Latest news with #AgurJõgi
Forbes
30-07-2025
- Business
- Forbes
Considering A Self-Healing Network? Leverage These Expert Tips
Self-healing networks—systems that automatically detect, diagnose and fix network issues without human intervention—promise a future of near-zero downtime, automated fault recovery and more resilient digital infrastructure. But for all their upsides, they're far from a plug-and-play solution. Companies exploring this technology should take the time to understand the complexity, investment and cultural shifts required to do it right. Below, members of Forbes Technology Council share their top advice for businesses evaluating self-healing networks. Their insights highlight not only how to unlock the technology's full potential, but also what pitfalls to avoid when implementing and managing these systems at scale. 1. Rethink And Define Your Network Architecture While a deep tech explanation is probably expected, in reality, the greatest value of this exercise is that the company has to rethink and define the architecture of its network solution from scratch. Through this exercise, companies discover opportunities to mitigate business risks, improving service quality and efficiency. Self-healing is just one aspect when the exercise concludes. - Agur Jõgi, Pipedrive 2. Adopt AES-Based Encryption As networks evolve to become autonomous and self-healing, AES-based encryption is no longer optional—it's essential. Self-repairing systems without robust encryption risk recovering into a compromised state. AES, with its proven strength and efficiency, ensures that resilience is matched by the security needed for truly trusted infrastructure. - Srinivas Shekar, Pantherun Technologies Forbes Technology Council is an invitation-only community for world-class CIOs, CTOs and technology executives. Do I qualify? 3. Invest In Monitoring And Automation Up Front One important thing to know is that self-healing networks reduce downtime but require upfront investment in intelligent monitoring and automation tools. The benefit? Long-term cost savings, fewer outages and faster recovery—but only if the network is designed with accurate telemetry and adaptive response rules from the start. - Sanjoy Sarkar, First Citizens Bank 4. Establish A Mature Infrastructure And Well-Defined Policies A self-healing network boosts uptime and reduces manual intervention, but success hinges on having a mature infrastructure and well-defined policies. Without proper configuration, automated responses can misfire. Businesses must invest in setup, monitoring and governance to truly benefit from a self-healing network's resilience and automation. - Hemanth Volikatla, SAP America Inc. 5. Understand That Full Autonomy Is Still Years Away A fully self-healing network that detects, diagnoses and fixes network issues without any human involvement is still years away. But low-code/no-code automation platforms and AI will make those processes faster and easier while taking incremental steps toward self-healing. Make sure these AI and automation tools have access to live network data—it makes everything much more accurate. - Song Pang, NetBrain Technologies 6. Ensure Proper Design And Governance One important thing a business should know when considering a self-healing network is that while it significantly reduces downtime and automates fault recovery, it requires careful initial setup, continuous monitoring and robust security policies. Without proper design and governance, automated responses could unintentionally escalate issues or create security gaps. - Bhupendra Singh, Marriott International 7. Prioritize Visibility A self-healing network doesn't just fix problems; it hides them. That's powerful—and risky. You'll reduce downtime, yes, but if you stop monitoring root causes, small issues can quietly become structural. Invest in visibility as much as automation or you'll be flying blind with autopilot on. - Oleg Sadikov, DeviQA 8. Take Advantage Of Continuous Learning Self-healing networks excel at executing playbooks for known issues, but their true strength lies in continuous learning. Businesses must understand that it's not a set-and-forget system—ongoing reinforcement learning is key to adapting to new failures and evolving the system's intelligence over time. - Kiran Patibandla 9. Start With Clean Data And A Clear Plan Self-healing networks sound like magic, but the real power lies in how you build them. They don't just fix problems; they free your teams to focus on what matters. But it takes more than tech. You need clean data, smart automation and a clear plan. The leaders who get it right aren't just preventing downtime—they're building a smarter, calmer future. - Aditya Vikram Kashyap, Morgan Stanley 10. Focus On Observability And Clear Failover Rules Self-healing networks are great for cutting downtime, but here's the catch: they're complex. You'll need top-notch observability and crystal-clear failover rules, because a bad setup can trigger a chain reaction of failures. But if you get it right, you'll see a big jump in resilience and a drop in operating costs thanks to quick, automated fixes. - Rohit Ayyagari, SunRun 11. Make Sure You Have The Necessary Infrastructure And Expertise One important