Training & Development

A learning culture is not built by offering more training. It emerges where curiosity, connection, and purpose intersect. Andrew Barry, in The Curious Lion, describes learning culture as a lotus where several forces overlap. I find this framing helpful because it moves the conversation beyond HR programs and into the fabric of the organization. At the individual level, there is curiosity. People must feel invited to ask questions, challenge assumptions, and explore. Without individual curiosity, learning remains compliance. At the organizational level, there is mission. Learning needs direction. When people understand what the company stands for and where it is going, their curiosity becomes focused rather than scattered. At the relational level, there is human connection. Learning accelerates in environments where people feel safe to speak, experiment, and reflect together. The fourth circle is continuous learning. Learning must be ongoing, not episodic. Not a workshop, but a way of operating. Continuous learning ensures that curiosity, mission, and connection reinforce each other over time rather than fading after the latest initiative. When these circles overlap, deeper elements emerge: Shared vision aligns effort. Shared experiences create collective memory. Shared assumptions shape how reality is interpreted. Shared stories transmit meaning across generations. At the center sits what we call learning culture. Not an initiative, but a pattern of how people think, relate, and evolve together. The question for leaders is not, “Do we offer learning opportunities?” It is, “Do curiosity, mission, and connection truly reinforce each other continuously in our organization?” That is where learning becomes cultural rather than occasional.

I always get in trouble for these types of posts, but age or arrogance, I do not care anymore. I have interviewed 100 of the best sales leaders over the past 5 years. None has impressed me as much as Carles Reina at ElevenLabs. He scaled their GTM from $0 to $330M in ARR in just 3 years. Today I released our episode with him and have gone over it to condense my biggest lessons from the discussion. 🚀 8 Lessons on Building a $330M+ Revenue Machine 1. The "20x" Quota Rule Forget the standard SaaS 6x–8x multiple. At ElevenLabs, the rule is simple: you must bring in 20 times your base salary in revenue. If your base is $100k, your quota is $2M. It sounds aggressive, but it sets a high-performance bar where over 80% of the team hits their targets. 2. Hire "Hunters," Not Just Product Experts A common mistake is hiring for product knowledge and hoping to "train" the sales muscle. Carles learned the hard way: you need people with a natural "hunter" mentality who are hungry, driven, and passionate. You can teach the tech, but you can’t teach the hustle. 3. Be "Ruthless" with Pipeline Reviews Carles holds monthly pipeline reviews where he drills into every detail in front of the entire team. If you aren’t doing your job, you get called out publicly. This transparency ensures everyone learns from each other's mistakes and keeps the team on their toes. 4. Salespeople Belong on the Road If the sales team is in the office for multiple days, Carles starts getting worried. A remote culture works if it’s a "road" culture. Sellers need to be out talking to customers face-to-face, not just hiding behind virtual meetings. 5. Land Small, Expand Fast Don't get bogged down waiting months for a six-figure enterprise deal. Land with a $12k contract to bypass layers of approval. Once the MSA is signed, the "land" is over, and the "outbound" mission begins to capture every other team in the organization. 6. Forecast with Brutal Negativity Optimism kills sales organizations. Carles advises being as negative as possible when forecasting. If a deal is worth $500k, forecast it at $24k. This prevents "inflated" pipelines and forces the team to work twice as hard to ensure the real targets are hit. 7. The 72-Hour "First Contract" Goal Onboarding at ElevenLabs isn't about weeks of reading manuals. New hires join calls immediately. The target? Sign your first contract within your first two weeks. Some have even closed enterprise deals within 72 hours of joining. 8. Treat Customers as a Community, Not a Transaction Transactional selling leads to churn. Building a community—where you give customers your WhatsApp, interact constantly, and do what's right for them even if it costs you money—is how you retain them forever. Huge thanks to Mati Staniszewski and Luke Harries for helping to make this one happen. (link in comments) #founder #funding #business #investing #vc #venturecapital #entrepreneur #startup

