Change Management

AI security/securing the use of AI is going to kill me. I use Claude Code almost daily. It's a problem.... Here's what I have to change AGAIN this week. Security researcher Ari Marzuk disclosed 30+ vulnerabilities across AI coding tools. Cursor. GitHub Copilot. Windsurf. Claude Code. All of them. He called it IDEsaster. The attack chain includes prompt injection, hijacking LLM context, and auto-approved tool calls executing without permission. Then, legitimate IDE features are weaponized for data exfiltration and RCE. Your .env files. Your API keys. Your source code. Accessible through features you thought were safe. Most studies I read claim that around 85% of developers now use AI coding tools daily. Most have no idea their IDE treats its own features as inherently trusted. 𝗦𝗼... 𝗮𝗳𝘁𝗲𝗿 𝗿𝗲𝘃𝗶𝗲𝘄𝗶𝗻𝗴 𝗔𝗿𝗶'𝘀 𝗿𝗲𝘀𝗲𝗮𝗿𝗰𝗵, 𝗵𝗲𝗿𝗲'𝘀 𝗜 𝘄𝗶𝗹𝗹 𝗯𝗲 𝗱𝗼𝗶𝗻𝗴... Be warned: All this is SO much easier said than done! Audit every MCP server connection. Checked for tool poisoning vectors where legitimate tools might parse attacker-controlled input from GitHub PRs or web content. Removed servers I couldn't verify. Disabled auto-approve for file writes. The attack chains weaponize configuration files and project instructions like .claude/settings.json and CLAUDE.md. One malicious write to these files can alter agent behavior or achieve code execution without additional user interaction. Move all credentials to a secrets manager. No .gitignored .env files in agent-accessible directories. API keys live in 1Password CLI. Environment variables inject at runtime through a wrapper script the LLM never sees. Start running Claude Code in isolated containers. Mounted volumes limited to specific project directories. No access to ~/.ssh, ~/.aws, or ~/.config. If the agent gets compromised, blast radius stays contained. Enable all security warnings. Claude Code added explicit warnings for JSON schema exfiltration and settings file modifications. These exist because Anthropic knows the attack surface. Add pre-commit hooks for hidden characters. Prompt injections hide in pasted URLs, READMEs, and file names using invisible Unicode. Flag non-ASCII characters in any file the agent might ingest. The fix isn't to stop using AI coding tools. The fix is to stop trusting them implicitly. What controls do you have for AI tools with write access to your codebase? 👉 Follow for more AI and cybersecurity insights with the occasional rant #AISecurity #DevSecOps

70% of change initiatives fail. (And it's rarely because the idea was bad.) Here's what actually kills transformation: You picked the wrong change model for the job. It's like performing surgery with a hammer. Sure, you're using a tool. But it's the wrong one. I've watched brilliant CEOs tank their companies this way: Using individual coaching (ADKAR) for company-wide transformation. Result: 200 people change. 2,000 don't. Running a massive 8-step program for a simple process fix. Result: 6 months wasted. Team exhausted. Nothing changes. Forcing top-down mandates when they needed subtle nudges. Result: Rebellion. Resentment. Resignation letters. Here's what nobody tells you about change: The size of your change determines your approach. Real examples from the field: 💡 Startup pivoting product: → Used Lewin's 3-stage (unfreeze old way, change, refreeze) → 3 months. Clean transition. Team aligned. 💡 Enterprise going digital: → Used Kotter's 8-step process → Created urgency first. Built coalition. Enabled action. → 18 months later: $50M in new revenue. 💡 Sales team adopting new CRM: → Used Nudge Theory → Made old system harder to access → Put new system as browser homepage → 95% adoption in 2 weeks. Zero complaints. The expensive truth: Wrong model = wasted months + burned budgets + broken trust Right model = faster adoption + sustained results + energized teams Warning signs you're using the wrong model: • High activity, low progress • People comply but don't commit • Changes revert within weeks • Energy drops as you push harder • "This too shall pass" becomes the motto Match your medicine to your ailment: Small behavior change? Nudge it. Individual performance? ADKAR it. Cultural shift? Influence it. Full transformation? Kotter it. Enterprise overhaul? BCG it. Stop treating every change like a nail. Start choosing the right tool for the job. Your next change initiative depends on it. Your team's trust demands it. Your company's future requires it. Save this. Share it with your leadership team. Because the next time someone says "people resist change," you'll know the truth: People don't resist change. They resist the wrong approach to change. P.S. Want a PDF of my Change Management cheat sheet? Get it free: https://lnkd.in/dv7biXUs ♻️ Repost to help a leader in your network. Follow Eric Partaker for more operational insights. — 📢 Want to lead like a world-class CEO? Join my FREE TRAINING: "The 8 Qualities That Separate World-Class CEOs From Everyone Else" Thu Jul 3rd, 12 noon Eastern / 5pm UK time https://lnkd.in/dy-6w_rx 📌 The CEO Accelerator starts July 23rd. 20+ Founders & CEOs have already enrolled. Learn more and apply: https://lnkd.in/dwndXMAk

