Engineers can't sign their name to a guess.

That's why generative AI stalled at the door of the control room.

This episode is about what got through instead.

Andy Webster is Senior Director for Digital and AI at KBR's Sustainable Technology Solutions division. His team spent the last three years going from an organisation curious about everything to one focused on a handful of bets: culling projects on a six-week clock, then backing physics-based AI hard enough to invest in it.

His argument: language models predict the next word, physics-based AI predicts the next state of your asset, and that difference is what earns an engineer's trust.

We get into:

- The "difficult, if not traumatic" project cull — and why stopping things created the velocity

- The six-week rule: every experiment defaults to stop unless it earns another six

- Physics-based AI explained properly: prediction constrained by gravity, thermodynamics, reality

- Why KBR went from reseller instinct to investor in Applied Computing, and what an ecosystem play looks like in engineering

- "What if your plant could think?" Talking to a physical asset like a colleague

- Souls on steam trains: what the history of tools says about the fear of this one

- Will professional bodies end up approving the data sets we trust? The next fight over "data is the new oil"

- Andy's hard-way lesson: the person saying no is as smart as you

Connect with Andy: linkedin.com/in/andywebster1

Connect with Helen: linkedin.com/in/helen-dawson

Sign up to The Hard Part newsletter: helen-dawson.kit.com/the-hard-part

AI Confidence Snapshot (4 mins): scorecard.helen-dawson.com

Everyone tells you to start your AI journey with a use case. I'm going to tell you to start with a notebook, a coffee, and a darkened room.
A solo episode: the two questions I give leaders to kick-start their AI thinking. No tools, no vendors, no pilots. Twenty minutes of honest thinking before you spend a penny.
We get into:
Question one: what's getting in the way right now — for you, your peers, and your team? Be honest. That list is your leadership to-do list.
Why "no use case is too small" is bad advice: AI should move the needle on your business, not do your conditional formatting
Question two: wouldn't it be cool if? Start with a problem you care about solving, and think six months ahead of today's capability
Why the quick win is a trap, and what to aim for instead: a shortcut to alignment on the big ambition
AI is an ingredient, it's not a meal
Connect with Helen: linkedin.com/in/helen-dawson
The Hard Part newsletter: helen-dawson.kit.com/the-hard-part
AI Confidence Snapshot (4 mins): scorecard.helen-dawson.com

Nuclear is about as unforgiving as engineering gets. Safety critical. Heavily regulated. So why does Graham Openshaw think it should be innovating faster, not slower?
Graham is Operations Director, Digital at Assystem, the second-largest independent nuclear consultancy in the world. His argument: proper governance and sponsorship aren't the brakes. Done well, they're what lets you manage riskand move faster.
We get into:

• The myth that people resist change, and why the frustration sits in how organisations are wired, not in the individuals
• The power of no: how every approval step hands somebody a veto they learn to enjoy, and how to make no the expensive answer
• Why a pickup truck explains everything wrong with corporate procurement
• There is no digital strategy. There is just strategy. And often the missing piece of the puzzle is defining outcomes
• Technical debt is compromise with bad branding
• Why internal projects deserve the same rigour as a client tender
• AI as a lever for quality improvement, because the expert becomes the checker, not the author
• Graham's hard-learned lesson: thinking is working
  Connect with Graham: linkedin.com/in/grahamopenshaw
  Connect with Helen: linkedin.com/in/helen-dawson
  Sign up to The Hard Part newsletter: helen-dawson.kit.com/the-hard-part
  

You probably sat through it aged 12: a history lesson about sources. Who wrote this, why and what are they not telling you. Turns out that lesson is super useful for working with AI.

In this short episode, Helen Dawson ( child of a history teacher) draws the line straight from GCSE source analysis to how large language models actually work. Generative AI has been fed a vast, partial, skewed corpus of everything ever written — and it answers by predicting the next word. Which means it's never truly right. It's only ever plausibly wrong, and sometimes that happens to line up with the truth. There's no signpost telling you which.

Helen makes the case that critical thinking is the number one skill of our time, and walks through the questions that protect you: Is this even the right tool for the job? What was this thing trained on? Did the way I asked the question seed the answer I got? And why footnotes, however much they made you cry during your degree, still matter. (If you weren't an Arts student, just trust us on this)

Guardrails have improved. They are not hard limits. Check your sources.

Key decisions on AI for government and business leaders.

In this episode, Helen Dawson explores the critical considerations for integrating AI into government and business. She emphasizes that AI should be viewed as an ingredient within broader solutions rather than a standalone fix, emphasizing outcomes over technology buzzwords.Main topics:

• The three-layered framework of AI: infrastructure, models, and functionality
• The importance of using AI to improve government outcomes and solving hard challenges
• Risks of vendor capture and the 'siege' dynamic in critical infrastructure contracts
• Edge cases and the unique challenges in public sector AI deployment
• The notion of AI as an ingredient versus a meal – focusing on real-world impact
• Ethical concerns: fairness, bias, and the distribution of gains in AI-powered society
• Strategic decisions governments face, exemplified by the NHS Palantir contract
• The importance of protecting supply chains and avoiding vendor lock-in

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Summary

Helen Dawson and Sandie Essemann discuss how to craft sales proposals that resonate with buyers by focusing on the buyer's needs, using industry language, and creating compelling storytelling. They share practical tips to improve proposal effectiveness and build stronger client relationships.

