Si and Neil hit episode ten and do what any good engineering manager would do: run a retro. They look back at the highlights, the episodes that didn't quite land, the feedback that stuck, and what they're committing to next season. It's a little self-indulgent, and they know it. But if you've ever reflected on a project and come away feeling better about the journey than the destination, this one's for you.

CHAPTERS

00:00 - Welcome to the season finale 07:16 - The numbers: who's actually listening? 13:19 - Favourite episodes and honest highlights 15:48 - The communities episode and why it hit differently 19:00 - Contradictions, side projects, and shifting perspectives 23:04 - How the podcast itself evolved over the season 27:00 - On feedback: what to take, what to leave 35:30 - Themes across the season (with a little help from an LLM) 41:26 - Are we doing another season? Yes, but here's the deal 43:42 - A future retrospective: what does a successful next season look like?

LINKS

Ministry of Testing - https://www.ministryoftesting.com/ Six Thinking Hats - https://www.debonogroup.com/services/core-programs/six-thinking-hats/ DORA metrics - https://dora.dev/ PETALS - https://petals.team/ feedback@managingengineers.net

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Si and Neil compare notes on one of the most underestimated challenges in tech leadership: hiring well. From writing the job spec to navigating AI in the interview room, this episode covers the full journey, with plenty of honest opinions, personal stories and hard-won lessons along the way.

• Writing the Job Spec (03:16) - Where hiring goes wrong before it's even started. The laundry list problem, gender-encoded language, and why a backfill doesn't have to be like-for-like.
• Screening CVs and the Network Problem (17:43) - AI-generated applications are flooding inboxes. Is the CV even fit for purpose anymore, and what does leaning on your network really cost you?
• Side Projects and What CVs Can't Show (25:06) - Why both hosts have shifted away from using GitHub profiles and portfolios as a hiring signal, and what that says about privilege in the process.
• The Interview Process (29:21) - Take-home tests, live pairing exercises and the heuristic that ties it together: the interview should look like the work.
• Culture Fit vs. Culture Add (36:23) - Stop hiring a friend group. Why diverse thinking beats a room full of people who all get on brilliantly outside of work.
• Technical Assessment in the Age of AI (43:19) - When anyone can AI their way through a coding test, what are you actually testing for? Si's approach: hand them an LLM and watch how they use it.
• The Arms Race (49:32) - Candidates using AI to game hiring, companies using AI to screen it out. And a word on privilege: not everyone can afford a Claude Pro subscription.

Connect with us

Got thoughts on hiring? We'd love to hear them.

• Email: feedback@managingengineers.net
• Si on LinkedIn https://www.linkedin.com/in/sijobling/
• Neil on LinkedIn https://www.linkedin.com/in/neil-younger/

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It took them eight episodes, but Si and Neil finally tackle AI. No future predictions (well, almost), no hot takes, just two engineering managers sharing what they're actually doing with these tools, what's surprised them, and what still makes them nervous.

They cover using LLMs as thinking partners, the difference between AI that writes code and AI that helps you engineer better, agentic tools and what happens when you give them real access, and why good engineering practices might matter more now, not less. Oh, and they do make some predictions at the end. They'll probably be wrong. That's kind of the point.

Timestamped to April 2026. This will be outdated by the time you listen to it.

CHAPTERS

• 00:00 - Illness, delays and finally talking about AI
• 04:32 - Framing it: LLMs vs AI as a broader term
• 06:09 - How Si and Neil are using AI day to day
• 12:41 - AI baked into everything: Copilot, Confluence and the Microsoft rebrand
• 16:24 - The accelerant problem: AI amplifies what's already there
• 19:38 - Industry noise, AI fatigue and working out the real value
• 30:06 - Agentic AI: what it is and why it changes things
• 34:01 - What they've learned from using LLMs (tips for getting started)
• 50:07 - Predictions: AI in engineering this time next year
• 53:32 - The future of EMs, QA and small teams

USEFUL LINKS

Dave Farley - Modern Software Engineering (Continuous Delivery): https://www.youtube.com/c/ContinuousDelivery

Microsoft Copilot: https://copilot.microsoft.com

Cursor (AI code editor): https://www.cursor.com

GitHub Copilot: https://github.com/features/copilot

Claude (Anthropic): https://claude.ai

OpenClaw (agentic AI tool): https://openclau.ai

Notion AI: https://www.notion.com/product/ai

CONNECT WITH US

Si Jobling - https://www.linkedin.com/in/sijobling/

Neil Younger - https://www.linkedin.com/in/neil-younger/

Listen wherever you get your podcasts.

CREDITS

Produced by Unstyled Studios.

Artwork by Si.

Edited in Descript.

Hosted on Pinecast.

Support Managing Engineers by contributing to their tip jar: https://tips.pinecast.com/jar/managingengineers

Find out more at http://podcast.managingengineers.net

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