The DevLab Podcast

Alexander Piskunov’s fund backed two hardware startups whose technology worked. One printed building parts on-site and went on to raise from Khosla Ventures. The other built giant human-piloted fighting robots for a TV deal that never came.

Alex has been on both sides of the table. He built and sold a wine import business, spent about ten years as an investor (including as founding partner at KAAN Ventures and partner at Ruvento Ventures), and now advises governments on technology and investment. He joins Phil Kell to talk about what investors look for in a startup once the tech works, what it means when existing investors skip a funding round, and what to check before you join an early-stage startup.

“An idea by itself, I would say it’s worth nothing. It’s all about the implementation.”

Would you take shares over salary at an early-stage startup? Tell us in the comments.

Connect with Alex: https://www.linkedin.com/in/alexander-piskunov

DevLab is brought to you by Archer from hackajob. Discover more at https://meetarcher.com

#DevLab #Startups #VentureCapital

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Ask a leadership team for their AI initiatives and the list comes back as savings. MJ's argument is that most companies are thinking far too small about what the technology can do, and she has an exercise for it. Write down your AI initiatives, but you're not allowed to mention efficiency, cost, or productivity per person. The second list takes longer to write, and it's the one worth having.

MJ is Chief Strategy and Revenue Officer at Credibly, where she runs growth and the company's AI programme. Before that she spent eight years at Ford, founded a mobility startup inside the company and took it external. She has a literature degree and an MBA, and she'll tell you she's a writer first and a technologist second.

We get into why an organisation behaves like a complex organism rather than a machine, what ROI looks like before it looks like money, why copying your best employee caps you at your best employee, and the shipping container story she uses to explain what automation actually changed. Plus deepfakes, shadow AI, and why she expects the strongest hires of the next decade to pair a technical skill with a humanities one.

Chapters

00:00 Intro
01:00 Ford, and building a startup inside a big company
05:31 What a failed startup teaches you about where you work best
08:54 Why an organisation is a complex organism, not a machine
14:17 The shipping container story
16:55 The small AI projects that go nowhere, and why you need them
19:01 What ROI looks like before it looks like money
21:49 Why copying your best employee fails
23:57 AI as an abundance model
27:06 Ban the word efficiency from your AI planning
29:45 Why leaders can't delegate their AI learning
32:24 Deepfakes, shadow AI, and risk becoming everyone's job
34:12 Efficiency at one end, burnout at the other
36:09 Compliance, ethics, and the certification that doesn't exist yet
44:23 What's missing from the AI conversation

Follow MJ on LinkedIn: https://www.linkedin.com/in/minyang-jiang-6981a148/

DevLab is hackajob's series on how AI actually lands inside organisations, with the people doing the work. Discover more at hackajob.com

#AI #AIAdoption #Leadership

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Luis Hernandez is a Senior Engineering Manager at Zillow, where he leads a team building Zillow's seller experience across Mexico and the US. In this DevLab episode he explains how a team split across Mexico and the US ships core product that millions of Americans open every day, how AI shows up in the actual engineering work, what Zillow looks for when it hires engineers, and why you don't have to become a manager to keep growing.

What you'll learn:

How Zillow builds core product from Mexico, not side projects
How to prepare for big tech interviews, and why failing a few is normal
The difference between high-impact projects and high-impact systems
How Zillow's engineers actually use AI, from writing code to the Zestimate
Why you can reach senior levels at Zillow without managing people
What Hack Week, team retreats, and Zillow's "Cloud HQ" distributed setup look like

Questions answered in this episode:

What does an engineering manager at Zillow do?
What is it like to work at Zillow as an engineer based in Mexico?
How does Zillow use AI in software engineering?
How do you get hired at big tech from Mexico?
Can you grow at Zillow without becoming a manager?
About DevLab: DevLab is the series where we sit down with the people behind the tech you actually use and find out how it really gets built.

Read more about Zillow and the team's work: https://hackajob.com/company/zillow

Like the sound of a team that builds core product from Mexico, invests in its distributed culture, and lets engineers keep growing without pushing them into management? Create your free hackajob profile and get matched to roles that fit: https://hackajob.com/talent/sign-up

🔔 Subscribe for more conversations with the engineers behind the tech you use.

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🔥 Hiring? Archer is hackajob's AI sourcing agent. It finds and qualifies the passive, in-demand talent your team can't reach and delivers them straight into your ATS, while your recruiters make every hiring decision. Book a free demo: https://hackajob.com/employer/book-a-demo

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What does it actually take to move AI from experiment to production inside one of the world's largest banks?

