#4 - Performance Reviews That Don’t Drain You, Offer Letter Analyser and so much more

Oh isn’t it nice to have the sun back?! For the UK folks, I hope you’re enjoying it as much as I have, mixing time spent at my computer 🏗️ 👷🏻‍♂️ with some very nice walks on the beach, the joys of living on the seafront - if you’re ever in Whitstable, hit me up!

However, enough bragging about sunsets, because you don’t have the time for that…

That’s pretty much the focus for this week - how can I save you time, money and effort in your work!

This week I will cover:

Deep Dive - A challenge from one of our community on improving performance reviews, in terms of quality, time spent assessing and creating reviews, calibrating the team and connecting to forward actions.

Quick Win - A guide and research backed checklist to identify, assess and resolve performance issues before they cause deeper problems.

Product Updates - Know Your Offer - a comp, equity, legals analysis tool for candidates to use to negotiate better outcomes.

News - Where to start? The landscape is changing daily, but i have a few specific areas for you

Who Am I?

Thanks to Luke O’Mahoney for sending so many new people my way! The king of People Ops as a Product always puts out great things himself - check him out.

I’m Matt Bradburn, I’m obsessed with:

1. Helping companies design ways to scale instead of growing by default. According to Google, I coined the phrase “People Debt” back in 2018 ❤️

2. Up-skilling People Ops teams AI capabilities - Course live on Maven - discount for readers - HERE, or join my 🆓 30 min session next Tuesday HERE if unsure - get in touch if you would like me to work more directly with your team.

3. Delivering a new way of consulting, (Still working on name for this) using me and AI to drive change in organisation design, progression and levelling, comp and reward and manager development, using my skills from running People Collective - 7 years, 150 startups and scaleups aided, it’s what I’m known for but now better 💪

Get in touch if you have a challenge with any of these - [email protected] 

My focus: Combining the People with the Robot - it’s the best way!

PS - Work on site taking longer than expected as I will now have sections for all my content on processes, as well as all the free tools I create, so thats fun!

🎯 Deep Dive of the Week

Sophie Kinloch dropped me a note that hit home this last week:

Sound familiar?

• If you’re running People Ops solo at a startup—like Sophie is at FlashPack—reviews can feel like a soul-sucking marathon.

• Managers burn out, People Ops gets buried, and employees get feedback that’s meh at best.

• Worse, it’s hard to show leadership how this ties to business goals—like hitting revenue targets or keeping customers happy.

• Let’s fix that: less time writing and calibrating, more time on meaningful growth plans, with a dash of commercial impact to make you look great…

Let’s break down the pain points:

1. Writing Overload: Managers can spend 5+ hours per person crafting reviews—stressing over tone, piling on examples, and fitting feedback into frameworks with 10 competencies. It’s exhausting and pulls them from real work.

2. Calibration Chaos: People Ops spends 10+ hours per team sifting through feedback to align scores and spot inconsistencies (one manager’s all 5s, another’s all 3s). Meanwhile, they’re not connecting this to what drives the business—like how a skill gap slowed a product launch.

3. Weak Next Steps: Reviews often skip the “so what?”—like how to prep someone for a promotion or fix a behaviour that’s quietly hurting team output (or even revenue).

The AI Solution: Practical Hacks with Precision AI Prompts

We’re using free AI tools (ChatGPT, Claude, Gemini) to streamline reviews and tie them to outcomes—like better team performance or happier customers. I’ve structured each prompt using a proven framework to ensure you get clear, actionable results every time.

Now, as I’m going to work with Sophie directly on this, I have used another company which I came up with as an example, called “GrowEasy”

Next week - you’ll get part 2 of this, where I build an MVP to solve this ever present challenge 💪

Hack 1: Summarise Feedback Like a Pro

AI can take raw feedback—peer comments, self-reviews, whatever—and boil it down to the good stuff, while highlighting what impacts your goals. For GrowEasy, aiming to cut customer churn by 15%, AI can flag who’s helping or hurting that target.

• How It Works: Paste feedback into a free AI tool with a structured prompt that ensures concise, goal-focused summaries.

