When you are building a business, there are a lot of things to think about, including the idea itself, the product, the team, and the budget. However, there is also one aspect that matters, but its value is often underestimated. It is PR. In this episode of the Innovantage podcast, its host and Sigli CBDO Max Golikov and his guest Remco Janssen are talking about the role of media coverage in the startups’ success. And that’s not the only point discussed. AI, tech innovation, and regulation in Europe are among other topics that you can learn about in this episode.Remco’s professional journey began just after the dot-com bubble burst in 2001. When he was a student, he started working as a customer service agent at a food-ordering website. Later, he left college to work full-time at the startup and took on everything from customer service and sales to copywriting. However, the startup was acquired by a bigger company, and the Amsterdam office was moved to Brussels. Remco chose to finish his studies. Then, he became a sports journalist. But the role was pretty demanding, with long hours and weekends spent at football matches. Looking for a better work-life balance, he decided to change his professional path and started a career in tech PR.By 2008-2009, he was deeply involved in both the Dutch and Austrian startup scenes and was helping fast-growing tech companies shape their public image. In 2014, he launched a simple WordPress blog dubbed Silicon Canals (a nod to Silicon Valley and canals of Amsterdam) to cover the updates in the startup world. It started in Dutch, and posts were quite infrequent at that time.Now, 11 years later, Silicon Canals is one of Europe's leading publications covering startups. Why startups avoid media and why it is a mistakeMany startups believe they don’t have the time, money, or resources for PR, especially in the early stages. They are focused on building the product (and of course, that’s essential). But according to Remco, such a mindset can hold them back.Coming from the Netherlands, he understands the cultural hesitation among startup founders in Europe. Unlike Americans, people in Europe are not accustomed to promoting themselves. Nevertheless, this modesty shouldn’t stop founders from thinking about media, PR, and marketing early on.It is not necessary to go straight to the biggest tech media on day one. It will be more sensible to start small. For example, it can be a good idea to write articles for a blog, launch a podcast, get invited to one, or just post regularly on LinkedIn or Instagram. Building your media presence starts with quite simple steps.Establishing visibility early helps position a startup for faster growth. By the time product-market fit is achieved or early funding rounds are raised, the existing media presence becomes a valuable asset. At this moment, it will make sense to reach out to bigger tech media and news outlets.In multilingual markets like Belgium, for example, startups need to prepare press releases in English, Dutch, and French. This adds complexity. But it is vital for reaching the right audiences. In contrast, the Netherlands often requires only Dutch, with English content used for broader coverage.Instead of avoiding PR due to any challenges, founders should build a media strategy into the company’s DNA from the first steps of their business journey. Today, in different regions, there are specialized PR agencies tailored to early-stage tech startups that can offer targeted support and guidance.Moreover, creating a basic PR and marketing plan has become quite simple. Such tools as ChatGPT or EU-based alternatives such as Le Chat from Mistral can help founders quickly define their messaging, draft content, and plan outreach strategies in just a few hours.Why early-stage startups must build social proofFor startups, building social proof isn’t optional. It’s essential. It plays a critical role in two key areas: fundraising and customer acquisition.In their early days, most startups rely on their inner circle to find their first customers. These are people who already know the founders or the company. But once product-market fit begins to take shape, that network of contacts is not enough. Then, startups enter a much harder phase. They need to reach cold prospects and unfamiliar buyers.At that point, potential customers and investors will almost certainly look up the company on the internet or have AI tools do it for them. If there is no media coverage, no podcast appearances, no LinkedIn activity, and no visible sign of expertise, the likelihood of scheduling a meeting or closing a deal drops dramatically.Startups need to be discoverable. Especially for bootstrapped companies or those in competitive sectors like AI, visibility can make a huge difference.The same principle applies to fundraising. Investors are far more likely to respond to startups that have been visible in the ecosystem and have already demonstrated value. Social proof always accelerates trust.What about negative PR?Many startup founders may be worried about the risks of a negative media reputation. However, as Remco explained, in reality, negative PR is rare unless a company is engaging in fraud or unethical behavior. Most early-stage startups aren’t under that kind of scrutiny. In fact, in the vast majority of cases, any media attention generates curiosity, which can lead to discovery, trial, and even growth.Founders shouldn’t fear press exposure. The real danger lies not in negative coverage, but in no presence at all. When a startup is invisible, it’s more likely to be associated with bad actors who make headlines on a regular basis. If a legitimate company has no visible track record, and only questionable projects do, public perception can blur the line between them.This is where high-quality, consistent PR becomes critical. Especially for investors conducting due diligence, clear media coverage helps distinguish legitimate startups from those that don’t deserve their attention.Common misconceptions and mistakes startup founders makeAccording to Remco, one common pitfall among startup founders is a sense of entitlement. While confidence is essential in entrepreneurship, it can sometimes transform into narcissism.This inflated self-perception often leads founders to view the media as a marketing tool rather than an independent voice. However, journalists are not obligated to show a company in a specific light. When founders want to earn media coverage through press releases or pitches, they should understand that journalists maintain editorial independence. They may reference competitors, raise critical points, or highlight historical parallels, even those that founders may prefer to hide. Control over the narrative should come only through paid content, such as sponsored articles or native advertising.Remco mentioned a recent incident with a founder from a top incubator who reacted aggressively when a photo published alongside a story wasn’t taken down upon request. The founder cited GDPR. However, media outlets operate under press laws that prioritize freedom of information and speech.The key takeaway here is that media coverage is not a courtesy. Journalists don’t work just to promote companies. They report stories they believe are interesting to the public. Remco deeply believes in journalism as a pillar of democracy. While some may say that tech coverage doesn’t have any relation to politics, European tech now plays a critical role in preserving democratic values. As geopolitical tensions rise, Europe can no longer afford to be dependent on foreign tech.To safeguard its future, Europe must invest in its own innovation, from chips, drones, and defense tech to cloud infrastructure. This isn’t just about sovereignty. It’s also about ensuring that European data is governed by democratic standards.Regulation plays a crucial part in that. While GDPR may not always apply to media, it is a powerful framework that protects individual rights. Major US-based tech firms continue to violate these rights. That’s why Europe needs to build its companies with the key democratic values in mind.Regulation and innovation: Where is the right balance?Max described regulation as a necessary framework that guides how technologies should be applied, where their limits lie, and where they add the most value. Regulation, in his view, helps define responsible innovation.However, he also acknowledged the opposing argument: excessive regulation can become a barrier to growth.In a capitalist system where profit often defines success, this raises a controversial question: Does looser regulation fuel innovation, or does it just create a situation where data and rights are less protected?Remco emphasized that, in his opinion, Europe is fundamentally a democratic society, not just a capitalist one. In a democracy, the goal is to protect all citizens equally, while capitalism often focuses solely on winners and losers.Remco compared Europe with other regions where capitalism has led to power being concentrated in the hands of a few. Such a situation weakens public institutions and increases inequality. In the European democratic system, founders should look beyond wealth creation or investor returns. They can help shape the future of European society, which comes with a responsibility to uphold democratic values.He acknowledged that bureaucracy and fragmented laws across the EU can slow progress. But the solution isn’t to abandon regulation. The best way to address such issues is to coordinate regulation better. Ethical innovation and strong governance are where Europe can lead. The European startup advantageOne of Europe’s persistent challenges in tech innovation is early-stage funding. Pension funds, for example, often invest heavily in US markets or traditional banks instead of supporting local startups. Redirecting capital into European tech could generate strong returns and power the region’s innovation ecosystem.Despite this funding gap, Europe has a unique strength. The region is actively building sustainable businesses without relying on massive investment. Unlike the US model of hyper-growth, European founders often focus on profitability from the start. This mindset has roots in the region’s long tradition of family-owned, multi-generational companies.With the rise of AI, this lean approach is proving even more viable. Many bootstrapped startups are reaching significant revenue milestones without raising large rounds. Instead of concentrating on IPOs or mega funding rounds, more European startups are building long-term, profitable businesses. They are not unicorns. They are zebras. And in today’s capital-efficient landscape, this may be a much smarter choice.Why content is the most powerful growth toolIn an increasingly crowded and complex tech landscape, content remains one of the most effective tools for growth (especially when its quality is high). According to Remco, founders should treat content as a core part of their strategy.Content builds credibility, fosters learning, and creates long-term value. Many successful careers and businesses, including those in tech journalism, have been launched through consistent blogging and publishing. Becoming your own media channel (articles, podcasts, or newsletters) can grow your network and even generate new business opportunities.AI, jobs, and the changing nature of workThe hype around AI is still strong, and with it comes concern about mass job displacement. These fears are especially strong in the tech space.While AI will likely reduce the need for junior developers doing repetitive work, it won’t replace skilled engineers. Nevertheless, here comes the next question: How will future seniors gain experience without junior roles? The industry must rethink the learning pipeline to ensure talent can still grow.AI-powered personal learning could play a crucial role here. Personalized tutors that adapt to each learner’s pace could accelerate skill development. This can be highly valuable for roles that now require faster onboarding and higher adaptability.Instead of eliminating jobs, AI may enhance them. Apart from this, such a shift calls for a reassessment of how we work. Many jobs still follow outdated 9-to-5 patterns. In a tech-driven knowledge economy, AI could encourage the introduction of more flexible and balanced work lives.Why deep tech is Europe’s opportunityRemco mentioned that Europe has a real chance to lead in deep tech. As AI is accelerating and energy consumption is increasing, there is a growing need for innovation in infrastructure to address pressing climate change problems. Quantum computing, photonics, and ultra-efficient data centers are some of the possible solutions.But it’s not just about AI. Europe must also tackle fundamental challenges, including sustainable food production, land use, nitrogen reduction, and energy efficiency. Apart from this, innovation in defense is required as well. Fortunately, the European Commission and national governments are beginning to align on this vision. Many startups are shifting away from venture capital. But deep tech still requires substantial early-stage funding. These companies often face long runways, sometimes taking 10 to 12 years to reach maturity. This makes them look not very attractive in today’s risk-averse market.That’s precisely why Europe’s pension funds, family offices, and private investors need to enter the game. These institutions manage large pools of capital and, beyond financial returns, they have a moral responsibility to support innovation that serves the long-term well-being of European society.Investing in deep tech today isn’t just about future profitability. It’s also about shaping the next 10 to 20 years of innovation.As Remco emphasizes, in this aspect, there is no time to be wasted.His call to action is clear: European pension funds, family offices, venture capitalists, and private equity firms must act together and invest in early-stage deep tech and innovation. Europe’s future competitiveness and progress depend on it.Find this conversation insightful? Don’t miss the next episodes of the Innovantage podcast! Max Golikov, together with his guests, will discuss a lot of other topics and offer new perspectives on technologies and their impact on the way businesses operate today. 

