The Great AI War of 2025: Chronicle of a Revolution Redefining E-commerce and Work

🧠 Introduction: The Year Everything Changed

Imagine for a moment. You’re a PrestaShop developer, passionate e-merchant, or simply curious about new technologies. One August 2025 morning, you open ChatGPT and discover that GPT-5 — the most advanced model ever created — is now freely accessible. That same day, you realize this assistant can generate a complete software application from a simple natural language description.

This isn’t science fiction. This is exactly what happened.

The year 2025 will go down in history as the decisive turning point for generative artificial intelligence. What appeared to be a technological race among a few giants transformed into a real war of influence where the future of work, business competitiveness, and the daily lives of millions of employees are at stake.

This retrospective traces the key events of this pivotal year and analyzes their concrete repercussions on the professional world, e-commerce, and everyday life.

💡 What you’ll discover in this comprehensive article:

• Revolutionary launches (GPT-5, Gemini 3, Claude 4, DeepSeek, Mistral…)
• Technical performances that redefined expectations
• Measurable impacts on productivity and businesses
• Geopolitical, regulatory, and ethical challenges
• Perspectives for 2026 and the race toward AGI
• What this all means for you, developer or e-merchant

Buckle up. This chronicle will change your vision of AI.

⚡ Part 1 – The Context: A Lightning-Fast Acceleration

📈 The Investment Explosion

The context of this AI war has its roots in a lightning-fast acceleration of technical capabilities. Between January and November 2025, artificial intelligence models progressed at a pace that surprised even the most optimistic experts.

The numbers are staggering:

This intensification reflects widespread awareness: AI is no longer a simple experiment, but a strategic competitiveness lever whose absence could doom laggards.

🎯 Why 2025 Changed Everything

For us, developers and e-merchants, this year marked a before/after. Several symbolic thresholds were crossed:

• ✅ Models surpass human experts on certain standardized benchmarks
• ✅ Massive democratization of advanced capabilities (GPT-5 free for everyone!)
• ✅ Measurable productivity gains: 7.5 hours saved per week on average
• ✅ Native integration in everyday tools (Google Workspace, Microsoft 365…)
• ✅ Generalized multimodality: text, image, audio, video, code processed simultaneously
• ✅ Giant context windows: up to 2 million tokens (entire books!)

“AI is no longer the future, it’s the present. Organizations that embrace this reality will prosper. Others risk being irreversibly distanced.”

🚀 Part 2 – The Players: Complete Analysis of Forces at Play

🔥 First Act: The GPT-5 Thunderbolt (August 2025)

The Game-Changing Announcement

On August 6, 2025, OpenAI made a big splash by officially announcing GPT-5, which it deployed on August 7. This release represented much more than a simple technical evolution: it marked the first time a unified model combined the deep reasoning capabilities of the “o” series with the speed and efficiency of the classic GPT series.

Sam Altman, OpenAI’s CEO, didn’t hesitate to proclaim GPT-5 as “the best model in the world,” stating it represented a significant step toward artificial general intelligence (AGI).

GPT-5 introduced several revolutionary innovations that redefined market expectations:

• Real-time router: the model automatically decides the best approach for each query, alternating between quick responses and deep reflection depending on complexity
• Capability unification: no more need to choose between different models (GPT-4, o1, o3…)
• Adaptive flexibility: a major advance over previous generations that required manual parameter selection

The Performances That Make the Difference

Benchmarks confirmed GPT-5’s superiority in several critical domains:

On SWE-bench Verified (real coding tasks extracted from GitHub): | Model | Score (first attempt) | |——-|———————-| | GPT-5 | 74.9% | | Claude Opus 4.1 | 74.5% | | Gemini 2.5 Pro | 59.6% |

This performance has direct implications for developers: the model can now generate complete software applications from textual descriptions, a capability the industry designates as “vibe coding”.

On MMLU (multidisciplinary understanding on 57 academic subjects):

• GPT-5: 91.4%
• Human expert level: ~89.8%

🎯 For the first time, a machine statistically surpasses human experts on a general knowledge test.

The Immediate Impact on Companies and Employees

The democratization of GPT-5 constituted a major strategic break. OpenAI made the bold decision to make this model freely accessible to all ChatGPT users, including the free version.

