Recruitment & HR

LinkedIn just responded to the bias claims. They think they refuted my research. I believe they just confirmed it. Following the recent discussions on whether the algorithm suppresses women's voices, LinkedIn's Head of Responsible AI and AI Governance, Sakshi Jain, posted a new Engineering Blog post to "clarify" how the feed works (link in comments). I’ve analysed the post. Far from debunking the issue, it inadvertently confirms the exact mechanism of Proxy Bias I identified in my report (link in comments). Here is the breakdown: 1. The blog spends most of its time denying that the algorithm uses "gender" as a variable. And I agree. My report never claimed the code contained if gender == female. That would be Direct Discrimination. I have always argued this is about Indirect Discrimination via proxies. 2. Crucially, the blog explicitly lists the signals they do optimise for: "position," "industry," and "activity." These are the exact proxies my report flagged. -> Industry/Position: Men are historically overrepresented in high-visibility industries (Tech/Finance) and senior roles. Optimising for these signals without a fairness constraint systematically amplifies men. -> Activity: The (now-viral) trend of women rewriting profiles in "male-coded" language (and seeing 3-figure percentage lift) proves that the algorithm’s "activity" signal favours male linguistic patterns ("agentic" vs. "communal"). 3. The blog confirms the algorithm is neutral in intent (it doesn't see gender) but discriminatory in outcome (because it optimises for biased proxies). In the UK, this is the textbook definition of Indirect Discrimination under the Equality Act 2010. In the EU, this is a Systemic Risk under the Digital Services Act (DSA). LinkedIn has proven that they can fix this. Their Recruiter product uses "fairness-aware ranking" to mitigate these exact proxies (likely for AI Act compliance). The question remains: Why is that same fairness framework not being applied to the public feed? 👉 What We Are Doing About It Analysis is important, but action is essential. I am proud to support the new petition, "Calling for Fair Visibility for All on LinkedIn". This isn't just a complaint; it’s a demand for transparency. We are calling for an independent equity audit of the algorithm and a clear mechanism to report unexplained visibility collapse. If you are tired of guessing which "proxy" you tripped over today, join us and sign the petition (link in the comments).

Louder for the people at the back 🎤 Many organisations today seem to have shifted from being institutions that develop great talent to those that primarily seek ready-made talent. This trend overlooks the immense value of individuals who, despite lacking experience, possess a great attitude, commitment, and a team-oriented mindset. These qualities often outweigh the drawbacks of hiring experienced individuals with a fixed and toxic mindset. The best organisations attract talent with their best years ahead of them, focusing on potential rather than past achievements. Let’s be clear this is more about mindset and willingness to learn and unlearn as apposed to age. To realise the incredible potential return, organisations must commit to creating an environment where continuous development is possible. This requires a multi-faceted approach: 1. Robust Training Programmes: Employers should invest in comprehensive training programmes that equip employees with the necessary skills for their roles. This includes on-the-job training, mentorship programmes, online courses, and workshops. 2. Redefining Hiring Criteria: Organisations should revise their hiring criteria to focus more on candidates’ potential and willingness to learn rather than solely on prior experience or formal qualifications. Behavioural interviews, aptitude tests, and probationary periods can help assess a candidate's ability to learn and adapt. 3. Partnerships with Educational Institutions: Companies can collaborate with educational institutions to design curricula that align with industry needs. Apprenticeship programmes, internships, and cooperative education can bridge the gap between academic learning and practical job skills. 4. Lifelong Learning Culture: Encouraging a culture of lifelong learning within organisations is crucial. Employers should provide ongoing education opportunities and support for professional development. This includes continuous skills assessment and access to resources for upskilling and reskilling. 5. Inclusive Recruitment Practices: Employers should implement inclusive recruitment practices that remove biases and barriers. Blind recruitment, diversity quotas, and targeted outreach programmes can help ensure that diverse candidates are given a fair chance. By implementing these measures, organisations can develop a workforce that is adaptable, innovative, and resilient, ensuring sustainable success and growth.