• Tooling: Claude’s free version works great. Here’s the prompt:

**Goal:** I want a concise summary of an employee’s feedback that highlights their impact on a specific business goal.  
**Return Format:** Return a summary in 2 sentences:  
1. Highlight the employee’s key strengths and areas for improvement.  
2. Note their impact (positive, negative, or mixed) on the specified goal.  
**Warnings:** Be careful to base the summary only on the provided feedback, avoid assumptions, and ensure the tone is neutral and professional.  
**Context Dump:** For context: I’m an HR leader at a 100-person SaaS startup called GrowEasy. Our goal is to reduce customer churn by 15% this quarter. The employee is part of the customer success team, and this feedback comes from peers and their manager during a monthly review cycle.  
**Prompt:** Summarise this feedback [insert feedback, e.g., “Sophie is great at building client relationships but often delays escalations, which frustrates the team”] into 2 sentences. Highlight strengths and areas for improvement, and note the impact on reducing customer churn by 15%.

Hack 2: Spot Patterns with a “Focus Finder” for Calibration

Calibration doesn’t have to mean endless reading. AI can scan feedback for tone and patterns—like who’s driving or derailing your goals—so you can focus on what matters most during calibration.

• How It Works: AI analyses feedback sentiment and impact, giving you a quick snapshot to guide discussions.

• Tooling: Use Claude’s free tier with this prompt:

**Goal:** I want to analyse an employee’s feedback to understand the sentiment throughout peer, personal and my feedback and impact on a business goal, identifying key themes for calibration.  
**Return Format:** Return an analysis in 3 parts:  
1. Sentiment (Positive, Negative, Mixed)  
2. Impact on Goal (High, Medium, Low)  
3. Key Themes (list 2-3 recurring themes in the feedback)  
**Warnings:** Ensure the analysis is based solely on the provided feedback, avoid overgeneralising, and focus on themes relevant to the goal.  
**Context Dump:** For context: I’m an HR leader at a 100-person SaaS startup, GrowEasy. We’re aiming to reduce customer churn by 15%. This feedback is from a customer success team member, collected during a monthly review. I’ll use this to calibrate with managers.  
**Prompt:** Analyse this feedback [insert feedback, e.g., “Sophie builds strong client trust but delays escalations”] for sentiment (Positive, Negative, Mixed), impact on our goal to reduce churn by 15% (High, Medium, Low), and list 2-3 key themes.

Hack 3: Forward Actions > Past Performance

AI can suggest next steps—like skills to build or behaviours to tweak—that support employee growth and business outcomes, giving managers clear, data-backed talking points. In particular, if you have a clear progression framework, you can build this into the prompting.

• How It Works: Feed AI your feedback, progression framework, and goal to get targeted growth suggestions.

• Tooling: Claude can handle this. Here’s the prompt:

**Goal:** I want actionable next steps for an employee based on their feedback, aligned with our progression framework and business goals.  
**Return Format:** Return 2-3 next steps in bullet points:  
- Each step should include a skill or behavior to improve and a practical action (e.g., “Upskill in X – try Y”).  
- Note how each step supports the business goal.  
**Warnings:** Ensure suggestions are realistic for a startup environment, avoid overly complex actions, and base them only on the provided data.  
**Context Dump:** For context: I’m a manager at a 100-person SaaS startup, GrowEasy. Our goal is currently to reduce customer churn by 15%. The employee is on the customer success team, and we use a 5-level progression framework where Level 3 includes skills like “proactive outreach.” This feedback is from a monthly review.  
**Prompt:** Based on this feedback [insert feedback, e.g., “Sophie excels at client trust but delays escalations”], our progression framework [Level 3: proactive outreach], and goal to reduce churn by 15%, suggest 2-3 next steps for the employee to improve, noting how each supports the goal.

Implementation: Making It Work for GrowEasy

Here’s how GrowEasy—a 100-person SaaS startup with feedback in Sheets, a 5-level progression framework, and goals like cutting churn by 15%—can pull this off using free AI tools. At a glance:

Step 1: Gather Feedback and Goals

GrowEasy’s got feedback from peers, herself and managers, with phrases like “Sophie’s amazing with clients but slow on escalations sometimes and doesn’t always intervene fast enough.” HR adds a goal: “Cut churn by 15%.” Dump feedback into a doc or Sheet. Or download from Lattice, Leapsome etc into a sheet.

