Future Of Work

Cloud Native technologies have long been at the heart of scalable applications. But now, with AI and Agentic Systems, the game is changing!   Unlike traditional AI automation, Agentic AI can make decisions, execute workflows, and adapt dynamically to system changes—without constant human oversight. This means self-healing, self-optimizing, and autonomous cloud-native infrastructure!  Here’s how Agentic AI can transform each layer of Cloud Native skills:  1. Linux & AI-Optimized OS   - AI-powered package managers automatically resolve compatibility issues.   - Agentic AI monitors system logs, predicts failures, and patches vulnerabilities autonomously.  2. Networking & AI-Driven Observability   - AI-driven network forensics using self-learning algorithms to detect anomalies.   - Agent-based routing optimizations, ensuring seamless traffic flow even in congestion.  3. Cloud Services & AI-Augmented Workflows   - Agentic AI predicts cloud workload demand and pre-allocates resources in AWS, Azure, and GCP.   - Autonomous cost optimization adjusts instance types, storage, and compute in real time.  4. Security & AI Cyberdefense Agents   - Self-learning AI security agents actively detect and mitigate cyber threats before they happen.   - Generative AI-powered penetration testing agents simulate evolving attack patterns.  5. Containers & Agentic AI Orchestration   - Autonomous Kubernetes controllers scale clusters before demand spikes.   - Agentic AI continuously optimizes pod scheduling, reducing cold starts and resource waste.  6. Infrastructure as Code + AI Copilots   - AI-driven infrastructure agents automatically refactor Terraform, Ansible, and Puppet scripts.   - Self-adaptive IaC, where AI updates configurations based on usage patterns and compliance policies.  7. Observability & AI-Driven Incident Response   - AI-powered anomaly detection in Grafana & Prometheus—flagging issues before failures.   - Agentic AI handles incident response, running diagnostics and executing pre-approved fixes.  8. CI/CD & Autonomous Pipelines   - Agentic AI writes, tests, and deploys code autonomously, reducing developer toil.   - Self-optimizing pipelines that rerun failed tests, debug, and retry deployment automatically.  The Future: Fully Autonomous Cloud Native Systems!  𝗗𝗲𝘃𝗢𝗽𝘀 𝗮𝘂𝘁𝗼𝗺𝗮𝘁𝗶𝗼𝗻 → 𝗔𝗜-𝗽𝗼𝘄𝗲𝗿𝗲𝗱 𝗼𝗯𝘀𝗲𝗿𝘃𝗮𝗯𝗶𝗹𝗶𝘁𝘆 → 𝗔𝗴𝗲𝗻𝘁𝗶𝗰 𝗔𝗜-𝗱𝗿𝗶𝘃𝗲𝗻 𝗰𝗹𝗼𝘂𝗱 𝗶𝗻𝗳𝗿𝗮𝘀𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲. The result? Zero-touch, self-managing environments where AI agents handle failures, optimize costs, and secure systems in real time.  𝗪𝗵𝗮𝘁’𝘀 𝘁𝗵𝗲 𝗺𝗼𝘀𝘁 𝗲𝘅𝗰𝗶𝘁𝗶𝗻𝗴 𝗔𝗜-𝗱𝗿𝗶𝘃𝗲𝗻 𝗰𝗹𝗼𝘂𝗱 𝗶𝗻𝗻𝗼𝘃𝗮𝘁𝗶𝗼𝗻 𝘆𝗼𝘂’𝘃𝗲 𝘀𝗲𝗲𝗻 𝗿𝗲𝗰𝗲𝗻𝘁𝗹𝘆?

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.