Most people get Reference Checks wrong! Here's how to get them right 👉🏻 Throughout my journey, I've had to make 1000s of hires and often struggled with evaluation through the standard interviewing processes. I read somewhere that ~60% senior hires go wrong even after the most meticulous processes so I wondered how to improve the odds. 🤔 What I discovered is that there's no substitute for spending time with the candidates and conducting ‘unnamed’ ref checks through your own network. But what I also learnt is that not every ref check is the same and you can end up with very different outcomes depending on how it’s done. So, through reading and experience, I came with the best practices that I christened with the acronym "PEARL", and here it is for the FIRST time🔥 P - Promise Reciprocity Busy professionals don't dole out intel freely. So, you must offer to return the favor – something as simple as “If ever you need my help for a ref check or otherwise, I'd be happy to help". A senior leader will immediately see its value & perhaps become more ‘available’ on the call. E - Ensure Confidentiality This is critical, especially in India. Candor is not part of our culture, so assure the referrer that you understand the sensitivity of this call and will keep it 100% confidential. Also that you'd expect the same if they ever choose to call you for a reference. If you still sense some hesitancy, maybe throw an ‘offer’ of a good-faith NDA. Don’t worry, nobody ever takes it up but it makes them less guarded. A - Ask questions that force specificity (close-ended & open-ended) Broad questions like – "How was their work ethic?" “Does she work hard?” - are a complete waste of time. You need to ask 2nd order questions that make it comfortable for the referrer to answer without feeling like they're maligning the candidate. For eg - “How do you think we can help the candidate grow?" is better than "Can you tell me about their weaknesses?” R - Retrieve critical insights Actively listen and probe for specifics. Did the candidate consistently meet deadlines? Why or why not? How did they handle pressure? Did they run towards solving problems or look for directions to carry out? These details paint a picture beyond the resume. L - Learn rehire potential And finally, the golden question – "Are you willing to re-hire or work with the candidate again? Why or why not?" Regardless of what the referrer may have said up to this point, most senior folks will have a hard-time giving you a false or misleading response to this one. This is the true gauge of the candidate’s potential and one I put a lot of weight in. To conclude, thank the referrer for their time, assure confidentiality again and commit to a quid pro quo. This leaves the door open for other ref checks you might wish to do in the future 😏 So, there you have it - A PEARL from my collection🙌🏻 Do comment with something that’s worked for you that I may have missed :) #hiring #startups #leadership

I’ve had 4 legal battles since starting my business. Could I have avoided them? Probably. But to be honest, I didn't have the funds to pay a proper lawyer, or the network of founders to ask the right questions to. I don't want that to happen to you. Here are 5 clauses I put in my contracts that might help you protect your work, your business and most importantly.. your sanity ↓ #1 Non-cancellable, non-refundable contracts. This shouldn’t even be an issue if you qualify your clients properly. BUT if someone signs, onboards, and then ghosts? We still get paid. And so should you 🤗 #2 Immediate or short payment terms Most businesses accept 30-to 90-day payment terms. I don’t. You wouldn’t work for 3 months without pay—so why should your business? Cash flow is your business’s lifeline. Protect it. #3 While we’re on payment terms… Your contract should include: → Interest on late invoices. → A clause that stops work if invoices aren’t cleared. → A guarantee that if a client delays the project, you still get paid. Your time isn’t free! #4 Your IP stays YOURS. Anything we bring into the agreement at Klowt stays ours. Anything we create for you is yours. Simple. I once ran a training session, and the client recorded it—then tried to sell it behind a paywall. Now, our contract states a £10,000 fine per breach. (And for that particular case, per breach = per view. 😅) #5 Don't work with d*ckheads. This isn't a legal clause, more legal... advice? 🤣 If someone is giving you red flags in any way at the beginning of your relationship, do not work with them. This could include but not limited to: - Focusing on immediate ROI. - Cost or discounts being a primary concern. - Pushing for work to kick off before contracts or payments. - Reaching out at inappropriate times - or in inappropriate ways. - Delaying initial payments. Legally binding contracts are a good insurance policy, but they're lengthy and expensive to implement if you actually have to go to court. So the best LEGAL advice I can give you as a 2x founder is, don't work with d*ckheads. And learn from my mistakes. It's a lot cheaper than learning from your own... trust me 😂. Was this helpful? 💜 I write a 2x weekly newsletter for founders and freelancers on topics like this. Join us here: https://lnkd.in/ejDbD94R