Some decades ago, websites were just static, informational pages that looked like digital brochures. Today, everything has changed. Digital platforms have evolved into dynamic, intelligent ecosystems. They are no longer limited to simply displaying content. Now, they understand context, adapt in real time, and can even make autonomous decisions.How is digital transformation reshaping business processes today? And what trends can we expect to see in the web space in the near future? These are the questions explored in the latest episode of the Innovantage podcast, hosted by Sigli CBDO Max Golikov.In this episode, Max is joined by Dominique De Cooman, Founder, CTO, and co-CEO of Dropsolid, a leading Digital Experience company based in Belgium.Dominique built his first Web 1.0 site in the early 2000s. A few years later, in 2007, he became active in the Drupal community. This marked the start of a nearly two-decade-long journey in open-source and digital experiences.Over the years, he witnessed the evolution of simple websites into complex, data-driven enterprise platforms. Now, they are known as Digital Experience Platforms (DXPs). While some view DXPs as a marketing notion, Dominique defines them as enterprise-grade websites designed for scalability and personalization.In 2015, as his company Dropsolid reached its second year, Dominique transitioned into business operations, taking on roles across sales, marketing, finance, and HR. In other words, he embraced the full spectrum of CEO responsibilities. In his current position, Dominique balances both technical and business leadership.The evolution of web content managementIn the early days of the web, content was added to websites manually using HTML. Later, this process was enhanced by CSS and JavaScript. As websites became more complex, server-side languages like PHP emerged. They enabled the creation of content management systems (CMS) such as Drupal or WordPress. By the mid-2000s, these open-source platforms dominated the market in their niches. WordPress was mainly used by small businesses. Meanwhile, Drupal addressed more complex and enterprise-level needs.The web space was actively evolving, and the same is true about user expectations. Non-technical users needed easier tools to manage content. This led to the rise of CMS platforms. But the possibility to work with content alone wasn’t enough. Businesses began looking for personalized, data-driven experiences for their users.This growing demand became a booster for the rise of Digital Experience Platforms. These are more advanced solutions that integrate content management with customer data. Such a platform allows organizations to deliver tailored content based on user behavior, preferences, and context across multiple channels, including websites, email, mobile apps, and even in-store screens.While definitions vary, a core feature of any DXP is its data-driven approach. Marketing automation tools and customer segmentation are also sometimes considered to be integral parts of the platform.Moreover, Gartner also includes cloud services in its broader DXP definition. But as Dominique highlighted, at its core, a DXP always merges content and data to provide personalized digital experiences.Low-code/no-code: Real innovation or just marketing?While the low-code/no-code movement is often seen as a marketing trend, the concept may bring real value, especially when applied to web content platforms. In general, low-code/no-code refers to tools that enable non-technical users to build applications with minimal coding. These capabilities have been present in platforms like Drupal and WordPress for years.Drupal, in particular, stands out for its robust architecture that supports structured data, entity-based APIs, and flexible content modeling. This makes it well-suited for low-code functionality, even if it doesn’t market itself that way.While dedicated platforms like Mendix focus entirely on low-code application development outside the CMS world, Drupal integrates similar flexibility within a content-first ecosystem.Given this, Dominique believes that, partially, the hype around low-code tools is explained by huge marketing efforts of the teams behind them. At the same time, platforms like Drupal have quietly offered these features for years without the label.Such tools as WordPress and Drupal have long enabled user-friendly content creation without coding. Nevertheless, unlike no-code/low-code platforms, their purpose has always been to simplify web publishing, not to replace the need for custom development entirely.How DXPs can address users’ needsThere are strong business cases for adopting DXPs that can demonstrate how companies can enhance operational efficiency and improve customer experience with such solutions. Personalized, streamlined digital experiences reduce support calls and improve internal workflows. On the content creation side, giving teams the right tools can greatly ensure much higher output quality and speed.While some critics argue that DXPs are monolithic, expensive, and inflexible, this view is usually based on their knowledge related to older, legacy platforms. Modern, open DXPs are composable and API-driven. As a result, they enable organizations to integrate and swap components as needed. Platforms like Dropsolid’s DXP, based on Drupal, offer modularity without sacrificing structure. This is possible thanks to thousands of plug-ins and modules that users can rely on.However, there is the other side of the coin as well. A fully composable setup may become overly complex and lead to what is often called a distributed ball of mud. Managing many microservices at once requires deep expertise and consistent vendor coordination. It means it can become a long-term operational burden.For most enterprises, a DXP offers a golden middle. It provides enough flexibility to adapt, and at the same time, enough structure to scale. DXPs can consolidate digital tools and reduce complexity. With their help, businesses can stay focused on delivering value instead of allocating all their efforts to managing infrastructure.Monoliths, microservices, and AI: What comes next for DXPsAccording to Dominique, the future of Digital Experience Platforms lies in finding the right balance between monolithic stability and microservice flexibility. The vendors that succeed will be those that help organizations strike this balance, and AI will play a pivotal role in this space.As AI becomes more integrated into enterprise workflows, business leaders are prioritizing projects that both enhance customer experience and drive operational efficiency, while still staying within budget. One challenge is the overwhelming number of data sources most enterprises manage. Quite often, their number can be over 100, and many of them are supported by lightweight SaaS tools.AI has the potential to replace many of these smaller services. With this technology, it will be easier to consolidate data, content, experience, and infrastructure. This shift in the tech space will ensure that only the strongest platforms will remain and unite the functionality of numerous fragmented tools.If these layers can communicate effectively, via APIs and frameworks, enterprises will be able to deliver more value with fewer tools, reduced complexity, and tighter budgets.Apart from this, Dominique revealed his optimism around the long-term future of open-source CMS platforms like Drupal. Drupal’s robust framework makes it well-suited for AI integration, and companies like Dropsolid are actively contributing to this evolution. For example, one of the co-maintainers of the official Drupal AI module is on the Dropsolid team.At recent developer events like Drupal Dev Days in Leuven, there was a noticeable surge of excitement around the role of AI in Drupal’s future. This momentum is likely to accelerate in the near future.Value of AI in digital transformationFor Dropsolid, the past year marked a turning point. Despite strong performance across its services and DXP business, Dominique faced what he described as an existential crisis.Amid the growing adoption and power of AI, Dominique started thinking about the probability that AI will eventually automate the services that Dropsolid and other similar companies offer today.These thoughts pushed him to start exploring how to build and host AI capabilities entirely within a company’s own infrastructure. During that work, Dropsolid partnered with Sigli, which is well-known for its deep expertise in AI infrastructure and data engineering.By late 2024, AI was advancing rapidly. It became clear that the viability of classical services models was increasingly in doubt. Dropsolid needed to change in order to stay on the market. The team organized internal workshops, hackathons, and consultations with AI startups. Initial skepticism among engineers was gradually replaced with enthusiasm. As a result, the company was split into two:Dropsolid AI, the new AI division focused on building the next-generation DXP enhanced by AI;The original solutions business, which continues to serve clients while aligning with this AI-first strategy.What makes the transformation even more compelling is the commitment from within. Dropsolid opened an internal capital round and allowed employees to invest in the AI business. The strong response was a clear signal of internal alignment and a promising sign to external investors.Practical value of digital experiences: Real-life examplesIn large organizations, digital experiences have far-reaching implications beyond user convenience. They directly impact efficiency, cost, and service delivery at scale. This is especially evident in sectors like healthcare, where even marginal improvements can translate into significant gains.Dominique mentioned an example of the University Hospital of Antwerp, which is one of the largest medical institutions in Belgium. With over 800,000 patient visits annually, even a 1% increase in efficiency can save substantial resources.Patient journeys typically span various touchpoints: websites where patients research symptoms, appointment systems, electronic patient records, and communication channels. The key challenge lies in integrating these systems to ensure that patients receive accurate information at every step without delays. This not only improves the patient experience but also helps optimize the healthcare process.From a broader economic perspective, especially in Europe’s publicly funded healthcare systems, shortening the patient journey translates into reduced costs for governments. AI-driven platforms can help patients navigate complex medical systems more efficiently. This helps reduce administrative burdens and enables hospitals to treat more individuals with the same resources.This concept of intelligent customer journeys is equally transformative in the commercial sector. Dropsolid has worked with enterprises managing complex ecosystems, where guiding users through a purchasing process is a core challenge. Traditional marketing automation and customer data platforms provide rules-based workflows. They are well-structured, but they lack the flexibility to adapt dynamically to real-world behavior and context.AI-enhanced digital experiences address such issues. They enable real-time guidance based on behavioral patterns, seasonality, external events, and user intent. For instance, Dropsolid collaborates with the leading publishing group in the Benelux region. The company manages a catalog of over 60,000 titles. By combining a DXP with CDP data, it becomes possible to build intelligent assistants. They can recommend content based on not just reading preferences, but also broader contextual data (like holidays, trends, or individual behavior patterns).Intelligent digital experiences allow organizations to move beyond manual processes and pre-defined workflows. It means that they can ensure more adaptive and more personalized experiences.The future of AI agentsIn their discussions, Max and Dominique also talked about AI agents. AI agents are rapidly becoming foundational to the next generation of digital infrastructure. According to Dominique, the future points toward a reality where AI agents are seamlessly embedded into every layer of software, from the experience layer to content management, databases, and even infrastructure.Intelligent integration platforms (iPaaS), such as n8n, are beginning to compete with frameworks like LangChain. Today, they successfully demonstrate how traditional workflow automation tools are evolving into agent-driven systems. In the future, chained AI agents capable of reasoning and orchestrating are likely to become standard components in software development.This trend isn’t limited to commercial platforms. In open-source ecosystems like Drupal, there are already frameworks being built to support the development and integration of AI agents at the application level. At the same time, there is growing interest in hybrid architectures. In such systems, enterprise-level AI agents coexist with distributed, localized agents operating closer to the user interface or experience layer. This model reflects the way biological nervous systems work: a central nervous system manages core operations, while peripheral nerves handle localized tasks with high precision and speed. In digital systems, this could mean enterprise-wide agents coordinating with smaller, specialized agents embedded at the interface or service level.However, this doesn’t mean deterministic code is going away. Traditional software logic will continue to play a crucial role. Particularly, it will be useful in well-defined systems where predictability and security are paramount. AI agents will likely augment rather than replace this code.In the long term, Artificial General Intelligence (AGI) may also have chances to become another promising concept. But, as Dominique mentioned, we are not even close to this stage now.As AI agents become more deeply embedded into enterprise ecosystems, governance and sovereignty over these systems will become absolutely essential.Growing responsibilityWhile the dream of many managers and business owners is to wake up and find an inbox full of productive AI updates like growing conversions, the nightmare scenario is still possible. You could just as easily find that same inbox filled with legal claims because an agent executed a creative but ill-judged campaign that offended users or violated regulations. Autonomous systems without oversight risk exposing organizations to reputational, financial, and legal consequences.This is why strong governance frameworks must evolve alongside AI capabilities. You cannot simply unleash autonomous agents in a business-critical environment and assume everything will operate as intended. Liability always remains on the organization, not the agent.The future will belong to those who can combine the strength of robust digital platforms with the agility and intelligence of AI without losing control over the outcomes.Curious about other tech innovations and their impact on the business world? In the upcoming episodes of the Innovantage podcast, Max and his new guests will continue talking about this and will touch on many other topics. Don’t miss it!

