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Executives are no longer measured by the weight of their title but by the scale of what they create, especially in an era reshaped by AI. The most effective leaders now marry vision with execution, using technology as a co-pilot to accelerate outcomes while keeping human judgment at the center. Strategy isnt declared anymore; its built in real time, constantly iterating and leveraging AI to turn ideas into outcomes faster than ever. The builder CEO is a visionary who architects systems, coaches teams, and removes obstacles through hands-on involvement. Heres how executives with a builder leadership style are involved with the day-to-day work and unite teams around a shared mission. FROM VISION-SETTER TO VELOCITY ARCHITECT The builder mindset thrives where growth, technology, and disruption collide. Customers demand speed, relevance, and trust simultaneously. Meeting those demands requires leaders who are adaptive, accountable, and relentlessly driven by outcomes. Builders shorten decision loops by being present where the work happens: sprint reviews, demos, and product trade-offs. Their involvement clarifies priorities, reduces friction, and ensures strategy is lived at every level, not left on a slide deck. Stability still matters, but speed is the differentiator. Builders create systems that allow rapid testing without recklessness: guardrails, rollback plans, and clear accountabilities. They collapse silos by taking ownership of the P&L, customer outcomes, and cross-functional metrics. Marketing, product, operations, and sales work as one team because builders demand it. Builders flatten hierarchies and empower autonomy, but with accountability. Teams know exactly which calls they can make, which require escalation, and how success is measured. When a feature underperforms, the team doesnt wait for a quarterly review. They assess metrics, test hypotheses, and implement fixes in days, not weeks. This rhythm of experimentation and fast learning ensures companies adapt in real time to customers and markets. The builder is always asking, What can we test now? and What can we improve today? BUILDERS IN AN AI-FIRST WORLD The builder archetype matters most in an AI-driven commerce environment. AI is the co-pilot bringing precision and scale, while human oversight preserves trust. Executives who design for measurement, keep human judgment where it counts, and integrate AI thoughtfully create enduring advantage. The best builders set a single customer outcome as the north star, participate directly in product reviews, require every experiment to have guardrails, and assign clear ownership for cross-functional work. They standardize where possible but keep space for human judgment where it drives value. AI, in their hands, is not a replacement but an amplifier, removing repetitive work so teams can focus on judgment, creativity, and engagement. This balance accelerates both growth and employee buy-in. THE HUMAN CORE OF BUILDING Builders arent flawless. Over-involvement can slip into micromanagement, while too much autonomy without boundaries breeds chaos. The remedy is clarity: metrics, cadence, and transparent ownership. Most importantly, builders lead with humanity. They celebrate wins, fail fast, and then mine failures for lessons, and ensure every team member understands the impact of their work. They know speed without trust is brittle, and systems without people are hollow. The modern C-suite is no longer judged by how many strategies it produces but by the outcomes it builds and the speed with which it learns. In an era defined by complexity and constant change, the builder mindset is the defining quality of leadership. The leaders who shape the next decade will be those with builder DNA. Elizabeth Buchanan is chief commercial officer of Rokt.
Category:
E-Commerce
IT development has been around for more than 60 years and it has undergone radical transformations from the emergence of the first programming languages and OS development to the internet boom and the current AI era. Although programming tools and approaches are constantly changing, one thing remains constant: Only those developers who can adapt and master new knowledge and skills survive. Im the chief software officer of a 70-strong team that designs a predictive maintenance system (PdM): A solution based on the Industrial Internet of Things (IIoT) and AI. Without continuous growth, our developers cannot remain competitive. The same is true in nearly every industry; when individuals stop working on their skills, a company can lose its edge. Heres a look at how we have created a system where professional development is an integral part of the work and how we help developers avoid and overcome stagnation. MUST EVERYONE GROW? Every team has specialists who prefer routine work, and to some extent teams need those people who do well in a position that does not require growth. But for a project to develop steadily, I believe such experts should not exceed 20% of the team. If their share is higher, other developers will eventually start to emulate their passive colleagues. Optimally, the majorityabout 80%should be actively developing and improving their expertise. Not everyone in the 80% needs to generate new ideas. The driver-to-performer ratio depends on the company’s development stage. A start-up needs 80% drivers because theyre the ones who forge ahead. Conversely, in mature companies, sustainable quality leads require constant hard-skill honing rather than a fountain of ideas. DEVELOPMENT THROUGH SMALL ACTIONS Encouraging developers to advance their skills can start small. For example, one underrated tool is having a person write tests to check their code, which is mandatory for everyone on our team, including senior specialists. Many teams use code reviews more often than writing tests. But when a developer writes a test, they may find that their method or function is too cumbersome, with many exceptions and dependencies, and its almost impossible to test it entirely. As a result, they begin redesigning their code and look for solutions to improve its logic. They study additional materials, such as technical blogs and best-practice guides, and consult with colleagues to deepen their expertise. However, tests have limitations. Once a person learns patterns, writes tests quickly and confidently, growth stops and routine begins. This tempts developers to automate their work. CASE-BY-CASE APPROACH There are many reasons why professionals pause in their development. They may be satisfied with their position/skills, bored, or facing challenging external circumstances. For example, most of our developers are Ukrainian, and our work has been affected by Russia’s full-scale invasion of Ukraine, which has been a great stress to everyone. Team members have responded differentlyapproximately 30% lost their motivation to do anything, and another 30% have taken a deep dive into their development. One strong junior immersed himself so deeply in his studies that in just six