Dell cut 25,000 jobs in two years. Then something unexpected happened. Revenue per employee shot up 15% - not from simple math, but from key decisions which are reshaping how technology companies operate. Revenue per employee since 2017: → Dell Technologies: $885K (Up 98% from $446K) → Hewlett Packard Enterprise: $494K (Up just 13%) → Cisco: $595K (Down 10%) → IBM: $214K (Essentially flat) This dramatic improvement didn't happen by accident. To understand how Dell achieved this transformation, we need to look at their history of reinvention. Dell's previous pivots: → 1984: Direct-to-consumer PC revolution → 1996: E-commerce pioneer with $1M/day in sales → 2013: $24.4B privatization escaping public markets → 2016: $67B EMC acquisition for enterprise presence → 2021: VMware spin-off to focus on core infra → 2022-2025: AI rebuild with workforce efficiency How did Dell go from 133,000 employees to 108,000 while continuing to grow revenue? To answer this question, I looked through their latest filings. Three key strategies emerged: 1. AI-Optimized Infrastructure Economics → Delivering 2-4x margins with AI servers → Reducing labor for higher-value infrastructure sales → Creating more value with less human intervention 2. Surgical Business Focus → Concentrating on Infrastructure Solutions Group → Growing AI-optimized server business by 22-38% → Exiting or downsizing lower-productivity segments 3. Organizational Simplification → Eliminating entire management layers → Streamlining decision-making processes → Maintaining output with substantially fewer people The implications extend beyond Dell. What we are seeing is a shift where revenue growth no longer directly correlates with headcount growth - breaking a pattern that's persisted in tech for decades. Tech companies now face a clear choice: → Continue with labor-intensive models or → Embrace technology-driven productivity At its core, this represents a fundamental shift in how value gets created in technology companies. The most valuable skills increasingly involve orchestrating technology rather than simply operating it.

Scaling from 50 to 100 employees almost killed our company. Until we discovered a simple org structure that unlocked $100M+ in annual revenue. In my 10+ years of experience as a founder, one of the biggest challenges I faced in scaling was bridging the organizational gap between startup and enterprise. We hit that wall at around 100~ employees. What worked beautifully with a small team suddenly became our biggest obstacle to growth. The problem was our functional org structure: Engineers reporting to engineering, product to product, business to business. This created a complex dependency web: • Planning took weeks • No clear ownership  • Business threw Jira tickets over the fence and prayed for them to get completed • Engineers didn’t understand priorities and worked on problems that didn’t align with customer needs That was when I studied Amazon's Single-Threaded Owner (STO) model, in which dedicated GMs run independent business units with their own cross-functional teams and manage P&L It looked great for Amazon's scale but felt impossible for growing companies like ours. These 2 critical barriers made it impractical for our scale: 1. Engineering Squad Requirements: True STO demands complete engineering teams (including managers) reporting to a single owner. At our size, we couldn't justify full engineering squads for each business unit. To make it work, we would have to quadruple our engineering headcount. 2. P&L Owner Complexity: STO leaders need unicorn-level skills: deep business acumen and P&L management experience. Not only are these leaders rare and expensive, but requiring all these skills in one person would have limited our talent pool and slowed our ability to launch new initiatives. What we needed was a model that captured STO's focus and accountability but worked for our size and growth needs. That's when we created Mission-Aligned Teams (MATs), a hybrid model that changed our execution (for good) Key principles: • Each team owns a specific mission (e.g., improving customer service, optimizing payment flow) • Teams are cross-functional and self-sufficient,  • Leaders can be anyone (engineer, PM, marketer) who's good at execution • People still report functionally for career development • Leaders focus on execution, not people management The results exceeded our highest expectations: New MAT leads launched new products, each generating $5-10M in revenue within a year with under 10 person teams. Planning became streamlined. Ownership became clear. But it's NOT for everyone (like STO wasn’t for us) If you're under 50 people, the overhead probably isn't worth it. If you're Amazon-scale, pure STO might be better. MAT works best in the messy middle: when you're too big for everyone to be in one room but too small for a full enterprise structure. image courtesy of Manu Cornet ------ If you liked this, follow me Henry Shi as I share insights from my journey of building and scaling a  $1B/year business.