Evaluating reasoning models is non-trivial. But you can use a verifier to check if answers are actually correct. I just finished a new 35-page chapter of Build a Reasoning Model (From Scratch), which is all about building such a verifier from the ground up. Symbolic parsing, math equivalence, edge cases… this was quite the project. But it’s now submitted and will hopefully appear soon on Manning’s Early Access platform. This chapter also includes a recap of other popular evaluation methods (multiple-choice, leaderboards, and judges): 3.1 Understanding the main evaluation methods for LLMs 3.1.1 Evaluating answer-choice accuracy 3.1.2 Using verifiers to check answers 3.1.3 Comparing models using preferences and leaderboards 3.1.4 Judging responses with other LLMs 3.2 Building a math verifier 3.3 Loading a pre-trained model to generate text 3.4 Implementing a wrapper for easier text generation 3.5 Extracting the final answer box 3.6 Normalizing the extracted answer 3.7 Verifying mathematical equivalence 3.8 Grading answers 3.9 Loading the evaluation dataset 3.10 Evaluating the model The code and sneak peak are on GitHub: 📖 https://mng.bz/lZ5B 🔗 https://lnkd.in/g8_7WtRX

Even though I’m a much better Python than JavaScript developer, with AI assistance, I’ve been writing a lot of JavaScript code recently. AI-assisted coding, including vibe coding, is making specific programming languages less important, even though learning one is still helpful to make sure you understand the key concepts. This is helping many developers write code in languages we’re not familiar with, which lets us get code working in many more contexts! My background is in machine learning engineering and back-end development, but AI-assisted coding is making it easy for me to build front-end systems (the part of a website or app that users interact with) using JavaScript (JS) or TypeScript (TS), languages that I am weak in. Generative AI is making syntax less important, so we can all simultaneously be Python, JS, TS, C++, Java, and even Cobol developers. Perhaps one day, instead of being “Python developers" or “C++ developers,” many more of us will just be “developers”! But understanding the concepts behind different languages is still important. That’s why learning at least one language like Python still offers a great foundation for prompting LLMs to generate code in Python and other languages. If you move from one programming language to another that carries out similar tasks but with different syntax — say, from JS to TS, or C++ to Java, or Rust to Go — once you’ve learned the first set of concepts, you’ll know a lot of the concepts needed to prompt an LLM to code in the second language. (Although TensorFlow and PyTorch are not programming languages, learning the concepts of deep learning behind TensorFlow will also make it much easier to get an LLM to write PyTorch code for you, and vice versa!) In addition, you’ll be able to understand much of the generated code (perhaps with a little LLM assistance). Different programming languages reflect different views of how to organize computation, and understanding the concepts is still important. For example, someone who does not understand arrays, dictionaries, caches, and memory will be less effective at getting an LLM to write code in most languages. Similarly, a Python developer who moves toward doing more front-end programming with JS would benefit from learning the concepts behind front-end systems. For example, if you want an LLM to build a front end using the React framework, it will benefit you to understand how React breaks front ends into reusable UI components, and how it updates the DOM data structure that determines what web pages look like. This lets you prompt the LLM much more precisely, and helps you understand how to fix issues if something goes wrong. Similarly, if you want an LLM to help you write code in CUDA or ROCm, it helps to understand how GPUs organize compute and memory. [Reached length limit; full text: https://lnkd.in/dS_buaTu ]

My client fired their entire SDR team on Tuesday By Friday, their pipeline had grown by 60% This sounds impossible It's not After auditing 50 B2B sales organizations over 10 years, I've uncovered the most expensive myth in modern selling: → The belief that MORE activity at the TOP of your funnel will fix conversion problems at the BOTTOM Let me share what actually happened: This mid-market software company was spending $350,000 annually on their 4-person SDR team - 100+ cold calls per rep daily - 17 meetings booked weekly - "Incredible metrics" according to leadership - But their close rate? A devastating 1.2% The VP of Sales was convinced they needed MORE outreach, MORE automation, MORE top-of-funnel I suggested something different: pause all prospecting for 7 days Instead, we had their account executives do something radical - engage with the 215 prospects already in their pipeline who'd gone cold after initial meetings Using a framework we developed: - 65 prospects responded within 24 hours - 41 booked follow-up meetings - 23 re-entered active buying cycles - 6 closed within 14 days (total value: $212K) The shocking revelation? - Their pipeline wasn't empty - It was overflowing with neglected opportunity. This company didn't have a lead generation problem. They had a lead nurturing catastrophe. By reallocating resources from mindless prospecting to strategic engagement, they've now: - Reduced CAC by 60% - Shortened sales cycles by 30% - 2x their close rate The counterintuitive truth: Sometimes the fastest path to growth is to stop chasing new opportunities and start converting the ones you've already earned. What percentage of your marketing and sales budget is focused on prospects who've already shown interest vs those who haven't? That ratio reveals everything about your future growth trajectory P.S. If you need help with your sales, send me a message