Atlassian has been fully distributed for almost five years. We don’t have all the answers, but we’ve learned a lot about how to keep teams thriving across time zones—and we’re applying those insights every day.  ➡️ Asynchronous work: Async tools are at the core of how we operate. Confluence is our virtual hub where we share stories, celebrate new hires, and collaborate effortlessly. We also use Loom to share videos and give feedback on our own time—avoiding those dreaded “this could have been an email” moments. In fact, we’ve saved nearly half a million meetings using Loom! ➡️ Designing workdays: We’ve learned to structure workdays for focus, collaboration, and meetings (only when absolutely necessary). Teams work across no more than two time zones, ensuring at least four hours of overlap to get things done together. ➡️ Intentional connection: Data shows that real connection happens when teams meet regularly—not sporadically in an office. We provide Intentional Togetherness Gatherings (ITGs), curated experiences, and focused in-person time to collaborate. ➡️ Adapting for different needs: It’s not one-size-fits-all. For example, new hires and grads often benefit from more frequent in-person meetups, so we make sure to offer opportunities for them to connect early on. https://lnkd.in/g2sSbe3v

Just out in Harvard Business Review, summary of the Hybrid Experiment results and lessons on how to make hybrid succeed. Experiment: randomize 1600 graduate employees in marketing, finance, accounting and engineering at Trip.com into 5-days a week in office, or 3-days a week in office and 2-days a week WFH. Analyzed 2 years of data. Two key results A) Hybrid and fully-in-office showed no differences in productivity, performance review grade, promotion, learning or innovation. B) Hybrid had a higher satisfaction rate, and 35% lower attrition. Quit-rate reductions were largest for female employees. Four managerial lessons 1) Hybrid needs a strong performance management system so managers don’t need to hover over employees at their desks to check their progress. Trip.com had an extensive performance review process every six months. 2) Coordinate in-office days at the team or company level. Schedule clarity prevents the frustration of coming to an empty office only to participate in Zoom calls. Trip.com coordinated WFH on Wednesday and Friday. 3) Having leadership buy-in is critical (as with most management practices). Trip.com’s CEO and C-suite all support the hybrid policy. 4) A/B test new policies (as well as products) if possible. Often new policies turn out to be unexpectedly profitable. Trip.com made millions of dollars more profits from hybrid by cutting expensive turnover.

Thank you, Google. You just open-sourced a single CLI for all of Google Workspace and it's built for both humans and AI agents. npm install -g @googleworkspace/cli What it does: → One command-line tool for Drive, Gmail, Calendar, Sheets, Docs, and every Workspace API → Zero boilerplate. Structured JSON output. Auto-pagination. → Reads Google's Discovery Service at runtime — when Google adds a new API endpoint, the CLI picks it up automatically → Ships with 100+ Agent Skills so your LLM can manage Workspace without custom tooling → Built-in MCP server for Claude Desktop, Gemini CLI, VS Code, and any MCP-compatible client → Model Armor integration to scan responses for prompt injection before they reach your agent This is a big deal for anyone building AI agents that interact with Google Workspace (everyone?) No more writing custom API wrappers. No more maintaining brittle integrations. One tool. Every service. Structured output ready for agents. The repo is Apache-2.0 licensed and under active development.

Women are changing their gender to "male" on LinkedIn to prove the algorithm is biased. And it's working. Visibility shouldn’t require women to sound less like ourselves. Yet here we are. All over my feed this week, women are changing their gender markers to “prove” a point – and the results are loud, undeniable, and honestly painful. Engagement jumps. Comments triple. Reach explodes. The bias becomes visible in real time. And I get it. It’s important work. It quantifies what many of us have felt for years but couldn’t “prove” in a way algorithms take seriously. Here’s the tension I can’t shake: If we keep performing masculinity to be heard… what are we training the algorithm to believe about our real voices? Because short-term proof comes with long-term consequences: Maybe.... → We risk signalling to the platform that feminine-coded communication isn’t “valuable” → Diluting the diversity the algorithm should be learning to amplify → We risk becoming attached to the virality instead of the message → We slowly lose the nuance, softness, depth, and empathy many women naturally write with → We normalize the idea that adaptation is the only survival strategy And that’s a cost I’m not willing to ignore. This isn’t about calling out women experimenting. It’s about asking a critical question: Are we documenting the bias… or accidentally reinforcing it? There has to be another way.... ....a better way. One that strengthens our collective voice instead of bending it. Rachael (whose article sparked this reflection) said something powerful: “Instead we could all find ten women’s posts per day – follow them, engage, and amplify their voices.” And dare I add – resharing their content with the same energy we’re giving this experiment? Maybe that’s the real secret sauce. Imagine that. Thousands of us intentionally raising the volume of women who are already writing with excellence, insight, and emotional intelligence. We are not gaming the system. We are reshaping it – one amplified voice at a time. And perhaps it’s time LinkedIn joined the conversation. So here’s my stance: We don’t beat bias by becoming less of ourselves. We beat it by being so visible, amplified, united, and supported – the algorithm has no choice but to learn. This conversation isn’t about virality. It’s about voice. And how we choose to protect it. What do you think? Is there a better way forward than swapping genders just to be heard? I’d love to hear thoughtful perspectives – especially from women navigating this tension in real time.

