Fullstack HR

First episode of the new interview series with people who do stuff with AI, not people who talk about AI. Joe Shahmoradian runs talent acquisition for EMEA at Morningstar, and everything in this episode is running in his team today.
In this episode:
How his team cut post-call admin by 75% with AI transcription on screening calls, and why the first tool got killed
Amira, the AI teammate that works like a journalist and turned five-day market intelligence reports into 90-minute video briefings
The AI clone Joe built before paternity leave, and what it did when he prompted it maliciously at 1 AM
Morningstar's playbook for adoption at scale, an AI Academy, a champions community that grew from 5 to nearly 200, and an idea hub with real ownership
What Joe would do in his first 90 days at a company starting from zero, and why governance comes before agents
Why the workforce of the future is humans and agents as teammates, and why the discourse needs more boldness
With Joe Shahmoradian, Director of Talent Acquisition EMEA at Morningstar.
Links mentioned:
Joe Shahmoradian on LinkedIn → https://www.linkedin.com/in/joeshahmoradian/
FullStack HR newsletter → https://fullstackhr.io

Subscribe to the FullStack HR newsletter → https://fullstackhr.io
Claude started watermarking every text it writes. Substack scores your posts for AI. Recorded from the car after two weeks off, this episode is about why both miss the point.
In this episode:
What Anthropic's new invisible watermark does, and what it can't do
How Substack's Pangram scan works, and why it's easy to circumvent
Why the human-versus-AI framing is the wrong test
The pieces I let AI write on its own, and why they tanked
The pieces I wrote alone that got the exact same feedback
My workflow, dictate in the car, let Claude turn it into an article
Why turning off the AI scan reads as shame, and what to do instead
Links mentioned:
How Claude's text watermarking works → https://www.anthropic.com/news/claude-text-watermark
How can I detect AI on Substack → https://support.substack.com/hc/en-us/articles/50891130623508-How-can-I-detect-AI-on-Substack
Pangram → https://www.pangram.com

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A week at Almedalen made one thing obvious. Most leaders shaping how Sweden thinks about AI have only ever touched Copilot or the free ChatGPT, and that single reference point is quietly capping what entire organizations believe AI can do.
In this episode:
Why almost nobody picks their own model, and how a Microsoft license becomes an AI strategy by accident
The screwdriver vs power drill problem. Copilot solves the job, but it sets your expectations far too low
How a single default tool shrinks the whole organization's sense of what AI is capable of
The shadow IT trap, where your best people quietly run Claude or ChatGPT on the side and you lose both security and their hard-won knowledge
Why limiting people to one tool becomes an employer branding problem over time
What the real frontrunners do instead. Securing Copilot, ChatGPT, Claude, and Gemini and letting people choose
The blunt take on IT departments that claim multi-model access is not doable on security grounds

Anthropic just dropped Claude Fable 5, and I've run it through the same test suite he's used on every major model for 2.5 years. The verdict is clear, but the bigger lesson isn't about the model at all.
In this episode:- Why Fable 5 feels like the most human-like model yet, and how it gives honest, direct feedback instead of patting you on the back- The worker scheduling test (30 people, legal requirements, hard constraints) and how Fable 5 handled it- A real client case where Fable 5 reworked a Copilot Studio workshop deck and improved the flow- The Mythos connection, the security guardrails, and why hacking headlines might be part PR- The pricing cliff on June 22. $10 per input token, $50 per output token, and Johannes's plan to pair Opus 4.8 for creation with Fable 5 for evaluation- The real bottleneck. Models are capable, organizations are not, and why experimentation time is the thing HR must fight for- McKinsey's warning that HR risks becoming a sub-department of IT if it doesn't take the driver's seat now
Links mentioned:- McKinsey HR Monitor 2026 → https://www.mckinsey.com/capabilities/people-and-organizational-performance/our-insights/hr-monitor

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Organizations keep telling Johannes Sundlo, the host here, "we've got the basics covered, skip ahead." Then he asks them to show how they use AI, and gets blank stares. This episode is about AI shame, where it comes from, and the one step you can't skip.
In this episode:
AI shame, what it looks like and why it's more common in 2026 than 2025
The pattern behind it. Buyers say "we're proficient, go straight to processes," but the proficiency is a sliver of what the models can do
Why this shows up most in leadership teams, and why leaders who skip the grunt work can't set credible AI expectations for their organization
The missing step. You can't jump to agentic processes before you've done the unglamorous work of learning what the model can do
Educate everyone, including truck drivers without computers, because employees are already getting AI advice on salary and managers in their spare time
Why being practical beats strategic-only thinking in AI adoption right now
Lessons from roughly 110 workshops this winter and spring, and why Johannes is scaling that down