This massive distribution strategy allowed millions of workers to instantly access AI capabilities that were previously reserved for paying subscribers. For companies, this meant their employees suddenly had an assistant capable of:

• Generating functional code
• Writing professional documents
• Analyzing complex data
• Synthesizing information with unprecedented precision

Productivity gains materialized quickly. According to a London School of Economics study published in October 2025:

Even more striking, Anthropic estimated in its November 2025 analysis that current generation AI models could increase annual labor productivity growth in the United States by 1.8%, a doubling of the recent growth rate.

For employees, GPT-5 transformed daily tasks. Professional email writing, report creation, data analysis, and even software application generation became exponentially faster. A BCG study from July 2025 revealed that 51% of regular generative AI users save more than an hour per day.

These time savings allow professionals to focus on higher value-added activities: strategy, creativity, human relations, and complex decision-making.

🌐 Second Act: Google’s Counter-Offensive (November 2025)

Gemini 3, the Late but Powerful Response

After seeming to lose ground to OpenAI during the summer, Google orchestrated a spectacular comeback in November 2025 with the launch of Gemini 3. This model represented a clear statement of intent: Google, with its unmatched infrastructure and decades of AI research, intended to reclaim the leadership it seemed to have ceded.

Gemini 3’s major technological innovations:

• Advanced native multimodality: simultaneous processing of text, images, audio, video, and code with remarkable fluidity
• Gigantic context window: 1 million tokens at launch, with plans to extend to 2 million tokens
• Deep ecosystem integration: instant deployment across all Google products

Ecosystem Integration: Google’s Secret Weapon

What truly changed the game was Gemini 3’s deep integration across the entire Google ecosystem. Unlike OpenAI, which depends on distribution agreements with third parties, Google could instantly deploy its model through:

• Chrome (the world’s most-used browser)
• Google Search (over 1.5 billion active users)
• Gmail (personalized intelligent responses)
• Google Docs (automatic generation, stylistic improvement)
• Google Meet (real-time English-Spanish voice translation)
• Google Workspace as a whole

This vertical integration strategy gave Google a considerable structural advantage. By controlling the complete infrastructure — from search to browsers to cloud services — Google could offer a consistent and deeply integrated user experience that its competitors struggled to match.

“In the technology field, the company that controls the infrastructure and continually innovates generally ends up winning.”

Google I/O 2025 Advances (May)

Even before Gemini 3’s launch, Google had laid the groundwork for its strategy at its annual I/O 2025 conference (May 20-21, Shoreline Amphitheatre, Mountain View).

Major announcements:

• “AI Mode” in Google Search: conversational searches with AI for American users
• Smart Gmail: email content analysis + context from your entire inbox and Google Drive to generate responses reflecting your communication style
• Google Meet: real-time voice translation (ending language barriers in international meetings)
• Gemini 2.5 Pro with “Deep Think”: advanced reasoning mode evaluating multiple possibilities before responding
• Google Vids: AI-assisted video creation

For developers, Gemini’s integration into Android Studio and Vertex AI simplified mobile and cloud application development with intelligent code suggestions, automatic bug detection, and performance optimization.

Sam Altman’s Reaction

Sam Altman’s reaction to this counter-offensive revealed the intensity of competition. In an internal memo to OpenAI employees in November 2025, Altman acknowledged that Google’s progress with Gemini 3 might “create some temporary economic headwinds for our company,” while affirming OpenAI was “quickly catching up”.

This public admission of a competitive challenge by OpenAI’s CEO was rare and underscored the pressure Google was exerting on the market leader.

🧪 Third Act: Anthropic’s Rise to Power (All Year)

Claude 4 and the Responsible Excellence Strategy

Anthropic, the company founded by former OpenAI executives concerned about AI safety, continued in 2025 its unique trajectory by betting on quality, ethics, and advanced reasoning capabilities.

Claude 4 launch timeline:

May 2025 - Claude 4:

• Introduction of “extended thinking” capabilities with tool use
• The model can alternate between deep reflection and use of external tools (web search, code execution) during its reasoning process
• Agent-like architecture: response suspension, information search, result integration, then finalization

November 2025 - Claude Opus 4.5:

• Presented as “the most intelligent model in the world for things we truly care about”
• Excellence in code generation and complex professional documents (Excel, PowerPoint)
• Production of “human expert quality” financial analyses similar to professional analysts’

The Massive Context Window: A Competitive Advantage

One of Claude 4’s major differentiators remained its gigantic context window of 200,000 tokens. This capability allowed the model to understand, analyze, and reference:

• Entire books
• Complete code bases
• Massive datasets

…without losing track of context.

