Enginears

We welcomed Dan Schiebler, CTO and Co-Founder Artemis Security. Today we'll be talking about the unique technical problems and scale at Artemis, what it means to build with an "AI-native approach," and how they've built a team with an extremely high bar for talent to tackle these complex challenges.

• Intro into Artemis Security and the problem space

• Dan's background at Twitter (X), Abnormal AI and founding Artemis.

• Understanding the technical landscape of "noisy data" and enormous scale

• How to build a high bar technical team and why in today's AI-native landscape

If you're keen to share your story, please reach out to us!

Guest: https://www.linkedin.com/in/dan-shiebler-10219b42/

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The workforce management and customer support world has been widely spoken about as one of the areas to change in the age of AI. This week we are welcoming John Wang from Assembled to talk to us about the journey of building Assembled (workforce management platform), key engineering/design choices to reducing AI spend.

We’ve got a great breakdown in the show of what it’s like to go from processing tens of billions of tokens daily to achieving "LLM frugality," the key engineering challenges faced, and the future of using AI to improve infrastructure.

• Intro into John's background and Assembled's mission

• Customer Operations has been widely reported as an area to change in the AI; what's his frontline view of this and what is actually happening?

• How they built the Assembled platform?

• Spotting an opportunity to keep performance high but reduce AI spend without impacting customer experience and why these decisions were made

• We broke down the engineering challenges of replacing models

• Future bets on agents, infrastructure in AI and where Assembled are heading.

If you're keen to share your story, please reach out to us!

Guest: https://www.linkedin.com/in/johnjianwang/

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This week I’m joined by Matt Lynch, CTO and Co-founder of Sage. Sage are bringing technology modernisation and Applied AI to the healthcare // care home industries. Matt is an ex-Palantir alumni, raised a $35M in Q1 2025, we’re going to be getting under the hood of some of the challenges in the technology <> healthcare intersection.

We broke down the problem space of healthcare technology and how it needed a refresh.

o   Hardware <> Software Interoperability in healthcare

• Applying AI to that

• Legacy Systems + Integration with cloud native + AI solutions/tools.

o   Engineering culture + challenges inside of Sage (product/platform challenges; mindset; FDE approach etc)

o   Velocity of people able to build with 2 people in

o   Anticipated technical/problem spaces to come in the healthcare space

• Future of Healthcare and what experts think the outlook might look like from a technology standpoint.

• Future plans for growth for Sage

o   Hiring Goals in NYC

o   Geographic Expansion

If you're keen to share your story, please reach out to us!

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This week we are joined by Charlton Roberts, CTO at FLORA. FLORA are building AI for the creatives. This week, we're going to be talking about three key components that really make up their business and how they build for the creative space.

They have three pods (Intelligence, AI and Craft)

This week we are diving into the make-up of Intelligence, AI, internal agents, re-routing between different models, collaboration, and Craft, performance, optimisation + more.

• We dived into Charlton's background and some of the time he's spent in the Creative space.

• Transition from larger Creative spaces to an AI-native environment

• What are FLORA building, why and how?

• The three pods that make up their platform (Intelligence, AI and Craft); we break them down, understand the engineering challenges in each and what thrives in those pods.

• Where's the creative space heading and why would you use an AI-native product moving forward?

• Who and how they are hiring in New York.

If you're keen to share your story, please reach out to us!

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This week I'm joined by Mek, who is VP of Engineering at Stuut, a Series A-backed A16Z business in New York. We're going to be diving into the AI-native world of accounts receivable. In Feb 2026, Stuut passed a monumental feat in processing a billion dollars in transactions for their customers. Mek joins us to discuss what they're building, some of their engineering challenges, and bringing some of his leadership principles to building an AI-native business and what we can learn from the team at this moment in time.

• Who are Stuut, who are they building for and why?

• The journey from $0-$1B and Stuut -> Stuut 2.0

• Taking engineering principals from growth journeys w/ GitLab and VMWare to what shipping looks like now.

• A day in the life of an engineer today and what "high agency" should look like.

• Building in an AI-native company

• How and who they are growing with?

If you're keen to share your story, please reach out to us!

Guest: https://www.linkedin.com/in/srunyu/

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Catherine Jue, co-founder at Kernel (https://www.kernel.sh/)

Kernel are building web agents in a crazy fast, open source way for them to be able to access the internet.

We're going to be talking about the technical, product, and business challenges that throw up something as ambitious as this. As we always do, we'll be getting to know the founder behind the idea, or the leader behind the idea.

-> Building a web browser agent and uncovering the use cases and capabilities

-> From millisecond speeds to cloud infrastructure at scale we break down some of the engineering challenges that exist at Kernel that you're trying to solve on a day-to-day basis.

-> The challenges in building a web browser agent and user / security adoption.

-> Introducing Managed Auth: a standardized way for agents to log in and stay logged in across the internet. (https://x.com/usekernel/status/2021581721280401709)

-> Who and how they are hiring.

If you're keen to share your story, please reach out to us!

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Newly-Series C funded Suno came to talk to us about AI-generated music in this new era of streaming AI-generated music at unprecedented scale and the ambiguity that comes with building in a new category globally.

• We broke down the mission

• We broke down the dynamics of the Platform team

• Outlining process of building at serious scale // availability = ultimate goal of platform engineering.

• How do you scale globally in an AI era where not many people have been before?

• How is AI changing the platform game?

• Deep-dive into some of their engineering challenges

• Growth over the next 12 months!

If you're keen to share your story, please reach out to us!

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Today I’m joined by Deductive AI. Sameer is an absolute powerhouse, one of the Founding Engineers at Databricks, spent 5 years at Meta building large scale services and now building Deductive AI.

Deductive are building self-healing, self-learning services. They are building reinforcement learning into their product offering to heal legacy (..even new code) being generated by AI.

• Sameer's background and being a Founding Engineer at Databricks

• Recognising an opportunity in reinforcement learning and self-healing / self-learning code and systems

• Building an AI-SRE

• Generating a course of action in ambiguous cases -> an open-ended engineering challenge that has never been seen before and planning for cases like this

• Bets that Deductive are placing in the next 6-12 months

If you're keen to share your story, please reach out to us!

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This week I’m delighted to introduce Ayush Sharma, Founder and CEO of Warp.

Warp are building the next-gen, AI-native employee management platform for fast-growing companies.

We are diving into Warp’s journey, why they are tackling the employee management space and more importantly the how behind their journey

– it wouldn’t be an Enginears podcast if we aren’t breaking down the product and engineering challenges behind this.

- 2 years in, closed $18M Series A, alongside YC, Dropbox C-level, Amjad (Replit)

- crew of highly technical + product folks.

- Understanding the friction points of the payroll ecosystem and how Warp are re-building this with a highly-technical, AI-native approach. - Scale, performance and fault-tolerancy challenges.

- Ayush's product-first mindset and how he believes companies of 2025+ will build category defining companies.

- Meta points around AI/LLM's

If you're keen to share your story, please reach out to us!

Guest: https://www.linkedin.com/in/ayushsharma01/

Careers: https://www.joinwarp.com/careers/roles

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If you're keen to share your story, please reach out to us!

Guest:

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Twitter: https://x.com/Enginearsio

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