• Time: 10 mins for a 10-person team

• Who: People Ops

Step 2: Summarise with a Purpose

Send the feedback by team to the Managers from peers and self feedback.
Manager then pastes Sophie’s feedback into Claude using the prompt from Hack 1:

**Goal:** I want a concise summary of an employee’s feedback that highlights their impact on a specific business goal.  
**Return Format:** Return a summary in 2 sentences:  
1. Highlight the employee’s key strengths and areas for improvement.  
2. Note their impact (positive, negative, or mixed) on the specified goal.  
**Warnings:** Be careful to base the summary only on the provided feedback, avoid assumptions, and ensure the tone is neutral and professional.  
**Context Dump:** For context: I’m an HR leader at a 100-person SaaS startup called GrowEasy. Our goal is to reduce customer churn by 15% this quarter. The employee is part of the customer success team, and this feedback comes from peers and their manager during a monthly review cycle.  
**Prompt:** Summarise this feedback [“Sophie is great at building client relationships but often delays escalations, which frustrates the team”] into 2 sentences. Highlight strengths and areas for improvement, and note the impact on reducing customer churn by 15%.

Output: “Sophie excels at building client trust, a win for retention. Her slow escalations could risk churn if unresolved, potentially undermining our 15% reduction goal.”

They do this for everyone on their team, then collate.

• Time: 20 mins for 10 folks—way better than 2 hours each.

Step 3: Find Focus Areas for Calibration

Managers then run the summaries through Claude using the prompt from Hack 2 and send it back to you:

**Goal:** I want to analyse an employee’s feedback to understand their sentiment and impact on a business goal, identifying key themes for calibration.  
**Return Format:** Return an analysis in 3 parts:  
1. Sentiment (Positive, Negative, Mixed)  
2. Impact on Goal (High, Medium, Low)  
3. Key Themes (list 2-3 recurring themes in the feedback)  
**Warnings:** Ensure the analysis is based solely on the provided feedback, avoid overgeneralising, and focus on themes relevant to the goal.  
**Context Dump:** For context: I’m an HR leader at a 100-person SaaS startup, GrowEasy. We’re aiming to reduce customer churn by 15%. This feedback is from a customer success team member, collected during a monthly review. I’ll use this to calibrate with managers.  
**Prompt:** Analyse this feedback [“Sophie excels at building client trust but delays escalations”] for sentiment (Positive, Negative, Mixed), impact on our goal to reduce churn by 15% (High, Medium, Low), and list 2-3 key themes.

Output: “Sentiment: Mixed. Impact: Medium (strong trust-building, but delays risk churn). Themes: Client relationships, escalation delays.” Compile in a Sheet—highlight high-impact folks for calibration chats.

• Time: 20 mins. Now you’ve got a cheat sheet that shows People Ops value in exec calibration.

Step 4: Suggest Growth That Moves the Needle

Managers use Claude with the prompt from Hack 3 then work with People Ops to refine:

**Goal:** I want actionable next steps for an employee based on their feedback, aligned with our progression framework and business goal.  
**Return Format:** Return 2-3 next steps in bullet points:  
- Each step should include a skill or behavior to improve and a practical action (e.g., “Upskill in X – try Y”).  
- Note how each step supports the business goal.  
**Warnings:** Ensure suggestions are realistic for a startup environment, avoid overly complex actions, and base them only on the provided data.  
**Context Dump:** For context: I’m an HR leader at a 100-person SaaS startup, GrowEasy. Our goal is to reduce customer churn by 15%. The employee is on the customer success team, and we use a 5-level progression framework where Level 3 includes skills like “proactive outreach.” This feedback is from a monthly review.  
**Prompt:** Based on this feedback [“Sophie excels at client trust but delays escalations”], our progression framework [Level 3: proactive outreach], and goal to reduce churn by 15%, suggest 2-3 next steps for the employee to improve, noting how each supports the goal.

Output:

• Upskill in escalation triage (Level 3) – Schedule a 1-hour training with a senior team member; faster escalations reduce churn risk.