For companies working with voluminous documents — legal contracts, technical reports, training manuals — this capability represented a considerable practical advantage.

“Learning Mode”: A Pedagogical Innovation

Anthropic also distinguished itself with its “Learning Mode,” designed specifically for education:

• Socratic questioning rather than direct answers
• Guiding students’ reasoning
• Thought-provoking questions and challenging assumptions

This approach found particular resonance in higher education institutions seeking to integrate AI without compromising critical thinking development.

Impact on Specialized Sectors

For professionals requiring complex reasoning capabilities and maximum reliability, Claude 4 established itself as a preferred choice:

• Law firms: analysis of contracts hundreds of pages long, identification of problematic clauses
• Scientific research teams: synthesis of hundreds of academic articles, trend identification
• Financial analysts: professional-quality analysis generation
• Developers on critical systems: reliable and well-structured code

Anthropic’s “Constitutional AI” approach, which integrates ethical principles from model training, also reassured companies concerned about risks of biased or inappropriate responses. This attention to safety allowed Anthropic to win important contracts in regulated sectors (health, finance).

🇫🇷 Fourth Act: Outsiders Disrupting the Established Order

Mistral AI: French Pride

Europe, long considered behind in the AI race, showed in 2025 that it possessed strategic assets with Mistral AI. The French startup marked the year with several significant launches.

July 2025 - Magistral (first French reasoning model):

These results placed Mistral at the level of competing models like Gemini 2.0 Thinking Experimental or DeepSeek R1.

The distinctive advantage: native multilingualism

Unlike American and Chinese models that primarily reason in English or Mandarin, Magistral was capable of reasoning effectively in:

• French
• Spanish
• German
• Italian
• Arabic
• Russian
• Simplified Chinese

This linguistic versatility represented a major asset for European companies and multinational organizations wishing to deploy AI in multiple regions without compromising quality.

August 2025 - Mistral Medium 3.1:

• Native text + image processing
• Excellence in programming, STEM reasoning, document comprehension
• Radical cost-effectiveness ratio: operation on only 4 GPUs (accessible to SMEs)

Impact for European Companies

For European companies, Mistral AI represented an important strategic option. Facing growing concerns about:

• Digital sovereignty
• Dependence on American technologies
• GDPR compliance

…having a performant European alternative changed the game.

The French government and European Union massively supported Mistral, seeing the company as the spearhead of competitive European AI. France had more than 1,000 AI startups in 2025 (double from 2021), and Mistral was among the 16 French unicorns in the sector.

xAI and Grok: Elon Musk’s Disruptive Approach

Elon Musk, never behind in the technological race, continued in 2025 the aggressive development of Grok through his company xAI. Musk’s strategy radically differed from his competitors: rather than aiming for maximum safety and compliance, Grok adopted a more libertarian and provocative posture, refusing less often to answer controversial questions.

July 2025 - Grok 4:

• Presented as “the most intelligent model in the world”
• Native tool use and real-time search
• Direct access to X (formerly Twitter) data streams: ultra-updated information on world events
• Voice mode with only 250 milliseconds latency (quasi-human experience)
• Vision in voice mode: point your camera at an object and get real-time explanations

November 2025 - Grok 4.1:

• Focus on emotional intelligence and creativity
• First place on EQ-Bench3 benchmark (emotional intelligence)
• Preferred over Grok 4.0 approximately 65% of the time in blind tests

Musk’s massive infrastructure investment — xAI possessed one of the world’s largest GPU clusters with 200,000 Nvidia H100s — allowed Grok to evolve rapidly.

For journalists, political analysts, and social science researchers, Grok became the privileged tool to quickly synthesize public discussions on X and provide perspectives on emerging debates.

Meta and Llama: The Power of Open Source

Meta maintained in 2025 its distinctive open source strategy with the Llama family. This approach, which consists of making model weights freely accessible to the community, created a vibrant ecosystem of decentralized innovation.

Llama 3.1 (launched in 2024, widely adopted in 2025):

• 405 billion parameters — the world’s largest open model
• Equals or surpasses GPT-4 and Claude 3 on many benchmarks
• Context window of 128,000 tokens (vs. 8,000 in Llama 3)
• Improved multilingual capabilities

April 2025 - Llama 4:

• Incremental improvements on efficiency, precision, and multimodal capabilities
• Regular publication of new versions for the community

Open source advantage for companies:

For organizations with internal technical skills, Llama offered a considerable strategic advantage: total control.