months, he mastered senior level theory. The rest simply adapted and returned to their usual pace. After 10+ years in tech management, I realized that everyone has different motivations for advancing their skills. Your task is not to pressure them but to understand what is holding them back and what incentivizes them. Some practices that Ive found helpful when developers stagnate are: Provide new context. Offer the developer an opportunity to work on another project or change domains. A new environment presents new challenges, requires adaptation, and learning. Present challenges. Give the developer a task that requires creative thinking and independent research. Dont provide an answer. This will let them take initiative and responsibility for the result. Encourage learning. If a person seeks development opportunities provide them with resources. For example, compensate for conference or workshop participation. Adjust expectations. Sometimes a person is satisfied with their expertise. In this case, its important to agree: If the developer doesnt want growth, they dont seek promotion. Each specialist must have their own development plan. We draw it up twice a year, based on in-depth assessment. We set goals that meet the company’s expectations and the developer’s interests. THE COMPANY’S SYSTEMATIC APPROACH In my experience, developers often stop focusing on advancing their skills when they are overloaded. After intense work, they no longer have the energy to learn. Learning by working is our main principle. We believe developers can improve their skills through hands-on experience, so we integrate this approach into employee development plans. Daily: Giving them a short technical digest and work with code through tests and reviews. Two-week sprints: Each sprint includes two to three days when a developer can try a new approach, technology, etc. Once a month: Internal clubs sessions in each department lasting one hour to 90 minutes where they can share experiences, run practical workshops, and exchange best practices. Once every three to six months: Three-hour sessions with external speakers, advanced training. FINAL THOUGHTS Im convinced that development begins with dialogue. You should understand what motivates a person. I also believe that there are no wrong decisionsonly different points of view. Developers shouldnt be afraid to disagree because critical thinking and constructive discussion always help team growth. Illia Smoliienko is the chief software officer for Waites.
Category:
E-Commerce
How did you get to this article? Maybe you opened a link in an email, or you navigated from the Fast Company home page. Perhaps you Googled agentic AI and this figured in the results. The point is, you almost certainly clicked, scrolled, tapped, or typed your way here, because thats the digital grammar that shapes nearly every online experience. But that 30-year-old paradigm is about to change. Agentic AI is ripping up the rulebook, by creating a new layer of intelligent, autonomous mediation between us and the digital world. Personal shopping agents will handle routine purchases, while in the workplace, agents will automate workflows and streamline procurement. Investors are excited, of course. Earlier this year, more than half of the Y Combinator startups chosen for its accelerator program were working in agentic, while the three biggest Q1 acquisitions in the AI sector involved companies building agentic enterprise technologies. This is because agents are about to transform how work gets done, how businesses operate, and how systems interact. And nowhere are the consequences more profound than in e-commerce. CLICKLESS COMMERCE Today, e-commerce success depends on online visibility, with search driving half of website traffic and fuelling the $75 billion search engine optimization (SEO) industry. But agentic AI upends the traditional business model. For agents, displays and brand content are less important. Merchants must focus on making product data machine-legibleaccurate, structured, and accessiblebecause machines wont browse sites. Theyll connect directly to sales platforms and databases via APIs, creating a parallel e-commerce track that serves agents rather than human shoppers. Building out that machine track will be a critical job for merchants, fintechs, software companies, and financial institutions. For merchants, an early task is compiling and structuring data in a way thats visible and relevant to agents. Another is creating seamless connections between merchant systems and agent systems. The good news is that the connective tissue is already here. New protocolsmodel context, agent-to-agent, and agentic paymentsnow enable agents to connect, communicate, and transact autonomously. MARKETING TO MACHINES: A NEW INDUSTRY For retailers, one question looms: How do I market to machines? As SEO evolves for human audiences, new disciplines are emerging to optimize digital environments for AI agents. Agent engine optimization helps make digital spaces easier for agents to understand and use. Agent interaction design focuses on how they communicate with platforms, APIs, and other agents to get things done for users. These areas connect with generative engine optimization, which improves content so AI systems can better generate recommendations and make decisions. Taken together, they signal a new ecosystemone that will create fresh roles, unlock new value streams, and redefine how businesses compete in an AI-driven economy. Another way of attracting machine buyers is to reward them. This is the agentic version of e-commerces affiliate system, where publishers, partners, and influencers are paid a commission for driving sales. Theres feverish speculation as to how an attribution mechanism may work, and who will get paid. There are plenty of challenges toonot least verifying agents identities, knowing with confidence which agent influenced the sale, and preventing fake agents from gaming the system. But the opportunities are apparent. The affiliate market is predicted to double in size by 2030, even without agents. FACE THE HEADWINDS Certain issues will require regulatory clarity. Agentic referral will have to be transparent, for example, to ensure fair competition. Then theres the matter of trust. Well need confidence in the agents and the ecosystems they operate in. Giving an autonomous bot spending authority is a big commitment, but getting it right is key to scaling agentic commerce. Ensuring agents can operate across different payment systems, platforms, and legal jurisdictions will also pose technical and regulatory challenges. That said, were about to experience the biggest transformation in e-commerce since it began. This promises to be an era of great innovationa time to build new tools, new ecosystems, and new ways of creating value. Agentic commerce isnt just a tech shift; its a reimagining of how we buy, sell, and connect in a digital world. Ken Moore is chief innovation officer at Mastercard.
Category:
E-Commerce
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