Table of Contents
Where did you go?
Hey folks,
Sorry it’s been a little while, between getting very busy with both people ops projects for clients and AI automation work + balancing time with kids + a healthy dose of imposter syndrome (why would people want to read what I have to say??) I stopped.
But, having had some good rest and recuperation I’m back and it’s kind of crazy what has and hasn’t changed in that time.
We've seen the core model builders make big releases - OpenAI dropped ChatGPT 5 with thinking, Anthropic brought Claude Sonnet 4.5 and Perplexity dropped labs - more on that later.
But as per my post this morning on Linkedin, the FUNDAMENTALS in People Ops rarely change, nor do I think they will extensively over the coming years.
This is coming from both my work within organisations and my forward looking fascination with AI.
Do I think it’s important to keep learning - absolutely - but to do so one a few fronts:
Contextual knowledge of the People Ops space is more critical than ever. It allows you to write better prompts, solve problems more effectively with AI, understand your workflows to be automated and know the strategic levers to be pulled. This applies to everyone at every level.
Tooling knowledge of the AI space in certain roles. But it changes by level and tooling. Should a CPO know how to build in n8n? Probably not, but at the same time, they have to get confident in assessing the output, so they need to know enough. Should a junior or mid level people person? ABSOLUTELY - because right now automation provides direct ROI and can elevate your career.
Systems thinking in senior roles - and building in junior. The CPO has to have a strategic systems thinking view and be able to get deep and ask the right questions where necessary, or build reports with accuracy - so their prompt chaining and critical thinking work has to be exceptional with the tools available. Junior folks need to learn how everything fits.
So yes, since I’ve been away, I’ve had a rethink and going to continue to focus my work on strategic people ops support, then AI education and automation building but separately.
Onwards to this weeks practicals⚡️💪
So, this week, I’m going to focus on:
A deep dive into how to build a simple n8n workflow to connect a CustomGPT to a workflow
Sharing my roadmapping guide for folks who want to start thinking about where AI is useful within their plans
A short walkthrough of the Comet browser from Perplexity and what you can use it for.
Who Am I?
For new subscribers, I’m Matt Bradburn. I was VP People at Peakon, built and sold the DBR community to Talentful, built and sold People Collective to Scede and now combing People Ops expertise with AI to solve my clients challenges.
Connect with me on Linkedin here
Hire me to run change management and People Ops projects like progression, levelling, comp and reward here
Hire me to get you back 200+ hours of time a year with automations here
🎯 Deep Dive of the Week
The problem:
Creating Job Descriptions Slows Down Hiring Launches
Hiring managers spend 2 hours crafting each job description from scratch.
HR teams spend another 30-60 minutes formatting, reviewing, and distributing them. The back-and-forth creates bottlenecks that delay critical hires by 3-7 days per role.
Your time = Your biggest cost. At £100/hour (loaded cost), every job description costs you £350+ in lost productivity.
The solution:
CustomGPT - AI asks hiring managers just 2 questions at a time, building complete job specs through natural conversation
Actions function - sends to n8n in a format it understands.
Auto Organisation - Folders / docs created in the right folder and naming convention every time.
Auto-Formatting - Instantly creates professional, branded documents with consistent structure.
Automatically notifies your team via Slack with ready-to-use documents
Works with your existing Google Workspace and communication tools.
ROI That Speaks for Itself
Time Savings
Before: 3-5 hours per job description (hiring manager + HR time)
After: 5 minutes of guided conversation
Time Saved: 95% reduction in job description creation time
Cost Impact
10 hires/month: Save £42,000+ annually in productivity costs
25 hires/month: Save £105,000+ annually
50+ hires/month: Save £210,000+ annually
Speed to Market
Faster Job Postings: 3-7 days faster time-to-post
Improved Quality: Consistent, complete job specs every time
Reduced Revisions: AI ensures all key elements are captured upfront
Why Human-AI Collaboration Wins
Human Intelligence: Hiring managers provide context, priorities, and nuanced requirements that only they understand
AI Efficiency: Handles formatting, structure, and distribution instantly - no manual work
Quality Control: Combines human insight with AI consistency for superior outcomes
Want some other ways to use this? Drop me a message and happy to discuss!
🤯 PS - I created all of the above in under 60 minutes….
I want to help as many folks in the space build their skills as much as possible over the next year.
I now have two course options for you:
1 - For those looking to focus on workflows, roadmapping, prompt chains and just learning about expanding beyond chatgpt - 4 week, $450 / £335
2 - For those looking to focus on automations, n8n and reducing time spent on manual work - 7 weeks, $900 / £670 (although, for the first 10 people to sign up from here, $300 off with code Waitlist?) - LINK
💡 Quick Win of the Week
If you’re a CHRO, you’re going through a lot right now.
So i’ve built you a guide to help on the strategic aspects of AI enablement.
It’s a big deep dive - but I focus on the human first, before going anywhere near the tooling…
✅ Anchor this
Behaviours drive strategy and tools. If you cannot see the behaviour, you cannot scale the capability.
Core behaviours
Context first Start with the business model, unit economics, and risk. Translate People decisions into revenue, margin, cash, and risk language.
Commercial creativity Generate options that improve both employee experience and EBIT. Use constraints as a design brief.
Critical thinking Interrogate assumptions. Separate fact, opinion, and inference. Ask what evidence would change your mind.
Relentless clarity Make the next step obvious. Write crisp one-pagers, not vague strategy decks.
Speed with safety Ship in small slices, capture learning, and add controls. No big-bang transformations.
Coaching and enablement Teach leaders to think with AI, not just use AI. Model good prompts, good questions, and good judgement.
Transparency Share what is automated, why, and how it is monitored. Employees should never guess.
Outcomes to aim for
Faster, higher quality decisions in hiring, org design, performance, and compensation.
A safer, more capable organisation that learns in public and improves every week.
A People function that speaks in commercial outcomes, not activity.
📰 News That Matters for HR
I’m actually just posting a couple things I find interesting this week, as none of you click my news articles 🤪
1. Perplexity Comet has changed my life. Download it, use it, come and share some use cases with others in the comments.
Perplexity Comet is scary GOOD.
This agentic browser connects to your apps and does everything you want autonomously.
10 powerful use cases👇:
1. Summarize and provide me all the links of this video
— #Alvaro Cintas (#@dr_cintas)
4:44 PM • Jul 16, 2025
Why the human side is the real reason AI transformations go wrong
We just wrapped up an 8-week AI Transformation Project with a 350-person Australian healthcare company.
The tech was the easy part.
The enterprise chaos & “people stuff” was way harder.
So here are 7 lessons from the trenches on how to work effectively with an enterprise:
— #Liam Ottley (#@liamottley_)
7:04 PM • Oct 6, 2025
👋 Let's Connect!
Finding this valuable? There's more where this came from!
✨ Share this newsletter with your HR network
🔗 Connect with me on LinkedIn: https://www.linkedin.com/in/mattbradburn/
💌 Have questions? Just hit reply!
Remember: AI in HR doesn't have to be complicated. Let's figure it out together, one practical step at a time.