In this episode of DevLab, Phil sits down with Francois Buet-Golfouse, Global Head of AI and Machine Learning for Barclays Global Markets. Francois has spent over a decade working at the intersection of quantitative finance and machine learning, helping AI ideas move from experimentation to production within Barclays Global Markets.

The conversation covers the real mechanics of building AI in a regulated environment: how to decide which ideas are worth pursuing, what it takes to get from proof of concept to production, and why starting with the business problem matters more than starting with the model.

Francois also shares his perspective on responsible AI in financial services, where agentic systems are heading, and what skills will matter most for engineers and data scientists as AI becomes more deeply embedded in how teams work.

In this episode:
 ▸ How AI ideas are filtered and prioritised across Barclays Global Markets
 ▸ The staged process that takes experiments from proof of concept to live production
 ▸ Why LLMs are only part of the story in finance
 ▸ What "silent bugs" in AI-generated code reveal about the limits of automation
 ▸ Agentic AI: the potential and the guardrails
 ▸ What Francois thinks people in tech should be focusing on right now

Guest: Francois Buet-Golfouse, Global Head of AI and Machine Learning, Barclays Global Markets
Host: Phil Kell, VP of Marketplace, hackajob

Although Mr. Buet-Golfouse is employed by Barclays, the views expressed here today are his own and may be different from those of, and should not be attributed to, Barclays.  The views expressed here are provided for information purposes only and are subject to change.  The content of this discussion does not constitute a recommendation from any Barclays entity or employee to any person.  Barclays is not offering to sell or seeking offers to buy any product or enter into any transaction by way of this discussion.  Barclays is not providing any financial, economic, legal, investment, accounting, or tax advice to any person through this discussion.

What would you like us to talk about next?

🔥 Looking for a new role? Create your free hackajob profile and let Archer, your AI advocate in the job market, match you to roles that fit your goals. Apply knowing you're a good fit: https://hackajob.com/talent/sign-up

🔥 Hiring? Archer is hackajob's AI sourcing agent. It finds and qualifies the passive, in-demand talent your team can't reach and delivers them straight into your ATS, while your recruiters make every hiring decision. Book a free demo: https://hackajob.com/employer/book-a-demo

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What does it actually take to build technology people can rely on? In this episode of DevLab, Phil sits down with three people from BAE Systems who all came into tech through very different routes and are now doing very different things.

Johanna started out wanting to be a primatologist. Davinder got her first computer from her uncle at 14 and has been writing code ever since. Emma came from sports coaching, via a call centre, into a career spanning IT, service management and business relationship work.

Together they talk about squiggly careers and the value of non-traditional routes into tech, what it means to stay hands-on as a senior engineer, building systems that sit quietly behind everyday life, AI adoption and where human judgement still matters, inclusion, neurodiversity and OutLink at BAE Systems, and what teams need to feel safe enough to actually do their best work.

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🔥 Hiring? Archer is hackajob's AI sourcing agent. It finds and qualifies the passive, in-demand talent your team can't reach and delivers them straight into your ATS, while your recruiters make every hiring decision. Book a free demo: https://hackajob.com/employer/book-a-demo

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Fauzia didn't plan to go into tech. She wanted to be a doctor. When Afghanistan's university entrance exam placed her in computer science instead, she had no laptop, no coding experience, and no clear idea of what she'd signed up for.

Then the pandemic hit. Then in 2021, everything changed again. Women were told they could no longer continue their studies.

In this episode of the DevLab podcast, Phil, VP of Marketplace at hackajob,  sits down with Fauzia, Software Engineer and Executive Director at CodeWeekend, a community-led bootcamp helping Afghan developers build real technical skills. 

They talk about her unexpected journey into tech, the reality of learning to code through internet shutdowns and electricity shortages, and the women's cohort CodeWeekend ran in 2025 for Afghan women banned from formal education.

This is a conversation about resilience, community, and what it looks like when talent refuses to be stopped.

Follow CodeWeekend on LinkedIn and get in touch for any collaborations: https://www.linkedin.com/school/codeweekend/

What would you like us to talk about next?

🔥 Looking for a new role? Create your free hackajob profile and let Archer, your AI advocate in the job market, match you to roles that fit your goals. Apply knowing you're a good fit: https://hackajob.com/talent/sign-up

🔥 Hiring? Archer is hackajob's AI sourcing agent. It finds and qualifies the passive, in-demand talent your team can't reach and delivers them straight into your ATS, while your recruiters make every hiring decision. Book a free demo: https://hackajob.com/employer/book-a-demo

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How do you secure an organisation the size of Tesco?