In a world increasingly shaped by artificial intelligence, automation, and rapid organizational change, what does it truly mean to lead? How can business leaders stay relevant in such a dynamic landscape? What role will humans play in this technology-powered future? These questions were explored in the latest Innovantage podcast episode, hosted by Sigli’s CBDO, Max Golikov. Max invited Stijn Staes to share his expert insights.Stijn is the founder of Stappen met Stijn, a transformation coach, and the host of a podcast on leadership, diversity, and the evolving relationship between people and agentic AI.Stijn has always had a passion for helping people to grow. His career began in nursing and hospital management. He traveled around the world with such organizations as Doctors Without Borders. Back in Belgium, he served as general manager of the country’s largest private youth institution. He always stayed focused on the same mission: unlocking human potential. For the past six years, Stijn has worked as an independent executive coach, sharing his insights through coaching and his podcast.What is diversity?According to Stijn, deep down, all human beings are fundamentally the same. Today, diversity is often treated as a buzzword, which is used to assign labels based on race, culture, gender, or identity. Nevertheless, Stijn emphasized that beneath these labels lies a shared human desire: to be seen, to be heard, and to feel connected.Effective leadership should start with recognizing this common humanity, while also adapting communication styles to meet people where they are. Cultural and personal differences matter. But they should act not as boundaries but as bridges. Stijn sees diversity not only in visible identity but also in how we communicate, relate, and create space for others to belong.He explained that true diversity in an organization is not just about representation. It is about developing the awareness and emotional intelligence to engage with people as individuals, each with their own way of being heard and understood.How to communicate in the right wayFor Stijn, effective communication, especially in leadership, starts with curiosity. He believes that staying curious helps us avoid judgment, which is the most common pitfall in human interaction. Miscommunication often stems not from what is said, but from assumptions we bring into a conversation when we fail to truly listen.Curiosity is the gateway to the right communication. It keeps us engaged and open to others’ views.Key challenges for building a diverse cultureOne of the key challenges in building a truly diverse culture is our natural desire to get involved with people who think, speak, and act like us. While this may feel comfortable, it is a serious mistake.According to Stijn, effective leaders must actively look for individuals who can offer constructive criticism and challenge ideas. This will not disrupt, but deepen understanding and improve outcomes. This requires humility and openness. For many leaders, the real challenge isn’t embracing diversity on paper, but learning to welcome feedback that doesn’t align with their own thinking.How to provide feedback: Trust and intentionStijn believes that trust and intention are two essential elements of giving feedback effectively. Trust creates the psychological safety necessary for honest communication. It means knowing the other person will speak with honesty, respect, and a shared commitment to growth. Without that foundation, feedback can easily feel personal or threatening.The intention behind the feedback is equally important. Feedback should not be about proving who is right or wrong. It also shouldn’t serve the ego. Its true purpose is to improve the organization’s services and outcomes for clients. When both parties understand that feedback delivers value and supports common growth, much of the emotional tension often associated with difficult conversations will be eliminated.Stijn is strongly confident that feedback culture works not only on a small, team-based level. It can be scaled across an entire organization. In his view, feedback should not be limited to face-to-face teams or familiar colleagues. It’s a fundamental part of a healthy organizational culture, and it should reach every level, including interns and CEOs.Asking simple, respectful questions (like how someone prefers to work or whether the timing is right) opens the door to meaningful, two-way communication.Are visionary leaders bad for the corporate culture?Visionary leadership is essential but only when paired with self-awareness and a genuine understanding of what the organization needs. Leaders must recognize not only their strengths but also their limitations and remain open to diverse perspectives.Stijn cautioned against authoritarian leadership, noting that while it might deliver short-term gains for shareholders, it undermines long-term sustainability. A resilient organization requires transparency and a culture of open feedback. This doesn't mean leaders must act on every suggestion they receive, but they should always listen, consider, and respond with thoughtful reasoning.This helps build not just a business, but a strong community around it.The most effective strategies for change managementWhile talking about approaches to changes, Stijn mentioned the case from his time as a general manager. His organization needed to integrate 150 new employees into an existing workforce of 300. This required forming 30 newly blended teams and simultaneously introducing a new way of working.Instead of imposing change from the top down, Stijn and his team focused on deep listening and inclusive planning. They did their best to understand what mattered most to employees. This transparent and people-centered approach was key to the transformation. Despite the scale of change, only 2% of employees left the organization.Instead of relying on algorithms or AI tools, they conducted one-on-one conversations, online questionnaires, and team meetings to find out what mattered most to their people.Leaders from across locations came together to analyze the findings and co-create new team structures. Several proposals for the reorganization were shared with employees, who could give feedback and even request alternative roles. As a result, almost everyone ended up exactly where they wanted to be.Stijn believes successful leadership rests on three pillars:Love for people and for what you are doing;Knowing your business and having a clear insight into what works and what doesn’t;Listening to your gut and trusting your intuition to act at the right moment.Pitfalls of change managementWhen guiding an organization through intensive transformation, something will inevitably go down a little (and that is usually income).This temporary drop, however, is not a failure. It’s the cost of meaningful, people-centered change. When done with care, clarity, and the right timing, the organization stabilizes and rebounds stronger. But if the transformation is rushed or poorly managed, the downward curve continues. An organization may experience employee dissatisfaction, increased turnover, and loss of trust.For Stijn, effective change management starts with a fundamental truth: there is always a change. Sometimes it is big, sometimes it is small. But it is constant. The real challenge isn’t initiating change, but allowing people the time and space to integrate it.Quite often, companies move from one transformation to the next without pause. A new manager comes in and brings another change. However, humans need time to settle, to process, and to feel included. In Stijn’s practice, his team always made sure to involve people actively. Weekly newsletters, employee-written reflections, and open communication created a sense of shared ownership and psychological safety.Change isn’t something you tick off a list. It lives on long after the formal transformation phase ends. Sustainable change requires a long-term mindset, a culture that embraces uncertainty, and leadership that shows up fully.If you see change as a box to check, it won’t work. Because this isn’t AI. This is human. And humans need to be seen and heard.Uncontrollable changesMax shared insights about Sigli. In its early days, Sigli was a young, energetic, and even impulsive team. It was common for employees, who were mostly in their twenties, to work late, play video games, and socialize a lot. The culture embraced this youthful energy.Over time, the team matured. Those who once spent late nights gaming now had families and different priorities. Staying late at the office became less common, and personal life took precedence. However, hiring practices continued to focus on attracting younger, energetic candidates, which created a cultural disconnect. This shift wasn’t a result of deliberate organizational change but rather a natural evolution driven by time. Here comes a question: How can a company manage or anticipate these kinds of uncontrolled, organic changes that happen naturally over time rather than through planned initiatives?Stijn emphasized the importance of self-reflection for leaders navigating change. He believes every leader must regularly ask themselves if they are still the right fit for their role and the company’s future. Given that external circumstances constantly evolve beyond anyone’s control, the only thing leaders can truly change is themselves.Stijn also pointed out that as companies grow, the leadership style and team composition may need to change as well. A startup’s energy might require younger leaders, while scaling up could call for more experienced, seasoned managers. They must be aware of their role in this evolution and have the courage to step aside if necessary.Self-reflection is the key tool for recognizing when organizational change becomes a must.Do surveys really work?That’s not a rare case when corporate surveys fail. Response rates are too low, while the data quality leaves much to be desired. In a 300-person organization, it’s typical to get only about 100 responses, and even then, the reliability of the answers can be questionable.However, there is nothing wrong with this format itself. The survey’s purpose plays a major role. In Stijn’s practice, surveys always worked best when participants could see clear personal relevance. For example, when a questionnaire directly impacted employees’ next career steps, response rates were 100%, as everyone understood its importance.If there’s no immediate benefit or urgency, responses always tend to be incomplete or socially biased. Therefore, it’s crucial to evaluate whether a survey is the right tool for the information needed. Sometimes, one-on-one conversations or group meetings might be more effective.Given all this, Stijn advised against relying on surveys alone. A combination of methods tailored to the goals and the audience can ensure the best engagement and data quality.Will everything be AI?The discussion also touched on the power of AI. Stijn mentioned an article arguing that AI will inevitably replace most jobs related to data, presentations, and routine business tasks. According to it, humans will remain essential mainly for fieldwork and personal interactions, while AI handles data-driven tasks efficiently and without complaint.Stijn also believes that many technical tasks, especially those repeated in meetings and spreadsheet discussions, will be taken over by AI. However, he stressed the importance of understanding where humans fit in this evolving landscape. It’s necessary to determine the ways in which people can grow, adapt, and focus on uniquely human strengths.For example, we shouldn’t underestimate the value of robots that can assist elderly people. But human connection cannot be replaced by such assistants.Every person should stay aware of new technologies and trends. But it is not a good idea to accept things just because they are popular. It is necessary to remain curious and question the true value of all innovations. Business leaders need to analyze whether some changes genuinely serve the company, society, and the world or whether they are just a new trend that has no practical benefits.The fact that AI can create art does not diminish the value of human-made art. While technology like 3D printers can produce sculptures, they don’t carry the same meaning or connection as those crafted by human hands. The same applies to drawings and paintings. AI-generated art lacks the personal insight and emotional depth that come from human creativity.The true value lies in creations made by people. Without the human element, this value is lost.Human touch: What sets people apart from AIThe role of AI in professional life is growing. However, it has its clear limitations. Stijn explained that there are AI programs that could technically replace an interviewer or even an interviewee. Nevertheless, he admitted that he doesn’t want to do an interview with a machine. The essence of a real conversation is unpredictability, nuance, and emotional presence.Artificial intelligence can’t replicate the human dynamic of live dialogue. Human interviews are not just about answering questions. It’s about connection.AI is a powerful tool, but not a replacement for human interaction. For instance, you can practice foreign languages with AI. But you can grow only with people.Key trends shaping the future of leadershipStijn highlighted a growing polarization in leadership styles. On one end, we can see ego- and result-driven leadership. On the other hand, there is a more human-centered, empathetic approach. These two directions seem to be drifting further apart.The real challenge lies in bridging the tech world and human-focused leadership. Technology is essential. But without a human, all this won’t make sense.And that’s one of the main theses voiced by the guests of the Innovantage podcast episodes. Technologies are changing and replacing each other. But human communication is always here. And it will definitely stay.Want to know more about the world of technology and business? New episodes with new guests are coming soon.