If you REALLY want to support women in the workplace, you need to start: → Offering flexible work arrangements, especially to support mothers. → Encouraging women to go for internal promotions → Paying women fairly and transparently → Creating environments where women’s voices are heard → Calling out microaggressions and biases when you see them → Offering leadership training and mentorship for women → Rethinking how performance and ambition are measured (not just who shouts the loudest) → Making networking and career progression opportunities accessible to all → Championing women even when they’re not in the room → Reviewing your hiring and promotion processes to eliminate bias → Creating policies that support women through all life stages (not just maternity leave) → Holding senior leaders accountable for diversity and inclusion goals → Ensuring workplace policies support women’s health, including menopause and period policies International Women’s Day should be about real, tangible action. Too often, we see businesses celebrating IWD while their leadership teams are still male-dominated, pay gaps persist and workplace policies don’t support women’s real needs. So, if you’re a business leader, hiring manager, or even a colleague... Ask yourself: What are you actually doing to make the workplace more equitable for women? 🤔

Master the core SQL commands that drive 80% of tasks. This post focuses on practical, real-world applications of SQL for maximum impact. Fundamental SQL Commands 1. 𝗦𝗘𝗟𝗘𝗖𝗧: Retrieving specific data        𝚂𝙴𝙻𝙴𝙲𝚃 𝚏𝚒𝚛𝚜𝚝_𝚗𝚊𝚖𝚎, 𝚕𝚊𝚜𝚝_𝚗𝚊𝚖𝚎, 𝚎𝚖𝚊𝚒𝚕 𝙵𝚁𝙾𝙼 𝚌𝚞𝚜𝚝𝚘𝚖𝚎𝚛𝚜;    2. 𝗪𝗛𝗘𝗥𝗘: Filtering results        𝚆𝙷𝙴𝚁𝙴 𝚙𝚞𝚛𝚌𝚑𝚊𝚜𝚎_𝚍𝚊𝚝𝚎 >= '𝟸𝟶𝟸𝟹-𝟶𝟷-𝟶𝟷' 𝙰𝙽𝙳 𝚝𝚘𝚝𝚊𝚕_𝚜𝚙𝚎𝚗𝚝 > 𝟷𝟶𝟶𝟶;    3. 𝗚𝗥𝗢𝗨𝗣 𝗕𝗬: Aggregating data        𝚂𝙴𝙻𝙴𝙲𝚃 𝚙𝚛𝚘𝚍𝚞𝚌𝚝_𝚌𝚊𝚝𝚎𝚐𝚘𝚛𝚢, 𝚂𝚄𝙼(𝚜𝚊𝚕𝚎𝚜_𝚊𝚖𝚘𝚞𝚗𝚝) 𝙰𝚂 𝚝𝚘𝚝𝚊𝚕_𝚜𝚊𝚕𝚎𝚜    𝙵𝚁𝙾𝙼 𝚜𝚊𝚕𝚎𝚜    𝙶𝚁𝙾𝚄𝙿 𝙱𝚈 𝚙𝚛𝚘𝚍𝚞𝚌𝚝_𝚌𝚊𝚝𝚎𝚐𝚘𝚛𝚢;    4. 𝗢𝗥𝗗𝗘𝗥 𝗕𝗬: Sorting data        𝚂𝙴𝙻𝙴𝙲𝚃 𝚙𝚛𝚘𝚍𝚞𝚌𝚝_𝚗𝚊𝚖𝚎, 𝚜𝚝𝚘𝚌𝚔_𝚚𝚞𝚊𝚗𝚝𝚒𝚝𝚢    𝙵𝚁𝙾𝙼 𝚒𝚗𝚟𝚎𝚗𝚝𝚘𝚛𝚢    𝙾𝚁𝙳𝙴𝚁 𝙱𝚈 𝚜𝚝𝚘𝚌𝚔_𝚚𝚞𝚊𝚗𝚝𝚒𝚝𝚢 𝙰𝚂𝙲;    5. 