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Tech Race Summit Brings Top Tech Leaders To Warsaw

by News Editor

August 21, 2026

Tech Race Summit, organised by SOFTSWISS, will take place in Warsaw on 10 September 2026 at Centrum Praskie Koneser, Plac Konesera 8. The event will bring together more than 30 international speakers and 1,000 attendees for what the organiser describes as “the first cross-industry forum to exchange ideas, technologies, and expertise, driving the future of large-scale digital products.”

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The summit gathers engineers, technology executives, infrastructure specialists, and product teams to discuss how companies respond to growing technical complexity, cybersecurity challenges, and the rapid adoption of AI across business operations and consumer products. Speakers and contributors have been confirmed from big-name companies including AWS, Oracle, Cloudflare, Google, Fastly, Tesla, PandaDoc, Shazam, Gcore, ScyllaDB, and others.

The Keynote Line-up

Andrey Doronichev, founder and CEO of Optic and former Google executive, will deliver a keynote on how AI is changing industries and work. Doronichev spent 14 years at Google, where he helped develop products used by billions of people worldwide.

Javier Verdura, Global Director of Product Design at Tesla, will present “Building High-Performance Teams: Lessons from Tesla.” His session will explore how a globally recognised technology company builds teams capable of delivering products at speed while maintaining quality and innovation.

Mikita Mikado, co-founder and Chief Product Officer of PandaDoc, will deliver “Building the Next Silicon Valley Businesses.” PandaDoc is an agreement-management company that reached a valuation of $1 billion in 2021. In his keynote, Mikado will share lessons from scaling PandaDoc into a global software company.

They are joined by Dhiraj Mukherjee, co-founder of Shazam, and Artur Bergman, founder and CTO of Fastly, whose sessions will address technology shifts and the future of internet infrastructure. Ivan Montik, founder of SOFTSWISS, is scheduled to open the summit.

Cross-Industry Forum For High-Load Businesses

As online gaming businesses grow across regulated markets, they face many of the same questions as global technology companies, especially how to build high-performing teams, develop products at scale, and compete for talent whilst maintaining speed of execution. By bringing together leaders who have been there, done that from Tesla, PandaDoc, Amazon Web Services (AWS), Oracle, Cloudflare, and other global technology companies, Tech Race Summit creates a forum where these experiences can be shared across industries.

The programme covers cloud architecture, artificial intelligence, cybersecurity, engineering leadership, observability, product development, and company building. All sessions are held in English.

Sergey Kastukevich, Chief Technology Officer at SOFTSWISS, describes the summit’s origin as follows:

“Tech Race Summit was created to bring together people solving difficult technology problems and to explore what the future of technology holds.”

Kastukevich adds to the cross-industry framing:

“The technology challenges facing iGaming today extend well beyond infrastructure. Building successful technology companies also depends on leadership, product thinking, and the ability to scale teams as the business grows […] Our goal is to give attendees practical insights they can apply to their own organisations, regardless of the industry they work in.”

Three-Track Programme

The summit runs across three parallel conference stages. The Vision Track features keynotes and discussions about AI, infrastructure, cybersecurity, and technology strategy. The Solution Track focuses on technical sessions and case studies from engineers and architects working on modern digital systems. The Experiment Track covers technical deep-dives, implementation lessons, and engineering practices.

Attendance And Registration

The offline event is sold out. Online streaming tickets remain available through the event website. Sponsorship information is also available through the summit’s partnership page.

For more information and ticket details, follow the link here.

About SOFTSWISS

SOFTSWISS is an international technology company that has developed solutions for the iGaming industry since 2009. The company provides software for managing online gaming projects and supports more than 1,500 brands worldwide. SOFTSWISS’ product portfolio includes the Casino Platform, the Game Aggregator, the Sportsbook, and the Prediction Markets Platform. The company has more than 2,000 employees across its international locations, including Malta, Poland, and Georgia.

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Google’s Gemini Has A Branding Problem As AI Apps Grow More Complicated

by News Editor

August 27, 2026

Google’s latest Gemini update highlights a broader problem in consumer AI: companies are increasingly turning internal tools and capabilities into separate products that users must learn to navigate.

In its announcement of new Gemini Live voice features, Google said users should not have to determine whether a task requires Spark, Daily Brief or a simple inbox search. Yet those are precisely the distinctions the Gemini app currently asks users to make.

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Too Many Features, Too Many Names

Gemini users can switch between Chat, Spark and Daily Brief, each with its own icon and place in the app. Rather than simplifying the experience, the growing list of branded features risks making the underlying technology more visible than it needs to be.

Daily Brief illustrates the problem. Google describes it as a source of personalised, proactive updates based on information from services such as Gmail and Calendar. In practice, however, some of its suggestions can feel less like useful assistance and more like unsolicited reminders about previous searches or unfinished research.

Spark has almost the opposite problem. The feature can act as an AI agent capable of completing tasks on a user’s behalf, but packaging that capability under a separate brand forces users to understand when and where they should use it.

A simpler approach would be to let users describe what they need and allow Gemini to determine whether a standard response, an agent or another capability is appropriate.

Gemini Is Not Alone

Google’s approach reflects a wider trend across the AI industry, where companies increasingly expose the architecture of their products through separate modes and branded features.

Anthropic, for example, asks users to distinguish between Claude’s standard chat experience and Cowork. ChatGPT similarly separates Chat and Work. For consumers, these distinctions can turn what should be a simple interaction into a question about which product or mode to use.

That approach is largely driven by how AI systems are built, rather than by how people naturally think about using them.

Apple Takes A Different Approach

Apple’s strategy for Siri offers a contrasting model. Rather than requiring users to learn a new AI interface, the company is integrating AI capabilities into tools people already use, including Spotlight, Photos, the camera and voice requests.

That approach could prove more effective as AI becomes a mainstream consumer technology. Users do not necessarily need to understand which model, agent or feature is handling a request; they simply need the system to complete the task.

Text-Based AI Offers A Simpler Model

The popularity of text-based AI assistants points in the same direction. Services such as Poke, Ollie, Lindy, Orchid, Lucas, Folk, Tomo and Instinct largely reduce the interaction to a familiar interface: send a message and let the assistant determine what needs to happen next.

That simplicity removes an additional layer of decision-making. Users do not need to choose between Chat, an agent or a specialised feature before asking for help.

As a16z investment partner Justine Moore recently argued, consumers increasingly want an AI assistant to feel like a contact they can message rather than another application they must learn.

For Google and its competitors, the challenge may therefore be less about adding capabilities and more about hiding the complexity behind them. The AI that wins mainstream adoption may ultimately be the one that asks users to understand the least.