Poland has long been known as one of Europe’s strongest software development and IT outsourcing hubs, supplying engineering talent and enterprise delivery capabilities to companies across Western Europe and the US.
While countries like Germany focused more heavily on fintech or SaaS products, Poland carved out its own service niche. As AI reshapes how software is built, that legacy is turning into a strategic advantage.
Miquido is a Polish software development and AI solutions company headquartered in Kraków. Founded in 2011, the company builds mobile apps, web platforms, AI systems, and enterprise software for startups, scaleups, and large organisations across industries such as fintech, healthcare, ecommerce, and entertainment.
Originally known for mobile development, Miquido has increasingly focused on AI-native software development, integrating generative AI and agentic AI workflows into enterprise environments.
I spoke to CEO Jerzy Biernacki to learn more about the direction and opportunities for Poland and the rise of what he calls Software 3.0.
For Biernacki, Poland’s biggest strength is its talent pool, which is rapidly embracing AI tools and building processes around them to deliver more, faster, without sacrificing quality.
At the same time, while Poland is not yet one of the top ecosystems in Europe, companies like ElevenLabs and DocPlanner are helping lead that charge with massive funding rounds. Specifically in AI, Poland now has two independently developed large language models — BIELIK and PLLuM. This is unusual, especially for Central Europe and even across the EU more broadly.
Poland is alos home to multiple top-tier software development agencies — including Miquido, as well as companies like Netguru, 10Clouds, and Spyrosoft.
From copilots to Agentic AI
The rise of large language models has already pushed software development through several distinct phases, according to Biernacki. In the early days of the AI boom, many believed developers would quickly be replaced altogether as companies rushed to adopt generative AI tools.
“The first phase was: ‘LLMs can be used everywhere, and they’ll replace everyone,’ particularly programmers and developers,” he said.
That narrative coincided with major layoffs across the tech sector, although Biernacki argues many of those cuts were more closely tied to companies correcting pandemic-era overhiring than AI-driven replacement.
Initially, AI coding tools primarily functioned as copilots, helping developers autocomplete code and accelerate workflows within their IDEs. But Biernacki says the market underwent a major shift in 2025 with the arrival of agentic AI coding systems.
“I think the major breakthrough was when Claude Code was released in May last year. That was a turning point,” he explained.
“Agentic AI code generation really became a thing, and it changed the way we work with software development.”
The later release of Codex further accelerated the transition. According to Biernacki, the two platforms now dominate much of the enterprise AI coding market.
“Those two tools basically overtook the market. They now have something like 75–80 per cent of the enterprise segment between them,” he said.
The shift is reshaping far more than coding itself. Biernacki argues that AI is transforming the entire software development lifecycle, from requirements analysis and design to testing, deployment, governance, and validation.
How Software 3.0 Is reshaping software development
As these workflows become increasingly autonomous, Biernacki argues the role of the developer itself is fundamentally changing, evolving toward oversight and verification rather than manual coding.
“The bulk of the work is no longer writing code — because writing code is now relatively cheap — but verification, architecture, governance, and validation.”
He believes automated validation will become one of the most critical layers in AI-assisted software development as enterprises look to safely deploy increasingly autonomous coding systems.
This has led to a shift in local hiring practices, with companies like Miquido placing greater emphasis on soft skills than on whether someone knows a language's syntax perfectly.
In terms of younger hires, Biernacki characterises the importance of university graduates who used AI throughout their studies and are naturally comfortable working with AI. He admits younger hires still need time to adapt to enterprise environments and operational discipline.
“We look for a different skill set now: people who can translate business requirements into prompts and who can work naturally with AI agents.
They also inject fresh energy into teams. Sometimes senior engineers get stuck in existing processes, and having fresh blood helps show alternative ways of working. They’re eager to learn, eager to adapt, eager to test new things. So I think they’re a really valuable addition to company structures.”
"Software 3.0 "creates a new divide between startups and enterprises
The divide between startups and enterprises is becoming increasingly visible in the AI-driven software era as companies adopt to Software 3.0 development workflows.
According to Biernacki, startups are moving far faster than larger organisations because they are being forced to adopt AI-native development practices to survive:
“Honestly, I think startups are leading the charge right now. Startups need to show investors tangible results extremely quickly across software sectors.
They can’t afford not to rely on AI-driven coding workflows — especially for early products and feature development.”
As a result, startups are shipping products and features at an increasingly fast pace. Enterprises, however, operate under very different constraints.
“Startups don’t have to worry as deeply about enterprise-grade security, reputation risk, or massive scalability from day one,” said Biernacki.
“Enterprises have to move more carefully because they need stability.