In this DevLab episode, we’re joined by Harry McLaren, Head of Cyber Defence, and Jason Larkin, Head of Platform Security Architecture at Tesco, to unpack how modern security works at real scale.

They talk through identity becoming the new perimeter, why attackers are increasingly “logging in, not breaking in”, and how architecture and cyber defence teams work together to reduce real-world risk. It’s a grounded conversation about fundamentals, complexity, cloud security, and what actually matters when theory meets reality.

Read more about Tesco: https://hackajob.com/company/tesco?hsLang=en

What would you like us to talk about next?

🔥 Looking for a new role? Create your free hackajob profile and let Archer, your AI advocate in the job market, match you to roles that fit your goals. Apply knowing you're a good fit: https://hackajob.com/talent/sign-up

🔥 Hiring? Archer is hackajob's AI sourcing agent. It finds and qualifies the passive, in-demand talent your team can't reach and delivers them straight into your ATS, while your recruiters make every hiring decision. Book a free demo: https://hackajob.com/employer/book-a-demo

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AI is moving fast. In legal tech, getting it wrong isn’t an option.

In this DevLab podcast episode, we’re joined by Min Chen, Senior Vice President & Chief AI Officer, and Serena Wellen, Vice President of Product Management at LexisNexis.

They share how AI is built in a high-stakes domain where trust and accuracy matter every day. From early NLP systems to modern GenAI, the conversation covers how LexisNexis approaches AI quality, collaboration between product and data science, and building AI fluency across teams.

If you’re building AI products in regulated or high-impact environments, this episode offers a grounded look at what responsible AI looks like in practice.

Read more about LexiNexis: https://hackajob.com/company/lexisnexis?hsLang=en

What would you like us to talk about next?

🔥 Looking for a new role? Create your free hackajob profile and let Archer, your AI advocate in the job market, match you to roles that fit your goals. Apply knowing you're a good fit: https://hackajob.com/talent/sign-up

🔥 Hiring? Archer is hackajob's AI sourcing agent. It finds and qualifies the passive, in-demand talent your team can't reach and delivers them straight into your ATS, while your recruiters make every hiring decision. Book a free demo: https://hackajob.com/employer/book-a-demo

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Buying a home isn't a small decision.

It's often the largest financial choice someone will make. So what does it take to build AI that people can actually trust in that moment?

Kelsey Juraschka, Principal Machine Learning Engineer at Zillow, shares how her team is designing AI systems that support users from search to keys in hand.

We get into:

• What it really means to test non-deterministic systems
• How Zillow approaches agentic AI at scale
• Why evaluation and trust are product requirements, not add-ons
• How AI tools are changing the way engineering teams work
• What kind of mindset actually helps you succeed in AI today

If you're an engineer, product leader, or just curious about how AI works behind the scenes at scale, this one's for you.

Read more about Zillow: https://hackajob.com/company/zillow?hsLang=en

What would you like us to talk about next?

🔥 Looking for a new role? Create your free hackajob profile and let Archer, your AI advocate in the job market, match you to roles that fit your goals. Apply knowing you're a good fit: https://hackajob.com/talent/sign-up

🔥 Hiring? Archer is hackajob's AI sourcing agent. It finds and qualifies the passive, in-demand talent your team can't reach and delivers them straight into your ATS, while your recruiters make every hiring decision. Book a free demo: https://hackajob.com/employer/book-a-demo

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Elizabeth Ferrao splits her time between product research and launching new products at C Spire. She started in engineering, moved into product, and now spends her days turning real customer conversations into ideas that actually matter.

In this episode, we get into:

✨ Why fast prototyping means nothing if you’re solving the wrong problem
🤖 The gap between what AI can automate and what only humans can understand
🔍 How continuous discovery actually works in practice
🎙️ Why hearing a customer’s voice beats any AI summary
🧩 What product teams get wrong about research, insight, and context
🤝 How engineering and product can work together without slowing each other down

If you build products, lead teams, work in engineering, or just want to get better at understanding people, this one’s worth your time.

🎧 Listen, learn, and subscribe for more conversations with the people shaping how tech gets built.

What would you like us to talk about next?

🔥 Looking for a new role? Create your free hackajob profile and let Archer, your AI advocate in the job market, match you to roles that fit your goals. Apply knowing you're a good fit: https://hackajob.com/talent/sign-up

🔥 Hiring? Archer is hackajob's AI sourcing agent. It finds and qualifies the passive, in-demand talent your team can't reach and delivers them straight into your ATS, while your recruiters make every hiring decision. Book a free demo: https://hackajob.com/employer/book-a-demo

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