• Set daily ticket review habit – Spend 15 mins each morning prioritising tickets; ensures timely responses, supporting the 15% churn goal.

• Practice proactive outreach – Reach out to 2 clients weekly to check in; strengthens relationships, directly aiding churn reduction.

• Managers get clear next steps, and you can whisper to the CFO, “This could save us €50k in churn.”

• Time: 20 mins for their team 🔥

Takeaway: Start Small, Spark Big Change

I actually used this a title for a first blog back in 2016. Little data sparks big changes, and it still applies today.

Here’s your 5-minute challenge: Grab one employee’s feedback and one goal (e.g., “Cut churn by 5%”). Paste into ChatGPT with the summary prompt from Hack 1. See how it shifts your perspective.

THEN: Stay tuned next week for how I take this and build into a small app

💡 Quick Win of the Week

Since we’re on the theme of performance, nothing hits your revenue per employee metric than a manager not intervening quick enough with underperformers. This doesn’t mean the interventions should not be handled with care and kindness, but sometimes managers miss the early signs.

Let’s fix that with my quick guide:

LINK TO THE PAGE HERE

🧠 Product Updates

Know Your Offer!

Back in 2021, I wanted to create a comp tool like Figures or Ravio, in fact I did, until my cofounders ran off with the code base and IP… Urgh, people 🙄

One way I wanted to build this, was ground up growth - help people know what they should be paid, forcing companies hands a lil bit.

So this last week I built an extension of this idea - how can you know whats in your contract and if its good?

• Salary - does it benchmark well for level, location, role type etc.

• Equity - is the level good? Are the clauses reasonable? Cliff, vesting period, exercise period, single or double trigger etc.

• Legals - what other potential nasties are in there?

• Whats missing - compared to other offers.

• How should I negotiate - create an email reply based on the insights and leverage I have!

Within 2 hours I had an MVP, using my knowledge, content and deep insights and guidance from Grok.

Within 6 I had finished this using Lovable, with a bunch of useful feedback:

The power of these tools is incredible, and the speed you can operate with amazing.

In fact I had someone ask if they could have me build a custom MVP of this for their recruitment company, so who knows, maybe I have a future development career ahead of me 😅

Check it out here:

https://know-your-offer.lovable.app/ 

Pulse App

I’m still behind on this one - adding to the pile for this coming week - promise you all an MVP next week:

📰 The news in AI for People Ops this week

Jeff Morris, a highly respected early stage investor put this out last night.

Why does it matter: The metric of Revenue Per Employee (or ideally profit per employee) is becoming far more critical in EVERY business. I have been saying it should be for years, and finally folks are using it 💪. You are in an ideal place to track it, and also map it against other people data. A very valuable position to be in.

What does this have to do with AI? Well, you’re seeing a lot of companies hiring far less people, but those people are becoming far more efficient… That would be the impact of AI.

Just look at what lovable have achieved:

• $0-$17,000,000 ARR in 3 months 🤯

• Team size: 45

The era of exceptional small teams is here… The role of People Ops is to enable, facilitate and create space for high performance and insane margins.

What Is an AI Agent and What Does This Mean for People Ops?

An AI agent is a smart software system that can act autonomously to complete tasks, make decisions, or assist users—think of it as a virtual assistant on steroids, capable of learning, reasoning, and interacting with data in real time.

You’re also going to hear about them… A LOT

For example, an AI agent might schedule meetings, analyze employee feedback, or even predict turnover risks, all without you lifting a finger. Here’s what this means for People Ops in startups and scale-ups:

• Automate the Boring Stuff: AI agents can handle repetitive tasks like scheduling 1:1s, sending reminders for feedback, or pulling data for reports—saving you hours each week to focus on strategic work like culture-building.

• Proactive Insights for Managers: Imagine an AI agent that monitors team engagement (e.g., Slack activity, survey responses) and alerts managers to potential issues, like a dip in morale, before they escalate. This could help you catch underperformance early, as we discussed in our report.

• Personalised Employee Support at Scale: AI agents can deliver tailored growth plans or learning resources to each employee based on their role and feedback (e.g., “Sophie, here’s a 15-min course on escalation triage”). This makes development feel personal, even in a growing startup.

It’s an insane time we live in people!

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