Do you sometimes feel frustration, as you are building a product to get the management off your back, rather than address the users? Here are 6 ways to become user-centric again: 1) Prioritize in a transparent way This is a great place to start. If your backlog is prioritized based on data and potential opportunity, risk, and cost, it will be easier to put forth user-centric initiatives ahead of those that came from upstairs. At the very least, you will have a good basis for an educated discussion. 2) Utilize users' perspective using user stories and personas If your team understands the users and their problems, it will be easier to craft something great that will later appeal to the same users. Just keep up the empathy of creating something by people for other people, and not get some metric magically go up! 3) Make user feedback public If everyone in the company can see the themes that come from user feedback, it will be way harder to ignore it in favor of some corporate nonsense. Let those voices be heard by everyone! 4) Have the NPS and user ratings at the forefront The same goes for a single metric representing the general product sentiment. If the number is low or, worse, is going down and everyone can see that, the responsible Product Manager has to react. 5) Focus on your product goals Now, upstairs mandates might not be the only distraction you face when trying to improve your product. To survive them all, focus on one thing: your product goals. This will allow you to demonstrate you are doing what you are asked for and you can use user feedback and points 1-4 to pursue those goals. Thus, it's like killing 2 birds with 1 stone. However, you can also simply: 6) Have the confidence to say "No" Not all company/legal/management requests can be ignored. Sometimes changing the law or a wider company initiative will require you to comply and that is OK! However, there will also be times when someone will try to force your compliance. This is where you need to be confident, and exercise your Product Manager's independence, especially when there is no data to support a specific request. There you go! My 6 ways you can become a user-centric Product Manager. How about you? Do you address your users or your management first and foremost when developing your product? Sound off in the comments! #productmanagement #productmanager #usercentricity

How do you build a long-lasting career as a freelancer, instead of it being a stopgap or short-lived side hustle? For starters, optimize for interesting, focus on financial longevity, and diversify your offerings. Passing the decade milestone as a freelancer, I’ve identified what’s helped to sustain my interest in the work, continue to drive demand from clients, and other insights that have made self-employment a viable, rewarding path. In my latest for Fast Company, I explore lessons in building a long-term practice based on what’s proven effective for myself and other freelancers. ➤ Niche down strategically so it’s clear what you offer, the types of clients you serve, and what’s unique about your expertise. You can’t be everything for everyone, get specific instead. ➤ Consistently share your ideas publicly, whether through podcasting, a newsletter, or otherwise so clients find you based on your insightful ideas and solutions. ➤ Craft a deployable network. According to Lola Bakare, build relationships with colleagues across sectors, and when the time is right, deploy their willingness to support you. “Be very willing to not just ask for help, but surround yourself in help,” she suggests. You can’t just rely on yourself to make it happen. ➤ Secure social proof. “Over-index on social proof. Early in your career, it's essential to ensure you're being taken seriously,” advises Dorie Clark. “The best way to do this is to gather as much social proof - i.e., easily understood and verifiable symbols of your competence - as quickly as possible.” ➤ Prioritize reliability. “This doesn't mean you have to perform perfectly. It means that you need to show that you value the relationship, and have appreciation and respect for clients who've hired you. That means doing what you've committed to doing, when you've committed to do it, and ensuring open communication around that process,” says Melissa Doman, M.A. ➤ Commit to yearly growth by setting aside time annually to go in-depth on a new learning opportunity that allows you to explore a new area of your business or expand upon an existing offering. ➤ Learn from missteps. “We will all make mistakes, and in my early years, I made a costly error when I relied on a verbal agreement with a friend. That experience taught me the indispensable value of contracts. By clearly defining what our services include—and do not include—we eliminate confusion and potential disputes. It's a preventive measure that has saved me from challenging clients,” added Nicte Cuevas. ➤ Pass on misaligned work. “Many freelancers burn out by working for difficult clients at low rates and then quit. They do this because they need the work — any work. If you can help it, don’t go full-time until you have enough savings to confidently turn work down. Even better, don’t go full-time until your business is threatening to interfere with your job,” suggests Josh Garofalo. Read the article below for all the lessons in more detail. ⭐