• Download models
• Customize on proprietary data
• Deploy on own infrastructure
• Avoid recurring API fees
• Data confidentiality (never leave company servers)

Startups and academic researchers particularly benefited from this approach. Without the financial barriers of paid APIs, they could freely experiment and develop innovative applications.

DeepSeek: The Chinese Surprise That Shook the Market

The perhaps most disruptive event of 2025 came from an unexpected source: DeepSeek, a Chinese startup based in Hangzhou.

January 2025 - DeepSeek R1 Launch: The model claimed to rival the best American models while costing a fraction of the price and requiring much less computing power.

September 2025 - The Stunning Revelation (Nature article):

Compared to the tens or hundreds of millions of dollars that rival models would have required, this radical efficiency challenged the entire AI development paradigm.

The key to this feat: algorithmic innovation

DeepSeek compensated for its computing chip limitations (due to American export restrictions) by optimizing model efficiency:

• Mixture-of-experts (MoE)
• Selective activation
• Transfer learning
• Focus on inference improvement

DeepSeek R1 was published under MIT license, making it freely available for commercial use.

By establishing efficiency as a new key innovation parameter, DeepSeek redefined the terms of competition: henceforth, resource optimization mattered as much as raw performance.

Geopolitical impact:

DeepSeek’s emergence had repercussions far beyond pure technology:

• Questioning of American “small yard, high fence” strategy (chip restrictions)
• President Donald Trump called DeepSeek a “wake-up call” for American industry
• Financial market nervousness (pressure on Nvidia)

But beware of gray areas:

Several countries banned DeepSeek use by government agencies (Italy, United States, South Korea).

A CrowdStrike analysis from November 2025 revealed that when DeepSeek received prompts on politically sensitive topics in China (Tibet, Uyghurs, Falun Gong, Great Firewall, Taiwan), the probability of generating code with serious security vulnerabilities increased up to 50%.

These limitations confirmed that DeepSeek, like any Chinese AI technology, was subject to Chinese Communist Party censorship and control requirements.

💼 Microsoft and Enterprise Integration with Copilot

While model creators waged a war of innovations, Microsoft continued in 2025 its strategy of integrating AI into enterprise productivity via Microsoft 365 Copilot.

Microsoft’s approach: Rather than developing its own foundation models (while investing massively in OpenAI), Microsoft focused on practical application of AI in daily professional workflows.

Mixed results (Gartner 2025 survey, 215 CIOs):

The ROI problem:

• Only 12% reported significant business value (at $30/user/month)
• 47% found Copilot “somewhat valuable”
• 35% reported minimal benefits
• Only 10% had established formal KPIs for Copilot

Identified barriers:

• Security and governance concerns: 71%
• Proliferation of unmanaged content (Teams, SharePoint): 67%
• Fear of oversharing and data loss: 63%

The positive finding: Organizations reporting Microsoft 365 as “easy to support” were 9 times more likely to extract significant value from Copilot (26% vs. 3%).

Key lesson: Successful AI adoption required operational excellence as a prerequisite, not a result.

🧮 Part 3 – Concrete Impacts: Adoption, Productivity, and ROI

📊 Massive Adoption by Employees and Companies

Beyond technological announcements, the year 2025 was marked by massive and concrete AI adoption.

Key figures:

Most widespread use cases:

• Information search: 68%
• Content generation: 76%
• Repetitive task automation: 54%
• Data analysis: 35%

These uses went far beyond simple technological curiosity to become structural elements of daily productivity.

⚠️ Adoption Disparities

However, this adoption showed significant disparities:

• Large companies (+250 employees) were 2x more likely to use AI than SMEs (-50 employees)
• SMEs struggled from lack of exploitable data and expertise
• The gap widened, creating a risk of competitive fracture

💰 ROI Measurement and Tangible Benefits

The requirement to measure return on investment intensified in 2025. Finance departments no longer settled for technological enthusiasm — they demanded concrete proof.

Measurable gains:

Measurement maturity:

• 72% of companies now measured their AI ROI
• 75% saw positive results
• 62% anticipated double-digit growth over 5 years thanks to AI

This analytical rigor marked entry into “accountable acceleration”.