Enterprise Architecture 4.0 is Coming 🚀 A new era is unfolding—Enterprise Architecture 4.0—where AI isn’t just an enabler; it’s a co-pilot. Traditional EA was about alignment, optimization, and governance. But in an AI-first world, EA must evolve into something far more dynamic: ✅ AI-driven decision-making ✅ Dynamic capabilities and value streams ✅ Agentic AI architectures ✅ Event-driven, composable ecosystems This isn’t just theory—it has started to happen. AI-powered digital twins are optimizing business landscapes in real-time. AI agents are making decisions, orchestrating workflows, and adapting at scale. The shift from rigid architectures to autonomous, event-driven enterprises is reshaping how we design, govern, and operate businesses. But with great AI power comes great responsibility. Enterprise Architecture needs to evolve to address areas including: ⚠️ How do we ensure governance, ethics, and compliance in AI-driven ecosystems? ⚠️ How do we manage dynamic touch-points between humans, AI Agents and external systems? ⚠️ How do enterprises bridge the gap between legacy applications and AI-powered decision intelligence? ⚠️ How do EA roles need to evolve to architect for AI-first enterprises? Enterprise Architecture 4.0 isn’t an upgrade—it’s a transformation. Organizations that embrace agentic AI, composability, and trust-based governance will lead the next era of digital enterprise. Are you ready for this shift? What’s your take on the role of AI in shaping the future of EA? Let’s discuss in the comments.👇 #EnterpriseArchitecture #AI #DigitalTransformation #AIinEnterprise #FutureOfWork

Consulting isn’t dying—it’s evolving. The traditional "finder, minder, grinder" framework that has defined the industry for decades is being disrupted. As client expectations shift and technology advances, the reliance on junior-heavy teams and leverage-based profit models is under significant pressure. The future of consulting lies in a new model where hands-on leadership is paramount. Corporate and Private Equity clients expect senior-level Partners to actively drive strategy execution. They want seasoned professionals with deep expertise to lead from the front, ensuring that solutions are not just designed but delivered with measurable impact. Successful consulting firms will focus on outcomes rather than hours. By integrating AI and other technologies, they will accelerate efficiency and enable senior leaders to focus on delivering real value. Clients are increasingly drawn to results-driven approaches that prioritise entrepreneurial thinking and experimentation over time-based billing. As technology advances over analytical tasks, human consultants must excel in areas machines cannot replicate: creativity, emotional intelligence, and cross-disciplinary collaboration. Coaching clients on how to leverage technology effectively will become a core skill, alongside curiosity and adaptability.

Company culture is NOT words on a wall. It’s how people feel on a Sunday night. If your team spends Sundays dreading Mondays, it’s not “just how work is.” It’s a cry for help. Culture isn’t about snacks or meditation apps. It’s how people feel—when they’re off the clock. So, how do you create a culture where people want to show up on Monday? Here are 5 game-changers: 1/ Build Trust ↳ Show transparency in decision-making. ↳ Create a safe space for ideas—no fear, no judgment. ↳ Trust starts with leaders; it’s earned, not demanded. 2/ Show Appreciation ↳ Celebrate small wins as much as big ones. ↳ Say “thank you”—it costs nothing but means everything. ↳ Be specific: “Your effort on [task] made a huge difference.” 3/ Encourage Rest ↳ Lead by example—don’t email at midnight. ↳ Promote breaks, PTO, and unplugging after hours. ↳ Productivity thrives when people are rested, not burnt out. 4/ Communicate Clearly ↳ Give feedback that builds, not breaks. ↳ Set realistic goals, timelines, and expectations. ↳ Clarity in communication removes fear of the unknown. 5/ Lead by Example ↳ If you want work-life harmony, live it. ↳ Culture isn’t what you say—it’s what you do. ↳ Share your own struggles and how you manage. 👉 Culture thrives when leaders set the tone. If you fix how people feel about coming to work? Mondays will take care of themselves. P.S. Repost this to inspire your network! ➡️ Follow Shulin Lee, for more.