Their primary concerns are reputation, compliance, security, and governance.”
For software development firms serving enterprise customers, reliability therefore becomes the critical differentiator.
“You can’t achieve that with pure ‘vibe coding’ and no safeguards. You need enterprise processes ensuring quality.”
Biernacki contends that the whole ecosystem is moving from “we provide developers” toward providing augmented delivery systems.
“I think the adoption rate in Poland is probably among the highest in Europe.”
He sees Poland’s edge is not about being the biggest AI market, because clearly it isn’t, but rather having an ecosystem of software companies that spent 10–15 years building enterprise software for Western European and global clients — and are now rapidly retooling around AI.
“The thing Poland may actually be leading in isn’t frontier AI research itself, but AI-augmented enterprise delivery. That’s where I think the country’s real value lies right now.”
Biernacki believes the software industry has now crossed a major inflection point, with agentic AI fundamentally reshaping how software is built and maintained, and leading to a competitive advantage.
“Companies like us have a temporary advantage over companies that aren’t aggressively adopting agentic AI workflows yet.
Though I think that advantage will eventually narrow as others catch up.”
At the same time, enterprises are facing rapidly growing regulatory and compliance complexity around AI systems and software governance.
“There’s also the growing complexity around regulation and compliance in enterprise software,” said Biernacki.
He argues that helping enterprises navigate this increasingly complicated landscape represents one of the biggest emerging opportunities for software companies. Biernacki also believes the industry is experiencing a form of Jevons Paradox, where making software development cheaper through AI actually increases overall demand for software rather than reducing it.
The long-term winners in the AI software era will not necessarily be the companies producing the most code, but those capable of redesigning their organisations around governance, reliability, and operational quality.
“The winners will be companies that redesign their processes around this new reality — including governance, compliance, and enterprise reliability — not the companies writing the most code or simply ‘vibe coding,’” he said.
Startups to watch:
AIstats
AIstats is a football analytics startup that uses AI, computer vision, and machine learning to analyse football matches from standard video footage. Its technology reconstructs games in 3D, tracks player and ball movement, and generates advanced tactical and performance insights without requiring stadium sensors or wearable devices.
The platform is designed to help clubs, scouts, and agents better understand player behaviour, team dynamics, decision-making, and tactical patterns through automated AI-driven analysis. The company also operates a consumer-facing football app that delivers live scores, predictive analytics, AI-generated match insights, and performance metrics across thousands of leagues worldwide.
Carein
Carein develops nutritional supplements designed to improve skin and hair health from the inside rather than relying only on topical skincare.
Founded in 2021, the company targets issues such as acne, hormonal acne, redness, pigmentation, ageing skin, and hormonal hair loss.
Its products combine vitamins, minerals, probiotics, plant extracts, adaptogens, and other active ingredients to support skin regeneration, hormonal balance, and the gut-skin connection. It works with medical experts to formulate its products and markets itself as a science-led premium skincare wellness brand.
DefendEye
DefendEye is a defencetech startup developing fully autonomous, AI-powered “search drones” designed for rapid intelligence, surveillance, and reconnaissance (ISR) missions.
Founded in 2023 and headquartered in Kraków, the company builds tube-launched drones that can deploy in under 10 seconds without requiring a pilot, joystick, or traditional drone training. Users simply launch the drone from a portable or fixed tube, and the onboard AI autonomously navigates, identifies humans, tracks movement, and streams encrypted live video back to a cloud command centre in real time.
The drones are built to operate even in GPS-denied or jammed environments and include low-light and night-vision capabilities for use in difficult battlefield or emergency conditions. The startup is positioning itself within the growing “drone as first responder” and autonomous defence systems market, where rapid situational awareness is becoming increasingly important for both military and civil security operations.
FormalFoundry.ai
FormalFoundry.ai is an AI governance and verification startup developing mathematically traceable AI systems and compliance tooling. It builds a verification layer for AI systems using formal methods and proof assistants, so companies can make AI outputs more reliable, auditable, and compliant.
This helps teams turn domain rules, regulations, and expert knowledge into machine-checkable logic to reduce hallucinations and errors.
Graphcode
Graftcode is a Polish software infrastructure startup tackling the large amount of time developers spend building and maintaining integrations between services, languages, and infrastructure layers.
According to Graftcode, engineering teams often lose 30–40 per cent of development time to API maintenance, DTO mapping, queues, versioning, and related backend complexity.
Its platform aims to remove that overhead by creating a unified communication layer between applications, enabling faster development, cleaner architectures, and easier scaling for distributed systems and AI-native software environments.
Instead of building separate services connected through traditional backend plumbing, developers can call methods across systems as if everything were in a single shared codebase.
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