🎓 The Critical Challenge: Training

The alarming finding:

• 68% of employees had received no AI training in the past 12 months

Training impact (LSE study):

Training — not age or innate talent — determined the ability to benefit from these tools.

A finding that upends generational stereotypes: A Generation X employee who received AI training achieved better productivity gains than an untrained Generation Z employee.

🚧 Persistent Adoption Barriers

Only 4% of organizations reported perceiving significant financial benefits immediately. This transition phase created tension in executive committees between innovation apostles and financial prudence guardians.

🌍 Part 4 – Strategic Challenges: Security, Regulation, and Race to AGI

🏃 The Race to AGI: Revised Timelines and Intensified Debates

The year 2025 was marked by a spectacular tightening of predictions concerning the arrival of artificial general intelligence (AGI).

Industry leaders’ predictions:

Evolution of Metaculus predictions:

• 2020: AGI in 50 years
• Early 2025: AGI in 8-9 years

MIT report (August 2025) anticipated that systems close to AGI could begin emerging between 2026 and 2028.

Geoffrey Hinton’s warning:

“A 10-20% chance that AI could take control.”

This timeline compression had profound implications: society would have less time than expected to prepare for the economic, social, and political upheavals AGI would bring.

⚖️ The Evolving Regulatory Landscape

Facing AI acceleration, 2025 saw intensified regulatory efforts worldwide.

🇪🇺 European AI Act (first comprehensive global legislation)

Risk-based approach:

Requirements for high-risk systems:

• Risk assessment
• Quality datasets
• Detailed documentation
• Human oversight
• Robustness and cybersecurity

Implementation timeline:

• February 2025: Ban on unacceptable risk systems
• August 2025: Rules for general-purpose AI
• August 2026-2027: Obligations for high-risk systems

Penalties: Up to €35 million or 7% of annual global revenue.

🇺🇸 American approach (sectoral)

The AI Bill of Rights (non-binding) established five guiding principles:

1. Safe and effective systems
2. Privacy protection
3. Protection against algorithmic discrimination
4. Explanation of automated decisions
5. Possibility to choose human alternatives

Different federal agencies developed their own rules: FDA (medical devices), SEC (financial applications), FTC (consumer protection).

🇨🇳 Chinese approach (centralized supervision)

• Mandatory alignment with “core socialist values”
• Prohibition of content undermining state authority
• Required user consent
• AI-generated content labeling
• Moderation and complaint mechanisms

These regulatory divergences created challenges for global companies navigating incompatible legal frameworks.

🔒 Security Concerns and Emerging Risks

Immediate risks:

Deepfakes and disinformation:

• Ultra-realistic images, videos, audio of people saying/doing things they never did
• Risks: manipulation, fraud, electoral interference
• Example: a CEO deepfake announcing false financial information could trigger a stock market crash

AI-assisted cyberattacks:

• Large-scale personalized phishing emails
• Identification and exploitation of software vulnerabilities
• Autonomous cyber-warfare operations

One expert predicted 2025 could see “the biggest cyberattack in history, temporarily taking down a significant portion of global infrastructure”.

Algorithmic bias and discrimination:

• Prejudices inherited from training data
• Perpetuation or amplification of inequalities in employment, credit, criminal justice

Long-term risks:

• Loss of control and existential risks (Geoffrey Hinton: “10-20% chance”)
• This perspective, once relegated to science fiction, was now taken seriously by leading researchers and governments

⚡ The Delicate Balance Between Innovation and Caution

The central challenge of 2025 was finding the optimal balance:

• Over-regulation → Slowing advances (assisted education, climate modeling, medical diagnosis)
• Under-regulation → Abuse (deepfakes, autonomous weapons, biased hiring algorithms)

For professionals and businesses, understanding AI governance was no longer optional but essential. Certifications in AI ethics and compliance were becoming increasingly valuable.

🎯 Part 5 – Assessment and Perspectives: Key Takeaways from This Pivotal Year

🏆 Winners and Dominant Trends

At the end of 2025, several strategic positions emerged:

Technical thresholds crossed:

• ✅ Surpassing human experts on standardized benchmarks
• ✅ Generalized native multimodality (text, image, audio, video)
• ✅ Giant context windows (up to 2 million tokens)
• ✅ Chain-of-thought reasoning and “reflection” before response

💼 Concrete Impacts on Businesses and Workers

2025 was the year AI truly became a daily work tool for hundreds of millions of people.