Key Topics

1. Upgrading the user experience, not the technology
2. Using industry-specific language and client language
3. Pinpointing the client's core problem
4. Visualizing what good looks like for the client
5. Creating memorable sound bites for pitches
6. Building early value into client relationships
7. Giving your company a human face in proposals

Keywords

sales proposals, B2B sales, proposal tips, industry language, storytelling, client engagement, sales strategy, technology, innovation, SaaS

Contact: Helen Dawson https://www.linkedin.com/in/helen-dawson/

Sign up to Helen's Newsletter: https://helen-dawson.kit.com/the-hard-part

Sandie Essemann https://www.linkedin.com/in/sandieessemann/

Sign up to Sandie' newsletter https://sandie-copy.kit.com/b5fe467b47

The Pope has said the thing that most CEOs are paying consultants to dance around. I talk through the The Vatican's Take on AI, Humanity, and Society from the Magnifica Humanitas.

This episode explores a surprisingly profound Vatican document on artificial intelligence, human dignity, and societal values, highlighting the moral and ethical considerations that are often overlooked in tech discourse.

Main Topics:

• The Vatican's perspective on AI and the common good
• Human limitations, dignity, and the risks of unchecked technological upgrades
• Ethical frameworks for AI governance and data ownership
• The role of work, community, and moral responsibility in an AI-driven future
• The Pope's document as a rallying cry for AI aligned with human and societal good

• Why embracing human limitations is essential to preserve creativity, surprise, and societal cohesion
• The danger of believing AI will fix inherent human weaknesses and the concept of unbounded human upgrading
• The importance of safeguarding human dignity and participatory work
• Practical strategies for leaders to navigate AI ethics, including governance, data ownership, and supply chain issues

Graham Young spent 25 years in big corporate energy: Shell, one of the largest global SAP rollouts ever attempted, decarbonising key accounts across the chemicals sector. Then he made the jump to a smaller, leaner, acquisition-hungry oil and gas company, and discovered that the levers he was used to pulling weren't connected to anything.

In this episode he and Helen Dawson dig into what that transition really teaches you: why systems thinking is becoming a core skill, why being an AI follower beats being a leader, and why steering the ship yourself beats persuading five other people to nudge the wheel

Keywords: Energy, Digital Transformation, M&A, AI, Business Strategy, Change Management, Technology, Leadership, Oil and Gas, Innovation, Harbour Energy

Graham Young on LinkedIn: https://uk.linkedin.com/in/graham-p-young/

Helen on LinkedIn: https://www.linkedin.com/in/helen-dawson/

The Hard Part newsletter: https://helen-dawson.kit.com/the-hard-part

AI Confidence Snapshot (four minutes): https://scorecard.helen-dawson.com

In this episode, Helen Dawson speaks with Lucy Scott Brown about the essentials of effective product management, the evolving role of communication, and the fascinating world of blockchain technology.

Whether you're a seasoned product professional or new to the field, Lucy's insights on teamwork, technical understanding, and innovative applications of blockchain will inspire and educate.

Key Topics:

• The core skills of a great product manager: understanding user needs and effective communication
• Balancing technical and business knowledge, and fostering diverse, collaborative teams
• Building communication skills: from early career experiences to leadership development
• Collaboration with engineering teams: respecting boundaries and mutual respect as key
• Exploring blockchain: how shared ledgers work, beyond cryptocurrency use cases
• Real-world applications of blockchain: anti-counterfeiting, certification verification, and currency stability
• Practical advice for companies exploring blockchain: problem-focused and avoiding hype
• Personal lessons: asking questions early and often, embracing vulnerability in leadership
• The importance of emotional intelligence and diversity in team dynamics

• Lucy Scott Brown’s LinkedIn

Timestamps:00:00 - Introduction to product management and guest Lucy Scott Brown
02:02 - What makes a great product manager?
02:30 - Key skills: understanding user needs and effective communication
03:48 - Balancing knowledge of business vs. technology
05:41 - The role of diversity and teamwork in product success
06:27 - Developing communication skills over time
08:14 - Respectful collaboration with engineering teams
09:22 - Building confidence through support and small wins
10:39 - Decoding blockchain: what it is and how it works
18:36 - Blockchain beyond cryptocurrency: real-life use cases
22:47 - Favorite blockchain applications and industry insights
25:26 - How companies should approach exploring blockchain technology
26:46 - Avoiding tech hype: focus on problem solving over solutions
27:43 - Hard lessons: asking questions and embracing vulnerability
29:20 - Leadership and learning from team diversity
30:44 - Connecting with Lucy for further insights