𝗝𝗢𝗜𝗡: Combining related data        𝚂𝙴𝙻𝙴𝙲𝚃 𝚘.𝚘𝚛𝚍𝚎𝚛_𝚒𝚍, 𝚌.𝚌𝚞𝚜𝚝𝚘𝚖𝚎𝚛_𝚗𝚊𝚖𝚎, 𝚘.𝚘𝚛𝚍𝚎𝚛_𝚍𝚊𝚝𝚎    𝙵𝚁𝙾𝙼 𝚘𝚛𝚍𝚎𝚛𝚜 𝚘    𝙸𝙽𝙽𝙴𝚁 𝙹𝙾𝙸𝙽 𝚌𝚞𝚜𝚝𝚘𝚖𝚎𝚛𝚜 𝚌 𝙾𝙽 𝚘.𝚌𝚞𝚜𝚝𝚘𝚖𝚎𝚛_𝚒𝚍 = 𝚌.𝚒𝚍;    Advanced SQL Techniques 1. 𝗦𝘂𝗯𝗾𝘂𝗲𝗿𝗶𝗲𝘀: Nested queries for complex conditions        SELECT product_name, price    FROM products    WHERE price > (SELECT AVG(price) FROM products);    2. 𝗖𝗼𝗺𝗺𝗼𝗻 𝗧𝗮𝗯𝗹𝗲 𝗘𝘅𝗽𝗿𝗲𝘀𝘀𝗶𝗼𝗻𝘀 (𝗖𝗧𝗘): Simplifying complex queries        WITH monthly_sales AS (    SELECT EXTRACT(MONTH FROM sale_date) AS month, SUM(amount) AS total    FROM sales    GROUP BY EXTRACT(MONTH FROM sale_date)    )    SELECT month, total    FROM monthly_sales    WHERE total > 100000;    3. 𝗪𝗶𝗻𝗱𝗼𝘄 𝗙𝘂𝗻𝗰𝘁𝗶𝗼𝗻𝘀: Calculations across row sets        SELECT    department,    employee_name,    salary,    RANK() OVER (PARTITION BY department ORDER BY salary DESC) AS salary_rank    FROM employees;    4. 𝗖𝗔𝗦𝗘 𝗦𝘁𝗮𝘁𝗲𝗺𝗲𝗻𝘁𝘀: Conditional categorization        SELECT    customer_id,    CASE    WHEN lifetime_value > 10000 THEN 'VIP'    WHEN lifetime_value > 5000 THEN 'Premium'    ELSE 'Standard'    END AS customer_segment    FROM customer_data;    Optimization Tips - Use indexes on frequently filtered columns - Avoid SELECT * and only retrieve necessary columns - Use EXPLAIN ANALYZE to understand query execution plans Learning Strategy 1. Start with simple SELECT queries on a sample database 2. Progress to filtering and sorting data 3. Practice joins with multiple tables 4. Explore advanced techniques with real datasets 5. Participate in online SQL challenges and forums By mastering these SQL commands and techniques, you'll be well-equipped to handle a wide range of data analysis tasks efficiently. Regular practice with diverse datasets will solidify your skills. What's your favorite SQL trick for streamlining data ? Share your insights below!

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.