I’ve been headhunting in the CPG industry for the past decade, and I’ve never seen a post-inflation market like we’re in right now. For the past three years, customers have been capitulating to price hikes by extending their budgets. But now, they’re at a breaking point. American families, already tethering on edges of their budgets, do not have the ability or the desire to expand their budget in order to accommodate increased prices. I’m sure you’d agree with this, because my family certainly does. With grocery bills through the roof, we’d rather skip on groceries and essentials rather than paying a premium right now. A couple things led us here, starting the pandemic and the post-pandemic impact on spending and savings. Secondly, the wave of AI and tech developments that caught us off guard. So, where do the companies go now? Once the “price increase” playbook is done, CPG brands can only win in both value and volume by shifting gears. In my chats with executives, I’m sensing a change in tone. To stay competitive, they’re looking for ways to shift from the post-pandemic survival mindset to a growth-focused one that accommodates the customer as well. Rather than hiking prices, the focus is now on bringing down costs, and getting to terms with consumer’s limited budgets and increasing product choices. Layoffs aren’t the only way to bring down costs. In my view, CPG companies do have the leeway to embrace data-driven innovation and efficiency to cut costs. Here are some of the ways in which companies can use AI and ML to achieve targets in 2025 and beyond: 1/ Predicting the demand: Post-pandemic behavior is tough to predict, especially in CPG markets. With AI, the companies can now leverage real-time insights from sources like point-of-sale systems, social media, and even economic indicators to see future trends more clearly. PepsiCo, uses Tastewise to track what consumers are eating across 60+ million touchpoints and making decisions that align with local preference. 2/ Inventory management: With AI-powered predictive analytics, companies are now turning inventory management into a science. Procter & Gamble’s Supply Chain 3.0 initiative is one example of this shift. 3/ Increased personalization: Leaders are tapping into geographical intelligence to connect meaningfully with audiences. Estée Lauder has a voice-enabled makeup assistant for visually impaired customers, reaching a new market while boosting brand loyalty. Bottom line is: customers are no longer meeting brands where they’re at. It’s high time that companies start caring about customers and their shrinking bottom lines. Are you excited to see your grocery bill go down in the next few months? #CPG #AI #ML #fmcg #marketing #trending

When your best people start to go quiet, it’s not just a silence - it’s an alert.

It means the worst parts of your culture are taking up space, and the voices you need most are pulling back. 

Silence from your core talent isn’t a lack of ideas or effort; it’s a response to a slipping environment.
 For leaders, this is your cue to take real action:
 1. Create Space for Honest Conversations: Set up regular, safe one-on-ones where people can speak openly. Don’t just ask for feedback—listen, act on it, and show that their voices lead to tangible change.

 2. Recognize and Address Toxic Behaviors: Don’t ignore the negativity, micromanagement, or favoritism that might be breeding. Set clear expectations for respect and collaboration, and hold everyone accountable, regardless of title.

 3. Celebrate Contributions Regularly: Acknowledge the work and ideas that come from all levels. Recognition shouldn’t be saved for major milestones; small, genuine appreciation keeps morale alive and reminds people they’re valued.

 4. Empower Decision-Making: Give your team the freedom to own projects and make choices. The best ideas come from people who feel trusted and respected, not micromanaged.

 When the real drivers of your culture stop speaking up, it’s a signal to recalibrate. 

Lead by example, and show that culture is built through daily actions - not just words. ♻️Rob Dance