This article explores how to launch successful AI projects that create measurable business value, based on Sigli's “AI Profit Toolkit” webinar for SMEs. It highlights key considerations before starting with AI, including when not to use it, how to evaluate feasibility with the AI value matrix, and the importance of aligning AI use cases with business KPIs. A real-world case study from a UK e-commerce company shows how an LLM-powered returns bot improved refund times and cut costs. The post also offers practical advice on data quality, quick-win AI pilots, and stakeholder sponsorship to ensure high ROI. Ideal for decision-makers seeking to implement AI with confidence and clarity. Artificial intelligence continues to change the way businesses operate. When applied sensibly, this technology opens up a wide range of new possibilities for efficiency, innovation, and profitability. At Sigli, we strongly believe that we should use our deep business and tech knowledge to help individuals and companies uncover the practical value of cutting-edge AI-powered tools. One of our latest initiatives in this space was a free educational webinar for SMEs titled “The AI Profit Toolkit”. The event was hosted by Sigli’s Chief Business Development Officer Max Golikov.This article includes the key takeaways from the webinar and offers actionable guidance for anyone looking to launch AI projects that deliver real value without excessive risks.What you should know about AI before you even startOne of the most important principles to understand before diving into AI is that it is not always the answer.AI is a powerful tool. But it doesn’t mean it should be applied universally. In many situations, simpler, more cost-effective technologies may yield better and faster results. The key is to find out why you want to use AI and whether a non-AI solution might accomplish the same goal with less complexity. If there are other approaches to addressing your needs, it may turn out to be much more sensible to use them instead of investing in an AI project.Nevertheless, we by no means deny the business value of AI. It’s absolutely measurable and wide-ranging. According to industry insights shared during the webinar, AI’s contributions to business value break down into several categories:57% comes from boosting productivity, primarily through automation.17% stems from automating routine daily tasks.16% is linked to enhancing customer experience.The remaining 10% covers a range of other use cases.The transformative power of AI is especially tangible when applied thoughtfully to pain points that drain time and resources.AI value matrixTo evaluate whether your future AI project is worth your time and money, we recommend you use an AI value matrix. This strategic tool helps find the right balance between the technical feasibility and business value of your ideas.According to this approach, on the technical side, you will need to assess:Data quality. The foundation of any successful AI project is high-quality data. Projects with clean, abundant data move faster and require fewer resources at every stage of development and maintenance.Technological complexity. Before committing to an AI project, you need to consider the resources needed to move from idea to impact. Low-complexity solutions (like plug-and-play SaaS and low-code components) tend to score best on the AI value matrix.Availability of talent and skills. Even if your problem seems to be solvable with AI, you also should carefully analyze whether you have experts with the required skills in-house or whether you are ready (and have the budget) to hire reliable partners. Moreover, if you choose the second path, make sure that you have a hand-off plan.On the business side, it will be necessary to focus on such aspects as:Alignment with business goals. AI should be tightly aligned with your strategic objectives or profit and loss (P&L) metrics. This ensures you are not chasing tech trends for their own sake but solving real, impactful business problems.Sponsor support. Every AI project needs a committed sponsor. In the ideal scenario, it should be someone who owns the budget and the performance metrics that the project aims to improve. For example, projects that have a C-level sponsor are likely to move much faster than those supported by people without the authority to sign cheques or make decisions independently.Measurable KPIs. Your AI use case should be built around a small set of clear, quantifiable KPIs. For instance, these metrics might include time saved, cost reduction, revenue growth, or user engagement. It makes sense to choose the KPIs that are already tracked and understood in your organization. This will help you avoid debate over measurement methods and simplify the “before vs. after” comparisons.The projects that score highest across both dimensions are those with the highest likelihood of success and return on investment.Choosing the right AI pilot: A real-world exampleDuring the webinar, Max Golikov shared a couple of powerful case studies to demonstrate what you should pay attention to while considering different ideas for your AI projects. One of the examples was Sigli’s cooperation with a mid-sized UK apparel e-commerce retailer.The company had an annual revenue of £48 million and 220K monthly orders. 12 fulfillment staff processed orders, returns, and refunds via three legacy tools (Magento, Zendesk, and homemade Excel macros).When the company turned to Sigli, they had serious issues with the time needed for different processes. The returns and exchange queue averaged 5000 orders, which caused 7-day refund delays and seriously hurt the company’s rankings on Trustpilot. Apart from that, manual triage was pretty expensive as it cost £3.40 per refund.Another problem was the fact that the customer support team had to spend 30% of time copy-pasting return merchandise authorization (RMA) info instead of applying upsell techniques and driving sales.To solve the described issues, it was offered to consider different ideas, including an LLM-powered returns-triage bot, a demand-forecast bot, and a personalized upsell recommender.As the AI value matrix shows, the first idea won.For such a solution, the company had rich training data. The team had access to 95,000 labeled Zendesk tickets, which made it easy and fast to train the AI model.From the integration perspective, there were no serious pitfalls. The solution only needed to connect with the Zendesk API and an existing RMA. It means that the implementation of this bot didn’t require a full system overhaul.Moreover, it was quite simple to detect clear success metrics. Such KPIs as cost per return and refund turnaround time were already being tracked daily. Thanks to this, it was possible to measure the immediate project impact.The project also could receive strong business sponsorship. The Fulfillment COO both owned the P&L and sponsored the pilot.All this led to a successful AI implementation and tangible outcomes:Cut cost per return to £1.90 (a 44% reduction);Reduced refund delays to 2 days (a 72% improvement);Boosted Trustpilot score by 0.3 stars.Key things to keep in mind to maximize the ROI of your AI projectLet us briefly summarize what we’ve discussed above. Based on our practical experience, we recommend focusing on the following points to ensure your AI initiatives deliver real value:Quick-win quadrant. Want to achieve quick wins? Select projects that score at least 7+ on technical feasibility and 8+ on business value on the AI value matrix.Clean and accessible data. Well-organized data always saves time and reduces rework.One clear KPI. Choose a metric that you have been already tracking for a while. Thanks to this, performance can be easily compared before and after implementation.A single, accountable sponsor. A budget-owning stakeholder accelerates decision-making and ensures follow-through.Measurable deliverables. Projects should be much more than just flashy tech demos. They should yield clear financial results.Closing thoughtsArtificial intelligence offers incredible opportunities to streamline operations, reduce costs, and deliver standout customer experiences. However, all benefits become available only when this technology is used deliberately. It means that AI should be guided by clear goals, supported by strong data, and evaluated by hard metrics.At Sigli, we can provide support for your business through every phase of the AI journey: from ideation and pilot planning to full-scale deployment. If you are ready to turn AI potential into business value, we are here to help.

