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Market intelligence, buying guides, and AI trends for the people who choose technology.
Your AI agent is brilliant and amnesiac. It forgets you the moment the session ends, because large language models are stateless by design. Here is how memory actually gets bolted on, and where it goes wrong.
Everyone blames the model. The real reason most AI projects stall is boring: the data underneath them was never ready. Here is what AI-ready data actually means, and how to get there before you spend another rupee.
AI regulation stopped being theoretical in 2026. Here’s what the EU AI Act actually requires, who it hits, the fines, and the governance moves every founder and buyer should make now.
One agent hits a ceiling. The 2026 shift is to teams of specialized agents that plan, delegate, and check each other, here’s how orchestration works, when it pays off, and how to start.
Building your own AI feels like control and differentiation. Usually it's a six-figure distraction. Here's the framework for when to build, when to buy, and when to do both.
A new class of AI doesn't call an API, it looks at your screen and clicks, like a person. It can finally automate the apps that never had integrations. It can also go wrong in brand-new ways.
Half your buyers' research now happens inside an AI answer they may never click away from. If the model doesn't mention you, you don't exist. Here's how to get cited.
Nearly half your SaaS licenses are unused, prices climb every renewal, and most teams just click renew. The renewal is the one moment you hold the leverage, here's how to use it.
For 20 years you paid per seat. Now the vendor charges per conversation, per resolution, per outcome, and the AI doing the work doesn't need a login. Here's what your next renewal really looks like.
Most teams can tell you their AI feature's uptime. Almost none can tell you if it's right. Evals are the discipline that separates AI that compounds from AI that quietly embarrasses you.
A quantum computer that can break today’s encryption does not exist yet, and that is precisely why your data is at risk right now. "Harvest now, decrypt later" is the quiet cybersecurity threat every technology leader should be planning for in 2026.
The clever prompt was never the hard part. In 2026, the AI agents that work and the ones that embarrass you are separated by one thing: context engineering. Here is what it is, why it matters, and how to get it right.