ESOPs don’t always work, but when they do its magical 5000 Swiggy employees made around 9000 crores in the IPO Some would have made 100 cr plus Many many more would have made 10 cr plus Life changing money for most people and will enable risk taking and another 100 plus startups from this set If you are evaluating offers from startups with significant ESOP component, this is how you should evaluate it For an employee to make meaningful money through ESOPs, 2 things must happen: - Growth in company value - Employee friendly ESOP policies that ensures employees make money when company grows a) Growth in Company Value This is where employees need to think like investors Just like investors are particularly wary of what valuation they are coming in, entry valuations should matter for employees too ESOPs are allotted basis the current valuation The likelihood of a 10x growth in your ESOPs if you are joining a startup valued at 100 million $ is much higher compared to joining a startup already valued at 5 billion $ A 75 lakh ESOP allotment in a 1000 cr valued org with chances of a 10x growth could be a better offer than 2 cr ESOP allotment at a 20000 cr valued org with lower chances of future growth The second thing to judge is the business model and the likelihood of the business to grow( very important for Seed/Series A/B startups) b) ESOP Policies The startup ecosystem is full of stories where employees didn’t make money despite the company growing and having multiple liquidity events. Swiggy, Zomato are examples of great ESOP policy. Many companies have extremely shitty ones Here are the things that should matter most while evaluating policies: 1. Vesting Schedule: The standard is 25% vesting after every year. Any schedule which has higher vesting towards the later years is a red flag Vesting should never be performance linked If performance is bad, it is management’s responsibility to fire 2. Vesting on Leaving/Startups Exit: If you exit, you should retain all options that has vested If a startup gets acquired before all your options vest, there should be accelerated vesting 3. ESOP Communication: There should always be written communication( preferably through ESOP portal) Verbal communication for ESOPs is a huge red flag 4. Strike Price: Strike Price should be as low as possible( Re 1 ideally). This maximizes the value creation for the employee 5. Holding/Exercise Period: Converting options to shares is a major tax liability exercise. With limited exercise period, it becomes impossible for employees to exercise as it means paying up to 40% real taxes on notional capital gains in an asset class that is not liquid Ideally, holding period should be infinite for vested options, even after exit This enables employees to wait for liquidity events without incurring upfront taxation to be paid out of own pocket

The best founders do one thing brilliantly... Hire. Here’s how we think about finding & attracting A-players for our portfolio companies: Most owners hire like they're running a restaurant. They think more cooks = faster service. Instead, they get a kitchen full of people bumping into each other, burning food, and blaming everyone else. That’s why hiring isn’t a numbers game. You don't need more people. You need the RIGHT people. It’s impossible to build a worthwhile business with mediocre talent. Over the years, we've developed a framework to find, attract, and close the top 0.001%. I call it the 4 C's to Top-Level Talent: 1. CURATE Start hiring before you start hiring. Follow smart people in your niche on Twitter. Connect on LinkedIn. Bookmark stuff that makes you say, "Damn, I wish I wrote that." Treat talent like a portfolio. Study first, invest later. The best hires happen when you're NOT desperately hiring. 1. CULTIVATE Engage without being weird. Compliment their stuff. Comment. Ask smart questions. Send them ideas. The best talent moves when THEY'RE ready, not when you need them. Plant seeds early. Water them consistently. 3. CLOSE When it's time to close the sale, go HARD. Fly them in. Meet their spouse. Pay more than you're comfortable with. I wasn't even looking for a company President when I met Marc. I wanted a CRO. But after one conversation, I knew he was our guy. So I changed the org to fit HIM. That's how good hires work. They change you. Don't squeeze top talent into your current structure. Bend your business around exceptional people. 4. CONTINUE Top performers won't always stay forever. That's okay. Even when they leave, keep them close. My old Head of Content now runs a 7-figure business. We still trade notes. They send better talent than any recruiter ever could. As someone who’s hired 100s of people, take it from me: Your best hires won't walk in the door with a resume in hand. They're already working somewhere else, crushing it. It’s your job to go find them. Hiring the right people is one of the most powerful growth levers for any business. If you want to see exactly how we attract and retain top-tier talent across our portfolio, I’ll be breaking it all down in an upcoming workshop. This is just one of several proven scaling strategies we’ll cover— more info here: https://lnkd.in/e4xUbkV9

If you’re an AI engineer trying to understand and build with GenAI, RAG (Retrieval-Augmented Generation) is one of the most essential components to master. It’s the backbone of any LLM system that needs fresh, accurate, and context-aware outputs. Let’s break down how RAG works, step by step, from an engineering lens, not a hype one: 🧠 How RAG Works (Under the Hood) 1. Embed your knowledge base → Start with unstructured sources - docs, PDFs, internal wikis, etc. → Convert them into semantic vector representations using embedding models (e.g., OpenAI, Cohere, or HuggingFace models) → Output: N-dimensional vectors that preserve meaning across contexts 2. Store in a vector database → Use a vector store like Pinecone, Weaviate, or FAISS → Index embeddings to enable fast similarity search (cosine, dot-product, etc.) 3. Query comes in - embed that too → The user prompt is embedded using the same embedding model → Perform a top-k nearest neighbor search to fetch the most relevant document chunks 4. Context injection → Combine retrieved chunks with the user query → Format this into a structured prompt for the generation model (e.g., Mistral, Claude, Llama) 5. Generate the final output → LLM uses both the query and retrieved context to generate a grounded, context-rich response → Minimizes hallucinations and improves factuality at inference time 📚 What changes with RAG? Without RAG: 🧠 “I don’t have data on that.” With RAG: 🤖 “Based on [retrieved source], here’s what’s currently known…” Same model, drastically improved quality. 🔍 Why this matters You need RAG when: → Your data changes daily (support tickets, news, policies) → You can’t afford hallucinations (legal, finance, compliance) → You want your LLMs to access your private knowledge base without retraining It’s the most flexible, production-grade approach to bridge static models with dynamic information. 🛠️ Arvind and I are kicking off a hands-on workshop on RAG This first session is designed for beginner to intermediate practitioners who want to move beyond theory and actually build. Here’s what you’ll learn: → How RAG enhances LLMs with real-time, contextual data → Core concepts: vector DBs, indexing, reranking, fusion → Build a working RAG pipeline using LangChain + Pinecone → Explore no-code/low-code setups and real-world use cases If you're serious about building with LLMs, this is where you start. 📅 Save your seat and join us live: https://lnkd.in/gS_B7_7d