thing a business should know is that while a self-healing network can improve uptime and reduce manual intervention, initial implementation can be complex and resource-intensive. Businesses must ensure they have the necessary infrastructure and expertise for proper integration, as the setup phase can require significant time and investment. - Sandeep Telu, Infosys Consulting 12. Reduce Risk Through Proper Configuration And Zero-Trust Principles A self-healing network isn't a plug-and-play solution—it requires disciplined IT processes, visibility and cybersecurity alignment. While it can reduce downtime and automate recovery, without proper configuration and zero-trust principles, it may mask deeper vulnerabilities instead of fixing them. - Scott Alldridge, IP Services 13. Assess External Dependencies A self-healing network provides greater resilience, stability and consistency of service, but it comes with added implementation costs. Businesses should assess their dependencies on external vendors and manage the potential impact of those dependencies by establishing robust SLOs, SLIs and SLAs. Any dependent, business-critical services should be able to meet the desired objectives in order to fully take advantage of the benefits of a self-healing network. - Abhi Shimpi 14. Consider Skills Gaps Businesses should consider the skills gap challenge. Self-healing networks cut downtime, but many firms lack AI-skilled staff to manage them. Nokia's training for AT&T's 5G rollout shows the way. Upskill teams to unlock resilience, ensuring AI-driven networks don't outpace expertise. - Durga Krishnamoorthy, Cognizant Technology Solutions 15. Invest In Clean Telemetry, Secure Automation And Identity-Aware Enforcement Self-healing networks don't just fix faults; they help encode better judgment. If that logic is flawed, you automate failure pretty quickly. Invest first in clean telemetry, secure automation and identity-aware enforcement. It's still key to know what the common issues are. Healing is definitely power, but only alongside visibility, auditability and controls that know who triggered what and why. - Dan Sorensen 16. Incorporate Clear Identity And Access Governance A self-healing network can enhance security, but without clear identity and access governance, it risks automating the wrong actions. Integrating knowledge graphs and digital twins allows organizations to simulate identity relationships and access paths. This ensures that corrective actions are context-aware and don't disrupt legitimate access. - Craig Davies, Gathid 17. Build In Root-Cause Logging From what I have seen in real-world systems, self-healing networks sound ideal but can mask deeper issues if not designed with transparency. They should not just fix problems silently, but log root causes clearly. Long-term resilience comes from learning, not just recovery. - Gopinath Kathiresan, Apple Inc. 18. Be Ready For The Impact On Engineers' Workloads Auditing the system will increase the workload for the engineers who maintain it. While the overall effort may ultimately save time and money, this is not a system you can simply 'set and forget.' It's essential to understand the processes of detection, patching and healing as well as the resulting outcomes. More often than not, automated systems can veer off course without proper human oversight. - WaiJe Coler, InfoTracer 19. Update Your KPIs Before investing, consider how your business measures success. Self-healing networks shift the focus from reacting to predicting, so KPIs must evolve. Traditional metrics like 'incident count' may decline, with value now lying in 'prevented failures.' Without redefining performance metrics, you risk misjudging progress. - Roman Vinogradov, Improvado 20. Emphasize Prevention Over Repair Prevention is more powerful than repair. Investing in self-healing infrastructure isn't just about crisis management; it's about sustained performance, stress resistance and long-term system reliability. A well-architected self-healing network rarely experiences catastrophic failure. It is an important layer in a broader strategy, one that relies on smart design and the people behind the scenes. - Trisha Swift, Mula Integrative Health & Wellness
Forbes
17-07-2025
- Business
- Forbes
Growing Excellence In AI: Advice For Junior, Mid And Senior Engineers
Agur Jõgi, CTO of Pipedrive and expert in scaling technology and organizations. Experienced as an innovator, founder and C-level manager. AI acceptance in the enterprise is growing. More AI features are being introduced, targeting ever-sharper use cases. Even more importantly, AI projects—which were initially slow to show value—are showing ROI. With any new technology, early adopters tend to focus on using it to build isolated features. But it takes time for organizations to move beyond novelty and truly integrate new tech into solutions that solve real customer problems and deliver a seamless, end-to-end experience. That evolution is valuable, but it often comes with baggage. Software engineering job listings have decreased. Thousands have been laid off across the tech sector, and many blame AI in part, though economic, geopolitical and national productivity issues are all affecting businesses in incredibly significant