𝗙𝗮𝗶𝗹𝘂𝗿𝗲 𝗶𝘀 𝗰𝗿𝘂𝗰𝗶𝗮𝗹 𝗳𝗼𝗿 𝗶𝗻𝗻𝗼𝘃𝗮𝘁𝗶𝗼𝗻 & 𝗴𝗿𝗼𝘄𝘁𝗵‼️   In today’s slow-growth economy, innovation budgets are tight. The pressure to deliver successful innovations with a strong ROI has never been higher. As a result, many innovation managers feel they must constantly justify their activities, fearing the potential failure of some projects. 𝗧𝗵𝗶𝘀 𝗳𝗲𝗮𝗿 𝗼𝗳𝘁𝗲𝗻 𝗹𝗲𝗮𝗱𝘀 𝘁𝗼 𝗵𝗲𝘀𝗶𝘁𝗮𝘁𝗶𝗼𝗻: fewer experiments, fewer bold moves, and ultimately, fewer breakthroughs. According to Deloitte’s “𝘛𝘩𝘦 𝘴𝘵𝘢𝘵𝘦 𝘰𝘧 𝘪𝘯𝘯𝘰𝘷𝘢𝘵𝘪𝘰𝘯 𝘪𝘯 𝘎𝘦𝘳𝘮𝘢𝘯 𝘤𝘰𝘮𝘱𝘢𝘯𝘪𝘦𝘴” 𝟯𝟭% 𝗼𝗳 𝗶𝗻𝗻𝗼𝘃𝗮𝘁𝗶𝗼𝗻 𝗹𝗲𝗮𝗱𝗲𝗿𝘀 𝘀𝗲𝗲 𝗮 𝗹𝗮𝗰𝗸 𝗼𝗳 𝗿𝗶𝘀𝗸 𝗮𝗽𝗽𝗲𝘁𝗶𝘁𝗲 𝗮𝘀 𝗼𝗻𝗲 𝗼𝗳 𝘁𝗵𝗲 𝗯𝗶𝗴𝗴𝗲𝘀𝘁 𝗼𝗯𝘀𝘁𝗮𝗰𝗹𝗲𝘀 𝘁𝗼 𝗶𝗻𝗻𝗼𝘃𝗮𝘁𝗶𝗼𝗻 in their organization. This is a missed opportunity. 𝗜𝗻𝗻𝗼𝘃𝗮𝘁𝗶𝗼𝗻 𝘁𝗵𝗿𝗶𝘃𝗲𝘀 𝗶𝗻 𝗮 𝗰𝘂𝗹𝘁𝘂𝗿𝗲 𝘁𝗵𝗮𝘁 𝗮𝗹𝗹𝗼𝘄𝘀 𝗳𝗼𝗿 𝗰𝗮𝗹𝗰𝘂𝗹𝗮𝘁𝗲𝗱 𝗿𝗶𝘀𝗸𝘀—the key word being 𝘤𝘢𝘭𝘤𝘶𝘭𝘢𝘵𝘦𝘥. Gone are the days when it was acceptable to experiment freely without a clear focus on commercial outcomes. Today, every innovation must eventually translate into measurable success. 𝗧𝗵𝗲 𝗴𝗼𝗼𝗱 𝗻𝗲𝘄𝘀? Risk can be managed. Companies can take strategic steps to balance innovation and risk: ✔️ Create transparency across your innovation portfolio. ✔️ Track progress using clear, actionable KPIs. ✔️Assess market potential for each innovation and decide on the optimal path—exit, spin-off, carve-out, or asset licensing. By embedding these practices into their innovation process, companies can confidently navigate the uncertainties of new ideas, making informed decisions at every stage. So, 𝗶𝗻𝘀𝘁𝗲𝗮𝗱 𝗼𝗳 𝗱𝗶𝘀𝗰𝗼𝘂𝗿𝗮𝗴𝗶𝗻𝗴 𝗶𝗻𝗻𝗼𝘃𝗮𝘁𝗶𝗼𝗻 𝗱𝘂𝗲 𝘁𝗼 𝘁𝗵𝗲 𝗳𝗲𝗮𝗿 𝗼𝗳 𝗳𝗮𝗶𝗹𝘂𝗿𝗲, 𝗲𝗺𝗽𝗼𝘄𝗲𝗿 𝘆𝗼𝘂𝗿 𝘁𝗲𝗮𝗺𝘀 with the right tools and frameworks 𝘁𝗼 𝘁𝗮𝗸𝗲 𝗰𝗮𝗹𝗰𝘂𝗹𝗮𝘁𝗲𝗱 𝗿𝗶𝘀𝗸𝘀 𝗮𝗻𝗱 𝗮𝗰𝗵𝗶𝗲𝘃𝗲 𝗶𝗺𝗽𝗮𝗰𝘁𝗳𝘂𝗹 𝗿𝗲𝘀𝘂𝗹𝘁𝘀!   FOOD FOR THOUGHT! 💭 How does your organization handle calculated risks? Is it encouraged, or do you face resistance? Let’s discuss in the comments! ———————————— ♻️ Share this to embrace failure as a driver for innovation! 💡 Follow me, Lara Sophie Bothur, for more insights on AI, tech trends, and how to turn challenges into breakthroughs! Credits to Roberto Ferraro / Recreation of his great work!