moments that reveal human judgment: catching an AI mistake, checking a claim before acting, or changing an approach that isn’t working.
4. Hiring managers review the work, our assessment, and supporting evidence to decide whom to interview or hire.

We grouped the 10 companies' works into 3 tracks: Product, Marketing, and Engineering. Each work was designed for about an hour. Examples include:

@GenDigitalInc: design a browser agent’s action pipeline that resists prompt injection.
@CreaoAI: turn design guidelines into enforceable rules and prove they catch real UI issues.
@cresta: build a support agent that follows policy and knows when to escalate.
@openart_ai: select consistent memories for an AI director.
@dify_ai: decide whether a support AI is ready to ship, backed by evidence.

Congratulations to our overall winners!

🥇 @samshanmukh: 97/100
🥈 Rohan R: 89/100
🥉 Shivam Mahajan: 87/100

And our track winners:
Product: Marcus Wong
Marketing: @AndrewDrok
Engineering: Akshat Patel

We know today’s job market is tough, even for people already in work:
- Juniors need experience to get experience.
- Career changers have skills their old titles don’t show.
- Laid-off professionals have to prove themselves all over again.
- Employed professionals must adapt to AI while keeping up with today’s workload.

That’s why we’ll keep hosting AI-Native Talent Hunts, with campus events at @UCBerkeley and @Stanford this November.

Follow our events calendar (lnkd.in/gzjNWahB) for your next chance to show what you can do.

View quoted post on X

Kolento Hou @KolentoH Oct 30

Excited to speak at the TechEquity Ai Summit on November 5 in Menlo Park!

I’ll join @OanaIgnatRo , Karthik Yogeshwar, and moderator Abhijeet Joshi for “Beyond the Hype: What AI Education Is Worth to Learners, Schools, and Employers.”

At @EmergencesLabs, we believe it's about Evaluation.

As AI becomes increasingly capable, the question is no longer just what people can accomplish with AI but:
1. what human skills we should be developing?
2. and how we evaluate them?

If we can't measure what people are actually learning, how do we know we're educating them in the right direction?

Looking forward to the conversation!

Big thanks to Sheena Tu, Uyoyo Charity Okonkwo, PMP, Rona Bianca Samaco, and Mahan Soltanzadeh, and the entire TechEquity Ai team for bringing this together!

Check the agenda: lnkd.in/gjpAmyQ2

Kolento Hou @KolentoH Oct 29

As AI becomes more autonomous, the question isn't just what machines can do, but what humans should remain responsible for.

Excited to moderate “Safety at Inference Time: Testing, Understanding, and Constraining AI Systems” at #InferCon on November 16 in San Francisco, hosted by @datadoghq

Looking forward to exploring how we can build AI systems that are not only more capable, but also more understandable, trustworthy, and accountable to humans.

Hope to see you there!

Kolento Hou @KolentoH Oct 24

Don't interview people about the work. Watch them do the work.

As more people delegate not just tasks, but their thinking and judgment to AI, the future of hiring signals lies in the process, not just the output.

Check out what we are doing at: neo-work.ai

neo-work.ai NeoWork AI: The Agent for AI-Native Talent Assessment We help organizations redesign roles and build AI-integrated work-sample assessments that identify & hire talent capable of 10x performance with AI.

Emergences Labs Verified account @EmergencesLabs Oct 23

We brought our AI-native talent playbook to @SHRM Northern California’s Annual Conference, hosted by the world’s largest HR professional association.

On stage, our CEO @KolentoH shared our approach to assessment: realistic work tasks, AI tools of the candidate’s choice, and visibility into how they work.

At our booth, 200+ people stopped by over two days, including HR professionals from consumer businesses, healthcare, and finance.

Their questions about AI varied. Some teams weren’t using it. Some were exploring workflow integration. Others were looking for more value from tools they already used.

Across these contexts, a polished result tells part of the story. Checking AI-generated answers, comparing approaches, and questioning assumptions can reveal transferable skills.

That’s what we want AI-native talent assessment to make visible.

Thank you to SHRM Northern California and everyone who shared their experiences with us!

More photos in comments! 👇

View quoted post on X

Kolento Hou

Latest posts 5