Today, Sigli devotes considerable efforts to helping individuals and companies discover the value of cutting-edge technologies, including artificial intelligence, and their influence on business processes. One of the most recent educational initiatives was a free webinar for SMEs called “The AI Profit Toolkit”. The key goal of the webinar hosted by Sigli’s CBDO Max Golikov was to provide the audience with practical recommendations on how to adopt AI in a practical, budget-conscious way. In this article, we will share the key insights on how to launch AI pilots that create a measurable impact without serious risks. What business value can AI create? The impact of AI can be broken into several categories. The largest portion (57%) of AI’s business value comes from boosting productivity.AI often helps automate daily tasks, reducing manual workload. Everyday routine automation accumulates 17% of the general business value. A share of 16% represents customer experience enhancements. 10% is related to other use cases.Is AI the best technology to use today? The golden rule number one that every business owner and decision-maker should learn is that AI isn’t required everywhere. It’s a powerful technology, but you shouldn’t use it unless you really need it. Instead, you also need to consider other tools. In many cases, their implementation can help you save money and, at the same time, achieve much better efficiency. Before you apply AI, you should have a very good understanding of why you need to do it. How can I estimate the profitability of any AI project? One of the most reliable ways to do it is to apply an AI value matrix. It helps prioritize projects based on technological feasibility and business value. The group of technological factors that should be evaluated covers data quality, technological complexity, as well as the availability of skills and people. Business factors include business goal alignment, sponsor support, and measurable KPIs (like the decrease of time or resources needed for performing this or that task). The project that will get the highest score in the overall results is likely to succeed and bring the most significant impact. How to analyze technological complexity? When you are considering the implementation of a particular AI tool, you need to understand how much time and what resources will be required to achieve the level when this solution starts bringing real value. There are several core questions that you need to ask yourself: Is there a similar native feature in your current SaaS/ERP? (Today, a lot of systems offer their own AI functionality and it is possible that you won’t need to introduce your custom tool instead). Does a managed API already exist? Are there any latency or throughput constraints? Is it secure to implement this solution? Is a security review needed? Those solutions that require minimal effort from your side (like low-code components or plag-and-play SaaS) will get the highest score according to the AI value matrix. What does business goal alignment show? This parameter will help you evaluate the link between the AI use case under consideration and a strategic or P&L (profit and loss) objective. Thanks to it, you will be able to move your focus from overhyped tech trends that don’t have any relation with your existing bottlenecks to mission-critical initiatives. How can I understand that one AI pilot is better than the other one? To answer this question, let’s turn to one of the real-life cases that the Sigli team worked on. The client was a mid-sized Dutch EdTech platform that has 175K active learners on its online courses. The main problem that the company wanted to solve was the reduction of time and resources that were required for user support services. Tutors used to spend 18% of their paid hours answering FAQs, which cost the company more than €1 million per year. Our experts had different project ideas under consideration. Some of them were an LLM tutor-assist bot, a drop-out risk predictor, and an adaptive learning path recommender. As you can see from the matrix below, the first idea won. But why did it happen? To launch such a bot, the company already had a rich set of labeled data (more than 22K historical chat transcripts tagged by topic). There were no specific difficulties in integrating the solution with the company’s platform. It was possible to apply clear success metrics (response time and tutor time). And last but not least, the project received strong support from a single sponsor (it was the Head of Learner Success who owned the tutor budget and worked with retention KPIs). As a result, the successfully implemented tool helped cut the median first-time response time by 84% from 8h to 1.3h and free 0.25 FTE (full-time equivalent) per tutor. How to make sure that my AI implementation will be a successful one? To maximize the ROI of your AI project, you need to focus on the key elements: Quick-win quadrant on the AI value matrix. You should select projects that score at least 7+ on Technical Feasibility and 8+ on Business Value. These are the ideal quick wins. Clean and accessible data. High-quality, well-organized data significantly reduces preparation time and helps avoid repeated model re-training. One primary KPI. It is vital to choose a use case with a clear metric that is already tracked. This makes "before vs. after" comparisons simple, and you can eliminate the need for extra instrumentation or debate. Single budget owner as a sponsor. Having one accountable stakeholder enables fast approvals, resource access, and sustained momentum. Measurable business deliverables. You should make sure that your AI project produces tangible, financial results. The goal is to prove that AI delivers profit, not just innovation for its own sake. Final word Artificial intelligence can help you overcome a lot of existing bottlenecks and greatly boost your business growth. But all this is possible only when AI is applied deliberately, with the right expectations and a strong business case. As you can see, the most successful AI initiatives are not driven by hype or fear of missing out. They are driven by clearly defined goals and measurable outcomes. At Sigli, we are always ready to support your business at any stage of your AI journey: from strategy development and pilot selection to full-scale implementation. Don’t hesitate to contact us and learn more about how to turn the potential of AI into real business value.

The episodes of the Innovantage podcast hosted by Sigli’s CBDO Max Golikov cover a wide range of topics, including technology, business, and the role of digitalization. In the spotlight of the new episode are not just technologies, but also people. How can business leaders successfully implement innovations without facing resistance from their teams?Thiago de Faria, Senior Solutions Architect at AWS and a recognized Team Topologies expert, shared his perspective on this and many other important questions.Thiago has spent the past decade at the intersection of data, distributed systems, and organizational dynamics. Through years of hands-on experience, he came to understand that success isn’t just about algorithms or tools. It’s about communication and how teams work together.This insight led him to pursue leadership roles, including such positions as CTO, director, and team lead. He later joined AWS, where he led startup solutions architect teams, working closely with early-stage startups. After a period of freelancing, Thiago returned to AWS. Now, he focuses on enterprise modernization. His goal is to help organizations realize that technology is rarely the real challenge in their transition. They need to pay more attention to everything else around it. “It is about people, and it has always been.”For Thiago, building sustainable businesses goes far beyond technology. It is about people and communication. Success depends on understanding human behavior, managing egos, and being kind.He doesn’t believe in the top-down leadership model and the "do it because I'm the boss" mindset in the modern world. Today’s teams are motivated by more than just money or fear. The traditional stick-and-carrot approach no longer works. Instead, leaders must tap into what truly drives people and apply that insight to how technology and organizations evolve.Team Topologies as a framework for structuring teamsThiago mentioned Team Topologies as a powerful framework for structuring teams and improving how they collaborate. It was developed and described by Matthew Skelton and Manuel Pais. The framework is based on the ideas of DevOps, Agile, Lean, Deming’s principles, and the Theory of Constraints. Its core goal is to enable fast flow from idea to production, while still meeting security, compliance, and feedback needs.Overplanning or overcommunicating can also be dangerous for team efficiency. Team Topologies introduces a shared language to design team interactions intentionally. Without this structure, teams often drown in context, which can result in cognitive overload and a loss of focus.In Team Topologies, the team is treated as the smallest meaningful unit. And the key idea behind that is the fact that sustainable outcomes come from well-structured, collaborative teams rather than separate heroes. Team Topologies isn’t a rigid framework or a call for company-wide reorganization. Instead, it starts with identifying value streams and understanding how work actually flows through the organization.How to implement significant cultural changes within teamsThiago emphasized that meaningful cultural change within teams is neither strictly top-down nor bottom-up. It requires a combined approach. Such changes take time. It can be quarters or sometimes even years. The key is to create sufficient awareness of the broader context, the processes in place, and the value stream itself. By determining bottlenecks and reducing handovers, organizations can begin shifting toward a more collaborative and efficient culture.This cultural shift is deeply tied to technical practices rooted in DevOps: continuous integration, continuous deployment, fast feedback loops, trunk-based development, and robust testing. But it’s not just about better tooling. It’s about bridging the gap between business and technology.One of the biggest mindset shifts is moving away from a factory-style model where tech teams wait for perfect requirements before building. Instead, developers must become more curious about the business and more engaged with customer needs. Collaboration shouldn't be sporadic, and it shouldn’t be handed off via tickets or rigid requirements. It should be ongoing. The core challenge lies in bridging the gap between existing infrastructure and organizational culture. It can’t be imposed top-down through mandates or principles alone.The real test of culture comes during crises like missed deadlines, outages, or security issues. In such situations, nobody wants to take responsibility for that because responsibility can be really painful.Often, it is not about people avoiding responsibility, but about misalignments and overloaded teams that make real ownership nearly impossible.That’s where the principle of fast flow becomes crucial. To avoid such situations, it is necessary to reduce cognitive load, streamline knowledge requirements, and minimize distractions. This will allow teams to focus on real ownership and deliver value more effectively.Psychological safety is a must for cultural changesAccording to Thiago, there is no one-size-fits-all model for implementing cultural changes. One of the biggest challenges is building psychological safety, which is a prerequisite for any meaningful transformation. If even one person on a team doesn’t feel safe, the team as a whole isn’t truly safe.Psychological safety starts with trust among teammates, across roles, and with leadership. Trust isn’t built through blind agreement. It’s built through transparency.For Thiago, a practical way to foster trust is to surface assumptions and clearly explain decisions. People don’t have to agree with every call, but they should understand the rationale behind it. Disagreement is fine when it is followed by commitment and free of blame if things go wrong.Platform groupsOne of the most impactful ideas to emerge from Team Topologies is the concept of platform groups. They are responsible for building and maintaining internal platforms, tools, services, and building blocks that reduce the cognitive load for product-focused teams.Thiago explained that teams that are directly delivering customer value are often overwhelmed. They are expected to handle everything: databases, deployment pipelines, infrastructure, testing frameworks, compliance, programming patterns, and business context. That’s an unrealistic cognitive burden, and it’s often why these teams default to focusing only on the technical layer.Platform groups solve this by offering clear, reusable paths, or prebuilt ways to deploy services, manage infrastructure, or handle CI/CD. Their main goal is to streamline delivery by eliminating unnecessary friction.However, many companies misapply this concept. They form a single overloaded “platform team” tasked with managing everything, from CI/CD and data infrastructure to Git workflows. As a result, such teams become a bottleneck themselves. That’s why the shift to true platform groups is important. Here, it is essential to keep in mind that they should be purpose-driven, focused units with clear boundaries, allowing for scale without burnout.Thiago also highlighted another team pattern from Team Topologies. It is enabling teams. They unite cross-functional experts, such as architects or systems specialists, who embed temporarily with other teams to unblock problems, offer guidance, and enable better practices before moving on. Companies should think of them as internal consultants focused on capability-building, not control.Transformative impact of cloud computingCloud computing introduced a profound shift in the technology landscape.The