ways. This is why it's vital that engineers at each, every and any stage of their career must understand how best to leverage AI within their roles. They must also stack skills to build a unique personal offering and cultivate the right orientation to showcase their value rather than what they 'do.' It's time to orient to outcomes over the role, overcoming any discomfort and thinking about work in a way that introspective high performers have been doing forever. Junior engineers may feel like their formal education is behind them, but in reality, their learning is just beginning. Technology evolves rapidly, and staying current means continuously developing new skills, exploring emerging tools and techniques, and pursuing ongoing certifications. Rather than seeing this as a burden, it should be viewed as an exciting opportunity—because being a technologist means committing to lifelong learning in a field that's constantly being reshaped. Ask any senior engineer and they'll tell you—they once trained on platforms and languages that junior engineers today may have never encountered. The tools of the trade evolve quickly, and it's only a matter of time before today's technologies are replaced or radically transformed. That's why continuous learning isn't optional—it's essential. Stay curious, stay motivated and keep exploring new ways to combine your skills. Focus on building expertise in areas that deliver real value, but understand that your toolkit will need to expand over time. Right now, AI is one of those pivotal tools—whether you're building with it or simply using it, it's crucial to understand how it works and take ownership of your role in its development. With solid experience and training behind you—and likely a clear trajectory within your career—one of the biggest mistakes at the mid-level is assuming you've learned all there is to know. As the saying goes, 'The best time to plant a tree was 20 years ago; the second-best time is now.' It's not uncommon for ongoing education or the drive for innovation to slow at this stage. That's understandable. By now, you've likely taken on greater responsibilities and become more attuned to business goals, recognizing how closely your success is tied to helping achieve them. This makes it the ideal moment to think about the specialist roles and unique contributions you could make within your organization. You've gained deep expertise, not just in your technical domain, but also in the workflows and culture of your company and sector. Use that knowledge to shape your next steps through targeted training, job shadowing or mentorship—whether giving or receiving it. And don't hesitate to make your value visible. Demonstrate your impact and actively live up to it. At the senior level, your greatest asset is accumulated experience, and it must be applied in ways that are both strategic and tangible. While you may not need to dive deep into every new technology like a practitioner, staying current is critical. You're expected to evaluate emerging tools and trends, understand their strategic implications and spot the familiar warning signs of hype, risk or potential missteps. In today's AI-driven landscape, seniority isn't defined by tenure—it's defined by impact. Senior engineers navigate ambiguity, influence outcomes and help others thrive. With AI increasingly handling execution-level tasks, the irreplaceable value lies in deciding what to build, why it matters and how to avoid common mistakes. That's where your experience makes the difference. You should champion outcome-oriented thinking. Ask: How does this serve the business, the user, the customer? Use your expertise to guide architectural decisions, assess risk and plan for the long term. AI may accelerate delivery, but it's up to senior engineers to set the direction. Finally, be a mentor. Change can be unsettling. Senior engineers are in a unique position to bring empathy and clarity, offering support, sharing context and leading by example. Create space for AI pair programming and foster a culture of peer learning. Help others grow not just by solving problems, but by framing them through stories that communicate value, not just output. In short, your role is no longer just to fix—it's to design frameworks. Alongside enthusiasm and a plan for adoption and skill development, engineering talent should also reflect on what to let go of. For instance, the traditional emphasis on perfectionism in code quality may start to shift. As speed, iteration and responsiveness become more valuable—and as AI tooling increasingly handles testing, code reviews and other "shift left" tasks—the expectation that humans must own every line of code may no longer hold. In some cases, responsibility for certain tasks may shift to AI tools or be distributed across teams differently than before. It's also worth acknowledging a deeply human truth: many of us crave stability. Yet in both business and technology, change is constant—only now, the pace and scale are more visible. The key is to develop agility in mindset, not just in processes. Change isn't just risk—it's also opportunity. Forbes Technology Council is an invitation-only community for world-class CIOs, CTOs and technology executives. Do I qualify?
