Insights
Frameworks, analysis, and field notes from a team that has built at Carousell, Goldman Sachs, and Bain.
If your Q4 AI budget review starts with 'how much did we spend on AI,' you are already having the wrong conversation.
Prompt engineering is not a technical skill. It is the new product specification language, and PMs who ignore it are already behind.
Enterprises budget for GPUs and API calls while ignoring the actual expense: rewiring how their people work.
The pilot-to-production gap is where most enterprise AI initiatives go to die. The reasons are structural, not technical.
The team structure that worked for traditional software products will actively hinder your AI product development.
Companies treating the EU AI Act as a compliance checkbox are going to ship slower and spend more. It is a product design constraint.
Most enterprises get the build-versus-buy decision wrong on LLMs because they evaluate it like traditional software procurement.
Earnings calls are the best lie detector for AI strategy. Q3 2025 separates the shippers from the slideware.
Traditional strategy firms are losing enterprise AI mandates to specialized players who actually understand the technology stack.
GITEX is no longer just a trade show. It is where the GCC's AI strategy becomes tangible, and the rest of the world should pay attention.
Your AI roadmap is probably organized around model capabilities instead of user problems. That is the most common way to build irrelevant products.
Prompt engineering as a standalone discipline has peaked. The skills that matter now are systems-level: evaluation, orchestration, and reliability.
Dubai, Abu Dhabi, Riyadh, and Doha are competing for AI talent and investment. The race is creating opportunities that most global firms are underestimating.
AI does not fit neatly into existing engineering team structures. The companies adapting their org design are outpacing those that are not.
VCs know wrappers are fragile. They fund them anyway because speed beats defensibility in the short term. That calculus has an expiration date.
When the CIO owns AI infrastructure and the CTO owns AI products, the result is organizational dysfunction disguised as a reporting structure.
GITEX is weeks away. Here is how to separate the signal from the spectacle at the world's largest tech event in the Gulf.
RAG is the most deployed AI pattern in the enterprise. It is also the most poorly implemented. The gap between demo and production is vast.
The AI talent market is splitting into two distinct pools with very different dynamics. Hiring strategies that ignore this split will fail.
Q3 numbers reveal a growing split: companies doubling down on what works and quietly killing what does not.
When AI can see, hear, and read simultaneously, the definition of what a software product can do expands dramatically.
Analyst reports focus on model providers. The real enterprise AI market is in the unsexy middle layer where integration and orchestration live.
Buying an AI agent platform is not like buying SaaS. The integration, customization, and control requirements change the calculus entirely.
September planning season is here. Before you add AI to every initiative on the roadmap, ask whether it belongs there at all.
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