first big transformation it enabled was accessibility. Cloud computing removed the barrier to entry. It turned infrastructure into a utility that is available on demand based on the pay-as-you-go principle. It enabled startups and solo entrepreneurs to bring ideas to life without the need to secure bank loans just to spin up their first server.But the second wave of transformation came with serverless technologies (or, as Thiago calls it, “serviceful” computing). Instead of managing servers or configuring infrastructure, teams can now focus almost entirely on solving business problems. These new patterns allowed developers to work faster, experiment more freely, and scale effortlessly. This approach closely aligns with the principles behind Team Topologies.Thiago admitted that this shift was the biggest he had seen in his career before the AI transformation that we can observe today.However, he emphasized that not everything belongs in the cloud. There are workloads that make a lot of sense to keep on-prem. This is especially relevant for companies with decades of investment, expertise, and operational maturity around legacy systems.The real challenge of cloud transformation isn’t just technical, it’s human. Telling someone their years of expertise with data centers or custom infrastructure are no longer needed can trigger fear and resistance. That’s why change management becomes essential.Cloud-first approach: Is it always a good idea?Many companies today embrace a “cloud-first” approach. But, as Thiago noted, it’s often cloud-first only until compliance or cost gets in the way. The problems typically begin when companies attempt a “big bang” migration and try to rebuild or replatform everything at once. Thiago recollected cases where highly competent teams are tasked with rebuilding existing systems from scratch on the cloud, but team members didn’t have enough experience in cloud-native patterns.What comes next is often a “lift and shift” migration. It means that applications are moved to the cloud using the same designs and operational assumptions that worked on-premise. As you can understand, this method can result in multiple issues.Sometimes a lift and shift makes sense (for example, when delaying migration would incur hardware costs or lease renewals). But that should be the exception, not the rule. Instead, Thiago advised a more incremental, wave-based approach that includes team enablement and intentional architectural planning.The key to successful cloud-first transitions again lies in psychological safety. Companies should help people understand why the transition is happening and show how their existing knowledge can evolve in a cloud context.From the cloud back to on-premise solutionsToday, there are a lot of talks about cloud repatriation, which presupposes moving workloads back to on-prem. However, Thiago clarified that, in practice, he rarely sees this happening at scale. More frequently, he can observe companies that have never completed their cloud transition in the first place. These organizations may have adopted a “cloud-first” mindset years ago, only to realize later that some workloads were better left on-prem, or that not all systems needed to move.According to him, it’s vital to understand that not everything needs to be in the cloud.But today, cloud providers are prepared even for scenarios that require local infrastructure. Quite often, they offer hybrid options. For instance, Outposts by AWS bring AWS-managed infrastructure into the customer’s data center, still connected to the broader AWS ecosystem. It means that businesses can maintain full control locally, but the rest of their systems can still run in the cloud.At the same time, he also highlighted that it’s a myth that running LLMs on-prem is automatically more secure. If you are calling a third-party AI endpoint with no guarantees, that’s one thing. But platforms like AWS Bedrock give you private, VPC-based endpoints where no one else can access your data.Development of cloud computingAccording to Thiago, the 80/20 rule is a good one to describe what is happening in the modern IT infrastructure. 80% of workloads can be handled by broadly available, standardized solutions, while 20% will always require specialized, often bespoke approaches.He explained that platforms like AWS have matured to a point where the majority of business needs can be met using higher-level, off-the-shelf services. The extensive partner ecosystem has enabled businesses to build powerful platforms on top of AWS, without having to reinvent the wheel.Most businesses no longer need to create their own data platforms from scratch. There are already high-level solutions that help them avoid most of the complexity.However, many large enterprises still run highly customized legacy systems, often built on mainframes, and in some cases written in outdated languages with hundreds of thousands of lines of code. These systems are not easy to modernize. But they may be too critical to simply discard.Thiago explained that the middle layer, which is the part between front-end experiences and the legacy back ends, has already been undergoing modernization for years. What is left now is the hardest part: modernizing the base layer. It can be a real challenge, especially when companies face a knowledge drain after original developers retire.That’s where AI and ML come into play.AWS, for instance, provides tools like AWS Q Transform for mainframe apps. It leverages AI to analyze and explain complex legacy codebases, making them easier to understand and refactor. Integration of AI and ML into existing systemsThe explosion of interest in generative AI and large language models has captured global attention. Nevertheless, Thiago cautioned against abandoning the foundations of traditional ML, which continue to deliver significant value across industries.In the conversation with Max, Thiago urged organizations not to overlook the decades of progress in statistical learning, which have become overshadowed in the post-ChatGPT era. Since the launch of ChatGPT that happened in November 2022, much of the industry’s focus has shifted disproportionately toward LLMs and generative models, often at the expense of simpler and more efficient ML solutions.Thiago compared today’s LLMs with a battalion of interns. Modern LLMs are capable of generating content, conducting research, and providing ideas, but they are inherently biased and often lacking in precision or authority.“They speak with confidence, like white Reddit males who think they’re always right,” Thiago joked.Hallucinations, inconsistency, and lack of source traceability are among the main issues related to the mass use of large language models. Thiago views this as a call to action for better guardrails, source attribution, and AI literacy.Tip for business leadersMax also asked Thiago to share advice for leaders who want to implement AI solutions and build resilient technical infrastructures.“Be empathetic and be kind. That is the most important thing that I can tell people. Everything else will follow from it,” Thiago said.With all the changes that they can bring, technologies are just tools, people are the drivers of transformation. Leaders must resist the urge to chase innovation for innovation’s sake. Instead, they should focus on enabling teams, simplifying processes, and creating environments where individuals feel safe, valued, and heard. This is the main conclusion that can be made from this insightful conversation.Want to learn more about the world of business and technology? New Innovantage episodes will be available soon.‍

In the episodes of the Innovantage podcast, its host and Sigli’s CBDO, Max Golikov, usually invites guests to talk about technology and its impact on business. But the topic of the latest episode will resonate with a much broader audience. This time, the focus is on the art and the mastery of pitching to investors. Let’s be honest, when teenagers want to go out late for a Friday evening, they also need to make some kind of a pitch in front of their parents.To dive into this and entrepreneurship in and of itself, Max joined the podcast Robin De Cock, Professor of Entrepreneurship at Antwerp Management School.Robin has spent nearly 20 years helping students and business owners develop their ideas. Over time, he noticed that even strong ideas often fail during investor pitches due to poor presentation, which can be frustrating after months of work. This encouraged him to start teaching people how to effectively pitch and sell their ideas. Based on this desire and inspired by the growing body of academic research on pitching, he decided to write his book “Mastering the Pitch”.Evolving perception of entrepreneurshipFor a long time, entrepreneurs were seen as visionaries who could almost predict the future. However, over the past 10 to 15 years, this perception has shifted, especially with the rise of methods like the lean startup.Today’s entrepreneurs focus more on testing hypotheses, experimenting, and validating ideas with the market in iterative cycles to reduce risk. While vision and risk-taking are still important, there is now a stronger emphasis on evidence-based approaches.What is Robin’s book about?Robin’s book “Mastering the Pitch” is aimed at helping people improve the way they present their ideas. His main goal behind writing this book was to ensure that strong, impactful ideas don’t go unnoticed simply because they were poorly presented. He wanted to support entrepreneurs with insights that are not only practical but also grounded in scientific research. Unlike many other books on pitching, which are often based on the author’s personal experience, Robin’s approach brings together data from different sources. The book is built on two key pillars. First, Robin translated complex findings from academic research on pitching into clear insights for a broader audience.Second, he conducted interviews with entrepreneurs and investors across Europe and the US to understand how academic insights align with real-world practice. In his book, Robin also addressed several myths about pitching, starting with the idea that there is a magical formula for success. He compared pitching to dating: what works with one investor might not resonate with somebody else. Another common misconception is the overemphasis on slides. While a visual component is important, Robin explained that successful pitching involves much more. It should also be powered by passion, energy, tone of voice, body language, and team dynamics. Nonverbal elements often play a larger role than words alone in convincing others. Surprising insights from pitching to investors researchOne of the most surprising findings Robin discovered in his research is just how quickly people form impressions. Studies show that within just 150 milliseconds, an audience begins to form an opinion of a speaker. After 30 minutes, people will have a lasting impression of you. This highlights the importance of being yourself from the very start.Robin emphasized that when you are trying to impress investors, pretending to be someone else is not the best way to do it. Perhaps you will be working with these people for years, therefore, honesty and consistency from the very early stages are essential. According to one study, people tend to fall into certain “boxes” or behavior patterns during a pitch. One box is called the pushover. It means that people often agree to change even core aspects of their idea to please investors. Nevertheless, standing firm on your core vision while staying open to constructive feedback is crucial for building long-term trust and credibility.The impact of cultural background on pitching to investorsCultural background plays a significant role in how pitches are delivered and evaluated. Much of the research was conducted in the US. In this country, pitching tends to be bold, direct, and focused on world-changing ideas. In contrast, European investors often look for detailed explanations, early evidence, and proof of concept.In Asia, the approach is more indirect and relationship-based. Trust must be established before business discussions can move forward, and the process is usually more hierarchical. Decisions often take longer as pitches need to pass through multiple levels of approval. Storytelling in pitchesAccording to Robin, the role of storytelling in effective pitching can’t be underestimated. Research shows that stories are 22 times more memorable than facts. Stories capture attention, make messages stick, and help audiences connect emotionally with the idea.Instead of simply listing key elements like the problem, solution, and business model, Robin encourages entrepreneurs to weave these into a narrative. For example, sharing a personal experience that led to discovering a broader market problem can make a pitch far more engaging. But crafting the story is only 50% of the challenge. The other half is delivering it in a compelling and captivating way. Use of humor: Is it a good idea?Humor can be a powerful tool in a pitch. In settings where multiple pitches happen in one day, a well-placed joke can help you stand out. Self-deprecating humor, in particular, can enhance authenticity and build trust.However, there’s a balance to strike. A little humor can enhance your message, but too much can shift focus away from your idea and make the pitch feel unprofessional. The key is to keep humor spontaneous and natural. It could be perfect to use it at the beginning to break the ice.The effectiveness of humor also depends on your personality and the audience. If humor fits your style and aligns with the general tone, it can work well. However, forced, inappropriate, and excessive jokes can damage credibility. Common pitching pitfallsOne of the most common causes of pitch failure is technical glitches, especially with live demos. Robin mentioned the infamous Surface tablet pitch where Microsoft executives struggled with a malfunctioning device. Given this, Robin recommended