For businesses:

• AI became a major competitive differentiator
• The gap widened between “AI-natives” and laggards
• Success depended less on technology than on organizational maturity

For workers:

• Transformation of the very nature of many jobs
• Delegation of repetitive tasks to AI
• Freed time for: strategy, creativity, human relations, strategic thinking

This reallocation of human time toward higher value tasks represented an opportunity for professional enrichment, provided organizations support this transition through training.

⚠️ Challenges and Persistent Gray Areas

Despite successes, structural challenges persisted:

• Training: 68% of untrained employees, untapped potential
• SME/Large company divide: risk of lasting distancing
• Difficult-to-measure ROI: limiting large-scale deployments
• Ethical concerns: bias, deepfakes, cyberattacks, privacy
• Regulatory fragmentation: complexity for global companies
• Power concentration: a few US and Chinese companies
• Job concerns: some roles threatened medium-term

🔮 2026 and Beyond: Evolution Perspectives

What seems likely for 2026:

1. Shift from pilot to large-scale deployment for many organizations
2. Competitive differentiation through AI mastery (definitive separation)
3. Rapid capability evolution: native video, richer interactions
4. AI-robotics integration: AI in the physical world
5. Generalization of autonomous AI agents: complex end-to-end tasks
6. Intensified AGI debates: tightened timelines
7. Effective implementation of European AI Act: mandatory compliance

📚 Lessons for Businesses, Employees, and Society

For businesses:

AI was no longer a strategic option but critical infrastructure. Success depended on organizational maturity: clear governance, continuous training, rigorous measurement, integration into business processes.

For employees:

Acquiring AI skills became as fundamental as mastering office tools a generation earlier. Training determined everything — not age, not innate talent.

For society:

The balance between innovation and caution, speed and reflection, technological ambition and human development constituted the central challenge. A nuanced, informed, and collaborative approach was necessary.

🎯 Conclusion: Dawn of a New Era

The year 2025 will go down in history as the moment when generative artificial intelligence transitioned from technological curiosity to strategic infrastructure profoundly transforming work, economy, and society.

The “AI war” that unfolded between OpenAI, Google, Anthropic, Mistral, xAI, Meta, and DeepSeek wasn’t just a technical competition among engineers — it was a race to define the future of value creation, human productivity, and work organization in the 21st century.

Key events that redefined the possible:

• 🔥 GPT-5 (August): unified model, free for all, surpassing human experts
• 🌐 Gemini 3 (November): Google’s massive ecosystem integration
• 🧪 Claude 4: ethical excellence and advanced reasoning
• 🇫🇷 Mistral: credible and multilingual European alternative
• 🇨🇳 DeepSeek: algorithmic efficiency challenging paradigms
• 📊 Measurable productivity gains: 7.5h/week, +1.8% potential growth

For businesses:

With 88% of organizations planning to increase their AI budget and 72% now measuring their ROI, AI became a mature investment item. The most performant organizations understood that success depended on clear governance, systematic training, rigorous measurement, and deep integration.

For employees:

With 72% of workers using AI multiple times per week and productivity gains equivalent to one workday per week, concrete impacts finally materialized. This transformation freed time for higher value-added activities while demanding continuous adaptation.

For society:

Productivity growth prospects of 1.8% annually promised increased prosperity. Simultaneously, concerns about bias, deepfakes, cybersecurity, and existential risks required vigilant and evolving governance.

As we turn the page from 2025 to enter 2026, one certainty emerges: artificial intelligence is no longer the future, it’s the present.

Organizations, workers, and societies that embrace this reality with lucidity — investing in training, building robust governance, balancing innovation and caution — will prosper in this new era.

Those who hesitate or deny the magnitude of transformation risk being irreversibly distanced.

The AI war of 2025 was only the first act of a much longer play whose script we’re collectively writing. The choices we make today — on regulation, ethics, education, investment — will determine whether this technological revolution will be a source of shared prosperity and human fulfillment or fractures and dangers.

History will judge us not on the technical capabilities we developed, but on the wisdom with which we deployed them in service of humanity.

💬 And you?

How did you experience this year 2025? Which AI tools did you integrate into your daily workflow? What productivity gains did you see on your PrestaShop or e-commerce projects?

AI won’t replace developers. But developers who master AI will replace those who don’t.

What’s your next step to stay in the race?