What does it take to build HR technology that delivers real business results?
Four HR tech product leaders explain how they turn customer ideas into product features, use AI to shorten feedback cycles from months to days, and apply AI in talent processes such as job architecture, skills data, and reporting. Guests are @Haris Ikram (CandorIQ), @Dara Brenner (Employ), @Linda Ginac (TalentGuard), and @Arnaud Grunwald (ClearCo).
They also cover the risks of HR teams vibe coding their own tools, how MCP and headless HR tech change who needs to learn the software, and where the industry is heading: AI-native services, shared data across customers, and governance for AI agents.
Key Takeaways
HR technology only works when the data going in is clean. Bad data multiplies when you add AI.
Good product teams solve the underlying business problem. They don’t just build the feature a customer asks for.
AI can pull themes out of sales and customer success calls, which gives product teams feedback that customers never send directly.
Building prototypes with AI lets customers co-develop features and see changes within days.
AI can build job architectures, keep skills data current, and generate board decks automatically.
With MCP and headless HR tech, hiring managers, interviewers and finance partners can do their part of a workflow in tools they already use.
Vibe coding is fine for personal tools. Shared tools bring risks to data security, compliance and ownership.
Code built inside a company is company property. It should live in the cloud, not on someone’s laptop or personal account.
Don’t shut down employee excitement about AI. Point it at fixing internal processes, and leave the high-risk builds to vendors.
As companies deploy more AI agents, they will need rules for who builds them, how governance works, and who approves them.
Timestamps
00:01 What makes HR technology work
00:05 Turning customer ideas into product features
00:07 How AI shrinks the product feedback cycle
00:09 How employers can become product partners
00:12 AI use cases in talent processes
00:15 MCP and headless HR technology
00:19 The risks of vibe coding HR tools
00:26 Compliance, sensitive data, and build vs. buy
00:32 AI-native services and shared data across customers
00:38 Why AI agents need governance
Keywords
HR technology, AI in HR, HR tech product development, vibe coding risks, MCP, headless HR tech, AI agents, HR data quality, change management, AI governance
Connect with the guests from this episode:
Haris Ikram, CandorIQ
Linda Ginac, TalentGuard
Dara Brenner, Employ
Arnaud Grunwald, ClearCo