always testing tech thoroughly and having a plan B.Another example of failures is Steve Ballmer’s overly enthusiastic pitch, which became more entertaining than convincing. This situation is one more proof that balance is a must.Cornerstones of investor relationship buildingA common misconception is that a 10-minute pitch will immediately secure funding. In reality, a pitch is just the starting point of a longer relationship-building process with investors. The goal isn’t just to impress them during your short speech, but to open a conversation that leads to follow-up discussions and eventual trust. Ideally, you will be able to reach a stage where investors approach you because your pitch, press coverage, or buzz around your idea makes them curious.Tailoring your pitch format to the context is crucial. At networking events, a clear and compelling one-minute or even two-sentence pitch can spark meaningful conversations. If you struggle to summarize your startup in a few lines, it may indicate you haven’t yet clarified your core idea. Meanwhile, a full 10-minute pitch should still leave room for dialogue and relationship-building, not just persuasion.Trust and honesty are essential. Trying to hide flaws or challenges can backfire. Investors are experienced and will uncover the truth eventually. Finally, doing your homework on investors is key. Each investor has a specific focus, budget range, and strategic interests. When you understand this, you can tailor your pitch to align with their goals. Moreover, some successful founders also keep investors in the loop with regular updates. This ongoing communication builds familiarity and trust, increasing the likelihood of future investment when the timing is right.The myth of the perfect first pitchOne of the most persistent myths about pitching is the belief that you only get one shot and that it has to be perfect. In reality, very few successful entrepreneurs deliver a flawless pitch the first time. Pitching, like any skill, improves with practice, iteration, and feedback.Take The Beatles, for example: they played over 1,200 live shows before landing their first record deal. Similarly, Jeff Bezos held around 60 investor meetings before raising Amazon’s first million dollars.Pitches evolve. The more you present your idea, the more you learn. With time, you can better realize where people lose interest, which questions come up repeatedly, and what truly resonates. That feedback loop is vital. If multiple investors point to the same weakness, it’s a signal to adapt your message or your business model.Failure is just a part of the process. You can’t succeed without failing along the way.Robin explained that entrepreneurship is rarely a smooth ride. It is more like a roller coaster filled with highs and lows. The way you interpret those ups and downs can make all the difference.If the goal is purely to make money as quickly as possible, the pressure can become overwhelming. Every setback feels like a crisis. However, if the journey is seen as a learning process or a chance to grow, experiment, and improve, then failures become valuable lessons rather than crushing defeats.This perspective applies equally to pitching. Viewing a pitch as a “make-or-break” moment only increases the pressure and anxiety. But if pitching is approached as an opportunity to learn, get feedback, and refine your message, it becomes part of a growth process. The stakes are still high, but the mindset is healthier and more sustainable.How to manage stressManaging stress before and during a pitch is also crucial. Science shows that how we perceive stress plays a major role in how it affects us. If you view stress as a sign that your body is preparing to perform, it can actually enhance your performance. But if you see stress as a threat or a sign of impending failure, it can quickly become debilitating.There are many personal strategies to manage stress, including physical activity, breathing techniques, or even small rituals.Besides that, preparation remains the most powerful antidote to stress. The more prepared you are, the more confident you will feel. But preparation alone isn’t enough. Practicing on stage, in front of an audience, is essential to becoming a great pitcher.AI in pitching to investors: Assistant, not replacementThe current AI hype has certainly influenced pitching, but it can’t replace the human element. As long as humans are making investment decisions, connection remains highly valuable. Pitching through avatars or fully AI-generated videos may deliver a polished message, but it lacks personal connection, which is critical. Investors want to evaluate you, your passion, your credibility, and your commitment. You can’t just sell an idea. You need to show who they will be working with.AI is best used as a co-pilot. It can:Help craft compelling slides;Speed up research;Improve storytelling structure;Offer suggestions on clarity or tone;Simulate investor feedback or likely Q&A questions.For instance, AI can critique your pitch from an investor’s perspective, helping spot missing elements or test how your story holds up under scrutiny. While not all feedback will be useful, it can highlight blind spots or spark new thinking.AI can also help founders prepare for the Q&A session by generating possible questions. Pitching and Q&A: Key tipsAfter the adrenaline rush of a pitch, many entrepreneurs make the common mistake of answering questions before fully hearing them. It’s important to listen carefully to the entire question before responding.During Q&A, avoid getting defensive or attacking the questioner. Investors always want to see that you are open to feedback and able to handle criticism professionally.A useful strategy is to prepare backup slides and “go-to” messages. They should include key points you want to reinforce throughout the Q&A.Structure of a pitchA pitch should have a clear beginning and end, and both are crucial. It’s best to start by connecting with the audience. You can share a personal story, a striking use case, or a key number that highlights the problem. You shouldn’t jump straight to the solution. Instead, it is recommended to focus on why the problem matters.The problem-solution fit must be clear and simple. If the audience doesn’t understand this early on, the rest of the pitch won’t land. This is the backbone of your presentation.To succeed, you need to close with a strong summary of your company, the problem you are solving, and your solution, or finish with your mission. A memorable opening and closing make your pitch much more powerful.Pitch mantra: Keep it short and powerfulInstead of long mission statements, every startup should have a mantra. It is a short, sharp phrase (even just three words) that captures the essence of the business. It helps founders distill their core purpose. It clarifies your thinking and gives others a clear, memorable takeaway.You can use it to open or close your pitch for a strong impression.Talking too much vs. too little in a pitchBoth extremes can hurt a pitch. But in practice, founders are more often guilty of talking too much. It’s rare to see a pitch where too little is said. More commonly, there’s information overload.But humans have a limited capacity to process information quickly. A pitch should be clear, focused, and paced. The perfect pitch in one wordMax asked Robin to describe the perfect pitch in just one word. And teh answer was: passion.Passion shows the founder’s drive and commitment. These are crucial qualities for surviving the highs and lows of entrepreneurship. But passion alone isn’t enough.Equally important is evidence. It is proof that the idea works and that the business case makes sense. A perfect pitch combines both passion and proof.Examples of great pitchesAccording to Robin, there are many strong examples today, especially from female entrepreneurs. One standout was Jasmine Tagesson, founder of Hormona, who delivered a compelling pitch at Slush 2021. Within the first 10-20 seconds, she clearly articulated the problem and created an immediate connection with the audience. It was concise, impactful, and emotionally resonant.A more iconic example is Steve Jobs during the launch of the iPod. His pitch had excellent pacing. He sped up to build excitement and slowed down to emphasize key points. He also delivered a strong competitive analysis, clearly showing the shortcomings of existing products and positioning the iPod as the superior solution. What entrepreneurs should know before a pitchAt the end of their discussion, Robin provided some advice for those who are preparing to make a pitch:Show energy, drive, and genuine belief in your idea.Be well-prepared, know your numbers, and demonstrate that you’re serious and committed.Build a match with investors. Be collaborative and easy to work with. Listen to feedback.In addition, Robin shared a useful framework. It is the four Ps of pitching:Profile. You need to explain who you are and why you are pitching this.Plan. It includes the structure, flow, and logic of your pitch.Proof. You should share evidence, market validation, and data to support your claims.Performance. How you deliver your pitch also matters. Pitching isn’t just a startup ritual. It’s a universal skill that applies to anyone trying to convince others of an idea, a project, or a vision. Whether you are pitching to investors, partners, or even your parents, the same principles will work. You need to be honest, open, and well-prepared.Want to get more actionable insights from business experts and tech leaders? New episodes of the Innovantage podcast will be available soon. Don’t miss them!

Discussions about the progress made in the AI world today are very often accompanied by assumptions that, quite soon, it will become more feasible to hire AI instead of real people. At first glance, it may seem that such concerns are indeed well-grounded. But is that the case? To talk about this and explore the real capabilities of AI agents, Max Golikov, the Innovantage podcast host and Sigli’s CBDO, invited Frank Sondors to the studio.Frank’s career started in big tech at Google. This allowed him to take a closer look at the power of machine learning, not just in advertising but also as a tool to drive business growth.Later, he worked at different companies, focusing on big data and AI. When he joined a company called Whatagraph, he began to question traditional approaches to scaling sales teams. At that time, the mindset was “growth at all costs”. This was often achieved by hiring more salespeople. But Frank saw this as flawed. Most sales teams suffer from high attrition, and only a small percentage of specialists deliver meaningful results. In his experience, for every 10 people that you hire, only one is a natural salesperson. Another 2 or 3 can be trained, while the remaining majority lack the motivation or even don’t fit for the role.This insight led him to co-found Salesforge, a platform designed to help companies build a sales pipeline with minimal headcount. The company uses big data and AI to automate repetitive sales tasks. By embedding agentic capabilities into the software, Salesforge enables businesses to rely less on average performers and empower their top salespeople to bring significantly higher output.AI agents: Easy explanationA lot of businesses today aim to hire so-called “autonomous humans”. These are individuals who can fully own a part of the business without constant oversight. For example, salespeople are expected to manage their pipelines, close deals, and solve problems independently. In such a situation, leadership can provide guidance instead of supervision.This concept parallels how AI agents function. Like autonomous employees, AI agents are given a specific goal and the context for achieving it. In a sales use case, an AI agent can get a task to reply to a prospect using information such as a sales playbook, pricing, or FAQs. Its objective is to move the conversation forward to a micro-conversion, like booking a meeting.Unlike traditional chatbots that rely on predefined scripts, AI agents can reason through incoming replies and use the available context to respond intelligently and dynamically. This increases the likelihood of getting the desired outcome.AI agents for sales teamsFrank believes that when it comes to integrating AI agents into sales teams, there is no one-size-fits-all solution. The ideal setup should always depend on the company’s structure and sales strategy.In large organizations with 50 or more salespeople, human representatives usually focus on high-value enterprise accounts where deal sizes and sales cycles justify the investment. However, working with smaller accounts, for example, in the SMB segment, often isn’t cost-effective due to the lower return per deal.This is where AI agents excel. They can be deployed to handle outreach via different channels, including email or LinkedIn. They can engage SMBs with tailored messaging to book meetings, visit a product page, sign up on the platform, etc.By assigning AI agents to lower-priority or high-volume segments, businesses can maximize efficiency. They free human reps to concentrate more on strategic deals.Frank also mentioned another key use case for AI agents. Many early-stage startups, with fewer than 10 employees, struggle with prospecting. Quite often, it happens because the founders are overwhelmed with product development and customer management.According to Frank, a startup’s survival is based on two things: building a great product and selling it effectively. If pipeline generation falls by the wayside, there are serious growth risks.Founders have several options:They can do the prospecting themselves (if they have the time and skills).They can hire an agency (it is a rather expensive approach).They can turn to AI agents (In this case, they can simply configure an AI agent within their sales software, which will handle outreach autonomously).Are there any limitations of AI agents?Despite the inspiring examples that showcase the potential