Forbes
18-06-2025
- Business
- Forbes
Talent Vs. Toil: Taking Care Of Business
Agur Jõgi, CTO of Pipedrive and expert in scaling technology and organizations. Experienced as an innovator, founder and C-level manager. getty One of the lenses through which tech leaders view their plans for success should be balancing talent and tedium. That is, the skills, attitudes and capabilities of your team versus the toil they must overcome in their day-to-day activities. One of the major keywords you've probably already flashed up is "burnout." Most of us can't maintain our best focus and output over either a long or acutely stressful period. The easy analogy is that of an athlete. A 100-meter sprinter trains for their event, and they may well be pretty good in a longer race. However, they haven't prepared for a marathon—mentally or physically. Tech workers are—either naturally or by career development and practice—primed for certain types of roles and responsibilities. If these are inconsistent, too onerous or often simply too tedious, then attention can slip, and the risk of burnout or disengagement rises. For teams with complex and mentally taxing tech roles that are facing mercurial economic pressures and rapidly changing tools and products, it helps to have a methodical approach to monitoring and supporting the right working environment. Time And Motion, Toil And Team In the mid-20th century, time-and-motion studies became a big business efficiency technique for improving work methods. Factories (or anywhere where there was physical motion, such as assembly lines) were increasingly optimized for better business efficiency. This kind of thinking influenced businesses of all kinds as it evolved, and the IT industry may be the most obvious inheritor of this style of process management. It would be reasonable to say workers didn't tend to get the better end of the drive for efficiency in times past. Speak of "the factory floor" or an "assembly line worker," and many people may have a bias that such working practices make a person a cog rather than an active agent. It's now well understood that employee experience and productivity are known to be entwined. Only leaders who keep their finger on the pulse of the holistic employee and business experience will keep their project and business performance in the green over the medium to long term. Leaders must understand the processes of their teams and be on hand to offer the benefit of experience. They must also advocate if the cost of toil and poor experience ever degrades their ability to deliver on business goals. KPIs, OKRs and metrics define the company goals and deliverables, but these must be translated into "human-readable" behaviors and processes to avoid work becoming a rote lever-pulling exercise. Starting Right And Continuing The Same Way Culture begins in many places, one of them at the point of hiring. Right from the get-go, find people during recruiting who know why they want to work for this company, fit in and strengthen the existing culture. A person with the right "why" will collaborate on the "how." Of course, it's good sense to offer great pay and benefits to go with a great culture as part of the whole employee experience. Equally importantly, choose people who want to develop and want to do it themselves rather than waiting for someone to develop them. Showing agency and a future orientation is a great way for employees to show they can overcome challenges, show resilience and positively support their teams. From there, every manager has a major task—to ensure the continuous professional and cultural development of their people and help out those whose desire for development has stopped. As a guide, my team members know that if they decide to leave, they will generally be trained and experienced enough to get a job offer from the market that's a level higher. Other companies will see a mid-level Pipedrive developer as a new senior as a result of our culture and drive for individual development and excellence. Experience Supporting Excellence The "greed is good/work 18 hours a day in the boiler room" style of management doesn't build a culture of excellence or long-term success. Collaboration and trust are what's needed to unlock really compounding strength and value. That's not to say the best teams don't have some high targets, tight deadlines or some healthy stress. That's how all athletes and professionals maintain a winning mindset and overcome challenges. What's needed is a culture of trust and a great working experience that supports teams in delivering their best over sustained periods. Working experience is very hard to get perfect. It's probably not perfect. People and their varied circumstances are always changing. Leaders at every level must regularly consider the kind of environment they want for their talent and make the right choices to balance experience, resources and expediency to stay on top of the challenge. Leaders must avoid "setting and forgetting." Culture changes with every act made and impression received. A poor hire, the wrong decision, a disruptive customer demand—anything can change it. Culture is made up of so many parts that it doesn't take much to send it down a different path. The mission/vision set from the top is a great start, but it must be backed by evidence that it's taken seriously and meaningfully across the majority of working activities. Taking Care Of Business "Taking care of business" in terms of making a great working experience means tending to factors like employee autonomy and empowerment. Merely taking a temperature check as part of an annual review cycle is a great way to uncover problems a long time after they should have been solved. Some areas, like recognition and appreciation, don't require much more than a thoughtful and empathetic approach to management. Toil must be transformed into meaningful work, and taking care of business doesn't merely refer to delivering on company goals. The company is an organization of people collectively. When they pull together, they grow collectively. When they lose the rhythm, that growth is hampered. Forbes Technology Council is an invitation-only community for world-class CIOs, CTOs and technology executives. Do I qualify?