You're in a job interview, you get the offer—but the salary? Way lower than expected. The worst move? Accepting on the spot. The second worst? Declining outright. Here's how you can take the 'ick' out of negotiating: 1. Start with Gratitude →“Thank you for the offer.” 2. Share Excitement →“I’m really excited about the role and joining the company.” 3. Address the Salary →“Before I accept, I’d like to discuss the salary. It’s below what I believe reflects the market value for my experience.” 4. Reinforce Your Value →“I’m confident my expertise in A and B, and my contributions to C and D will drive success here.” 5. Reiterate Market Value →“Based on my research and track record, I believe a salary range of X to Y would be more in line with the industry.” Where to do research? Check salary data on sites like Glassdoor, Payscale, and LinkedIn, or ask industry peers and recruiters for real-world insights. Pro tip: Use multiple sources to get a well-rounded view and always adjust for location and years of experience. P.S. Have you ever accepted a salary because you didn't know how to negotiation? I'll go first: Yes, I have...

Today we unveil our inaugural list of Skills on the Rise in Information Technology, a data-backed ranking of the 10 fastest-growing skills that IT workers should be investing in to get ahead in today’s world of work. Given the breadth of technical knowledge required for IT roles, the rankings highlight a number of specialized skills like AI Literacy (No. 1), Technical Documentation (No. 7) and LLM Application (No. 10). Confidential Information Management comes in at No. 2 — a nod to the critical role of data protection and privacy in today’s regulatory landscape. To compile the list, we looked at unique LinkedIn data to reveal the IT skills that professionals are increasingly adding and that companies are increasingly hiring for. Check out the full list of Skills on the Rise in the U.S. and our methodology here: https://lnkd.in/SkillsontheRise25US. Which skills stand out to you on the list? And what other IT skills do you see rising in demand right now? Tell us in the comments. #SkillsOnTheRise

The most important skills today and in the next years will be human capabilities: critical and analytic thinking, resilience, leadership and influence, overlaid with technological literacy and AI skills to amplify these human capacities. World Economic Forum's new Future of Jobs Report provides a deep and broad analysis of the drivers of labour market transformation, the outlook for jobs and skills, and workforce strategies across industries and nations. It's a really worthwhile deep dive if you're interested in the topic (link in comments). Here are some of the highlights from the Skills section, which to my mind is at the heart of it. 🧠 Analytical Thinking Leads Core Skills. Skills like analytical thinking (70%), resilience (66%), and creative thinking (64%) top the list of core abilities for 2025. By 2030, the emphasis shifts even more towards AI and big data proficiency (85%), technological literacy (76%), and curiosity-driven lifelong learning (79%). This shift underscores the critical role of technology and adaptability in future workplaces. 📉 Skill Stability Declines but at a Slower Rate. Employers predict that 39% of workers' core skills will change by 2030, slightly lower than 44% in 2023. This reflects a stabilization in the pace of skill disruption due to increased emphasis on upskilling and reskilling programs. Half of the workforce now engages in training as part of long-term learning strategies compared to 41% in 2023, showcasing the growing adaptation to technological changes . 🌍 Economic Disparities in Skill Disruption. Middle-income economies anticipate higher skill disruption compared to high-income ones. This disparity highlights the uneven challenges of transitioning labor forces across global regions, particularly in economies still grappling with structural changes. 🚀 Tech-Savvy Skills in High Demand. The adoption of frontier technologies, including generative AI and machine learning, is increasing the demand for skills like big data analysis, cybersecurity, and technological literacy. These trends indicate that businesses are aligning workforce strategies to integrate these advancements effectively. 📚 Upskilling Is the Norm, Not the Exception. By 2030, 73% of organizations aim to prioritize workforce upskilling as a response to ongoing disruptions. This reflects a shift in corporate investment priorities towards human capital enhancement to maintain competitiveness.