of AI agents, there are a bunch of downsides that businesses should be aware of.One of the biggest pitfalls isn’t the technology itself. It is the context in which it is used. For example, many smaller companies approach Salesforge looking to scale outreach. But the problem is that at this time, they haven’t even achieved product-market fit. In those cases, it doesn’t matter whether outreach is done by humans, agencies, or AI. All the efforts will be bound to fail.The second thing is that even with product-market fit, companies may lack channel fit. For instance, not every customer will respond well to cold outreach via email or LinkedIn. If a company has chosen the wrong acquisition channels, AI agents won’t magically fix this problem.Frank compares AI agents to Google Ads. You invest in it to generate conversions. But if it doesn’t perform, you churn. At Salesforge, the team is actively learning where AI agents work best. They consider different industries, deal sizes, and other variables to create a full picture.Frank also mentioned some other challenges with AI agents. For example, when you task AI with writing emails, it often fails to create messages that feel genuinely human. Depending on how the agent is built and orchestrated, the output can look as obviously AI-generated. For many customers, it may be a red flag today.Crafting AI-generated emails that look like human-written ones requires significant effort. It involves careful prompting, rich contextual data, and smart engineering behind the scenes. Tools like n8n or Make.com can help automate workflows, but if the end result feels robotic, it reduces the chances of getting a response.Four pillars of success in salesAccording to Frank, success in modern sales depends on what he calls the core four pillars.Pillar 1. Email deliverabilityThe first and most overlooked factor is whether your emails are reaching inboxes. Deliverability, or getting messages into the primary inbox, not spam, is foundational. Great sales outreach starts with using software that consistently ensures this. It doesn’t matter how strong your targeting or messaging is if no one sees your emails.Pillar 2. Email infrastructureThe second pillar involves the email infrastructure, which includes software and hardware components that impact deliverability and sending reputation. Frank stresses that a well-configured infrastructure improves overall email success.Pillar 3. Message itselfThe third pillar is where AI agents are currently making the biggest impact. It’s email copy.Preparing a high-quality, personalized email often takes a human around 15 minutes. It involves researching the prospect on LinkedIn, checking their company website, and finding relevant angles for personalization. Despite that effort, the harsh reality is that 90% of emails go unanswered. Quite often, it happens because timing is off or the recipient simply isn’t in-market.That’s why AI agents can be so powerful. They can combine two essential datasets:Seller data (what your company does, the problem it solves, value props, pricing, and the cost of inaction);Buyer data (publicly available information about the prospect, such as their role, industry, behavior, or company context).By merging these, AI can generate emails that are highly tailored. Such emails can be written in the recipient’s native language, which can dramatically increase response rates. For example, sending outreach in French to prospects in France can double reply rates. But there is a catch. When people respond, they usually expect the conversation to continue in French. So you need to have a French-speaking sales rep ready to continue the communication, or you will lose trust.Pillar 4. TargetingNo matter how good your emails are or how well they are delivered, if you are reaching out to the wrong people, you are wasting time and money.Historically, SDRs or marketers worked with large lists pulled from databases and manually qualified leads. It is an extremely time-consuming and error-prone process. Now, AI agents are starting to take on this task more effectively.Frank said that AI is better than humans at list qualification for one simple reason. The error rates are lower. AI can process thousands of leads using consistent logic, flagging which contacts match your ICP and which don’t.Where AI agents excelThe efficiency of AI agents greatly depends on the deal size and the sales cycle length. For instance, for high-value, long-cycle enterprise deals, the use of co-pilots that assist humans is far more realistic than full automation. Enterprise sales are still deeply relationship-driven, and the risk of an AI making an error remains a sticking point. The larger the stakes, the less businesses are willing to fully delegate tasks to AI.However, in low-ticket deals with short sales cycles, AI agents shine. In this space, autonomy and speed greatly matter. Businesses can deploy AI agents to run scalable outreach at high volumes.Despite the current limitations, AI agents already provide impressive performance for small-account outreach. Frank sees reply rates of 2-2.5%, with 10-20% of those replies being positive. Even with high processing costs, the return on investment justifies scaling these agents for such tasks.Speaking about the future, Frank mentioned the value of agentic swarms (not standalone agents, but interconnected teams of AI agents, each handling different parts of the sales process). Businesses should view such swarms of AI agents as digital SDR teams. One agent can handle list building, another crafts outreach, another manages follow-ups, and another coordinates calendar scheduling.Future of AI agents and humans in businessAI agents are already transforming how companies recruit, build processes, and optimize operations. It raises a big question: Will humans still remain in the business in the future?Every business has repetitive tasks, and smart companies are trying to automate those tasks using AI agents. As Frank shared, at Salesforge, they started aggressively doing this a couple of months ago by implementing n8n, an advanced workflow automation tool. It helps to build complex flows, trigger AI agents, write code, and manage operations without increasing headcount.That’s the goal of such efforts: to scale output without scaling team size. Salesforge plans to create 1,000 n8n flows by the end of 2025, which means about 10-20 new flows per week. Everyone at Salesforge contributes to this by identifying repetitive tasks they want to eliminate.This automation-first mindset also shapes how they approach hiring. Frank explained that when they face a business problem, they ask the following questions.Can we solve it with an off-the-shelf AI agent?If not, can we build a custom automation in n8n?If that fails, can we bring in an agency or consultant?If not, only then they we consider hiring a person.They have chosen such an approach because today hiring is slow, expensive, and competitive, especially in tech. The role of an "American mindset"Frank also mentioned the importance of what he calls the American mindset. It is based on staying ahead of the competition by improving efficiency, cutting unnecessary headcount, and constantly optimizing operations. In his opinion, businesses that fail to innovate or streamline simply let others outperform them.Some industries haven’t changed in 20 or 30 years, and Frank finds that deeply concerning. Meanwhile, countries like the US and China continue to evolve at enormous speed. If European businesses don’t adopt the same urgency, foreign players will enter the market and show how it should have been done.Experimentation in businessAccording to Frank, experimentation is a big reason why many companies are super successful. In his words, great businesses are built on the principle of improving by 1% every day. But that kind of consistent progress doesn’t happen by accident. It comes from deliberate testing and learning.He emphasized that without experimentation (it can be A/B testing, trying new features, or optimizing internal processes), businesses can’t grow. A good example here is Google. While its homepage may seem static, the company is constantly running thousands of experiments, even shifting a button by a single pixel to see if it drives better results. These micro-optimizations, powered by vast traffic and rapid testing, are part of why Google stays ahead.Continuous optimization for attention and valueIn today’s crowded digital landscape, dominating attention isn’t a matter of chance. It is the result of relentless optimization. Whether a business is B2B or B2C, Frank believes it must become focused on intersecting with their potential customers where they spend their time. For most professional audiences, that means LinkedIn.But what content will be the most valuable for them? This varies by audience. That’s why it is essential to experiment. Frank himself regularly tests different content types to measure engagement and refine his approach. Optimization isn’t just about the content itself, but about learning what resonates. It requires daily posting, ideally once or even twice a day, from Monday to Friday. While this level of effort is resource-intensive, it’s justified given the organic reach and brand authority it can generate. At present, Frank doesn’t see AI agents as capable of producing the nuance or authenticity required for this kind of content strategy. However, that could change in the future.He also noted the emergence of AI-generated avatars, fake but highly realistic video personas that are already being used in some marketing campaigns. As AI moves from text to voice and video, Frank sees 2025 as a turning point in the “video phase”. This year, we will increasingly encounter synthetic content that will look quite realistic. Therefore, businesses must be even more thoughtful and strategic in how they capture attention and build trust.While most of this work still relies on what Frank calls the “human puff”, he sees a growing role for AI agents in the near future. His company’s head of YouTube has developed a tool that analyzes video assets and helps repackage them for LinkedIn in ways designed to boost engagement. The tool recommends post formats, hashtags, which companies or individuals to tag, and other elements that maximize visibility and performance.This hybrid approach, powered by human-led creativity and AI-driven optimization, can be viewed as the future of content strategy. AI agents are not ready to replace humans in storytelling, but they are increasingly used in guiding what types of content are likely to succeed.Based on what we’ve heard from the experts who visited the Innovantage podcast studio earlier, this hybrid formula is quite applicable to many domains today. AI is becoming more mature and advanced, but a human touch is still a must.To learn more about the power of technologies in the business world, don’t miss the next podcast episodes.

In today's digital-first world, trust isn’t an afterthought — it’s a critical requirement. Data breaches, project failures, and inconsistent delivery have made businesses more cautious than ever about who they work with. At Sigli, we believe that trust should be built into the very core of our operations — not just our technology stack, but our team.That’s why, as of March 3rd, 2025, every new hire at Sigli will undergo a mandatory background check, powered by our new partnership with Certn.Why background checks matter in techIn many software and AI development companies, background verification is either sporadic or absent altogether. But as a partner entrusted with sensitive data, mission-critical systems, and long-term strategic initiatives, we believe clients deserve full confidence — not just in our code, but in the people behind it.Why Sigli chose CertnCertn is a globally recognized leader in background screening solutions, designed for speed, compliance, and scalability. Unlike traditional providers that rely on fragmented databases and slow turnaround times, Certn leverages AI and direct integrations with thousands of global data sources to deliver background checks that are:Fast – Most reports are completed within minutes, not days.Global – Certn covers 200+ countries and territories, enabling seamless checks for distributed and remote-first teams.Compliant – Built to comply with international standards like GDPR, SOC 2, and FCRA.Candidate-friendly – Designed to respect privacy and provide transparency during the process.By integrating Certn into our hiring flow, we ensure that our growth doesn’t compromise our standards — and that every team member is vetted with the same care, no matter where they’re located.What this means for our clientsFor our clients, this partnership represents more than a new policy. It’s a message: when you work with Sigli, you’re working with a team you can count on — not just for technical excellence, but for integrity.Sigli's clients trust us with more than just code. They trust us with business continuity, innovation pipelines, customer data, and strategic outcomes. Knowing that each Sigli team member has passed a robust, standardized verification process adds another layer of assurance — one that matters more than ever in today’s landscape.Raising the industry standardIn many ways, background checks have been overlooked in the tech sector — seen as a corporate necessity only for certain roles or industries. At Sigli, we believe that’s due for a change. High-trust partnerships require high-trust teams. And high-trust teams begin with verified people.This isn’t just a checkbox for Sigli — it’s a conscious choice to lead by example. We hope it sets a new benchmark for what clients expect, and for how companies approach growth responsibly.The bottom lineSigli is not just building AI products. Sigli is building a company where trust is engineered into every detail — from the way we code, to the way we hire.Thanks to our partnership with Certn, we’re confident we can scale that trust as we grow. Line by line. Hire by hire.