Is your leadership's management philosophy stuck in the 1960s? Let's redefine it: Leadership by Being Engaged. The concept of "management by walking around" came from Bill Hewlett and Dave Packard (HP founders) in the 1960s, popularized by Tom Peters in 1982, and gets used today to describe what's missing in #remote work. "The expected benefit: by random sampling of events or employee discussions, managers are more likely to facilitate improvements to the morale, sense of purpose, productivity and and quality... compared to remaining in a specific office area, or the delivery of status reports." The literal concept doesn't work if your managers have people who are working in multiple locations, now the majority case. 60 to 80% of all "enterprise" company managers now have #distributed teams. 100% of Fortune 500 Execs have teams that are #distributed today, according to Atlassian (kudos Molly Sands, PhD). #RTO mandates rooted in this philosophy are trying to return to a world that no longer exists. Leaders need a both/and approach. Get employees together to jump-start #belonging, and build better #culture and #performance by being involved in the digital #collaboration tools that your teams use every day. Let's redefine a philosophy rooted in co-location into one for the #digital age. Four starting points for leaders looking to get digitally engaged: 🔸 Increase transparency. Internal transparency around clear goals and realistic progress against them drives focus on outcomes, and builds trust. 🔸 Get engaged in the work. Execs need to stop saying "Teams/Slack etc are for the kids; you'll find me in email" and get into the tools people use every day to work through account issues, project updates, and problem solving. 🔸 Participate in digital communities. Social forums at work build belonging. That cuts across everything from an Abilities ERG to Sneakerheads. Finding community at work boosts retention; even leaders need to find that. 🔸 Get a reverse mentor. Being available and engaged digitally can feel foreign as a leader, and initially scary to a team. Find a digital native in your organization who can coach you! What's your take? Retire the phrase, or revive an important concept?

AI Innovation in HR: Listening to People at Scale Anthropic has piloted Interviewer, a new AI research tool powered by the Claude model that autonomously designs, conducts, and analyzes in-depth, qualitative interviews at scale. This tool is an example of how AI will change the methodology of collecting organizational insights. Key Features: 1) Adaptive Conversations: Claude Interviewer can engage employees in natural, 10–15 minute chats, dynamically adapting questions based on responses, simulating a human interviewer. 2) Achieving Scale: Conduct thousands of detailed qualitative interviews quickly and parallel, significantly reducing the cost and time limitations of traditional methods. 3) Full Pipeline Management: The solution manages the entire process, from initial planning to automatic thematic analysis of transcripts. This autonomous execution allows for outcomes to feed back into AI models to propose follow up actions. The power of scalable qualitative data is highly relevant for HR: 1. Performance Management: Collect deep insights on team dynamics, leadership effectiveness, and skill gaps. 2. Engagement Research: Move beyond survey scores to truly understand the contextual factors driving satisfaction and retention. 3. Job Analysis & Evaluation: Accurately map complex roles by gathering detailed data from incumbents on evolving responsibilities and workflows. Anthropic tested Interviewer on 1,250 professionals, demonstrating its capacity to deliver genuine, scalable qualitative perspectives necessary for informed strategic decision-making. As similar tools become standard, data privacy and control will be key considerations for adoption. See Anthropic publication. https://lnkd.in/eqPVrBqX