💎 Accessibility For Designers Checklist (PDF: https://lnkd.in/e9Z2G2kF), a practical set of cards on WCAG accessibility guidelines, from accessible color, typography, animations, media, layout and development — to kick-off accessibility conversations early on. Kindly put together by Geri Reid. WCAG for Designers Checklist, by Geri Reid Article: https://lnkd.in/ef8-Yy9E PDF: https://lnkd.in/e9Z2G2kF WCAG 2.2 Guidelines: https://lnkd.in/eYmzrNh7 Accessibility isn’t about compliance. It’s not about ticking off checkboxes. And it’s not about plugging in accessibility overlays or AI engines either. It’s about *designing* with a wide range of people in mind — from the very start, independent of their skills and preferences. In my experience, the most impactful way to embed accessibility in your work is to bring a handful of people with different needs early into design process and usability testing. It’s making these test sessions accessible to the entire team, and showing real impact of design and code on real people using a real product. Teams usually don’t get time to work on features which don’t have a clear business case. But no manager really wants to be seen publicly ignoring their prospect customers. Visualize accessibility to everyone on the team and try to make an argument about potential reach and potential income. Don’t ask for big commitments: embed accessibility in your work by default. Account for accessibility needs in your estimates. Create accessibility tickets and flag accessibility issues. Don’t mistake smiling and nodding for support — establish timelines, roles, specifics, objectives. And most importantly: measure the impact of your work by repeatedly conducting accessibility testing with real people. Build a strong before/after case to show the change that the team has enabled and contributed to, and celebrate small and big accessibility wins. It might not sound like much, but it can start changing the culture faster than you think. Useful resources: Giving A Damn About Accessibility, by Sheri Byrne-Haber (disabled) https://lnkd.in/eCeFutuJ Accessibility For Designers: Where Do I Start?, by Stéphanie Walter https://lnkd.in/ecG5qASY Web Accessibility In Plain Language (Free Book), by Charlie Triplett https://lnkd.in/e2AMAwyt Building Accessibility Research Practices, by Maya Alvarado https://lnkd.in/eq_3zSPJ How To Build A Strong Case For Accessibility, ↳ https://lnkd.in/ehGivAdY, by 🦞 Todd Libby ↳ https://lnkd.in/eC4jehMX, by Yichan Wang #ux #accessibility

In 2008, Michael Phelps won Olympic GOLD - completely blind. The moment he dove in, his goggles filled with water. But he kept swimming. Most swimmers would’ve fallen apart. Phelps didn’t - because he had trained for chaos, hundreds of times. His coach, Bob Bowman, would break his goggles, remove clocks, exhaust him deliberately. Why? Because when you train under stress, performance becomes instinct. Psychologists call this stress inoculation. When you expose yourself to small, manageable stress: - Your amygdala (fear centre) becomes less reactive. - Your prefrontal cortex (logic centre) stays calmer under pressure. Phelps had rehearsed swimming blind so often that it felt normal. He knew the stroke count. He hit the wall without seeing it. And won GOLD by 0.01 seconds. The same science is why: - Navy SEALs tie their hands and practice underwater survival. - Astronauts simulate system failures in zero gravity. - Emergency responders train inside burning buildings. And you can build it too. Here’s how: ✅ Expose yourself to small discomforts. Take cold showers. Wake up 30 minutes earlier. Speak up in meetings. The goal is to build confidence that you can handle hard things. ✅ Use quick stress resets. Try cyclic sighing: Inhale deeply through your nose. Take a second small inhale. Exhale slowly through your mouth. Repeat 3-5 times to calm your system fast. ✅ Strengthen emotional endurance. Instead of avoiding difficult conversations, hard tasks, or feedback - lean into them. Facing small emotional challenges trains you for bigger ones later. ✅ Celebrate small victories. Every time you stay calm, adapt, or keep going under pressure - recognise it. These tiny wins are building your mental "muscle memory" for resilience. As a new parent, I know my son Krish will face his own "goggles-filled-with-water" moments someday. So the best I can do is model resilience myself. Because resilience isn’t gifted - it’s trained. And when you train your brain for chaos, you can survive anything. So I hope you do the same. If this made you pause, feel free to repost and share the thought. #healthandwellness #mentalhealth #stress