The value of human creativity in art and design.

Why the hell can't AI companies leave well enough alone. It seems a lot of companies were caught off guard by Anthropic's MCP and instead of acknowledging it's value and advancing it's adoption, they decided to muddy the waters by releasing yet more protocols... A2A, ACP, AG-UI. 

I believe #Agentic_AI for offline, automated multi-tasking represents the next stage of practical intelligence. The idea of an AI that can think, decide, and act without continuous internet access fascinates me. It could transform how we approach productivity, especially in areas with unstable connectivity. I see it as a bridge between autonomy and adaptability an AI capable of managing multiple tasks efficiently while learning from its surroundings to make context-aware decisions in real time.

How to keep your AI Agents reliable, even at global scale? As enterprises expand across channels, languages, and markets, one weak link in the AI ecosystem can disrupt thousands of customer interactions. The AI Ops Center gives teams the real-time control they need from instant oversight to proactive alerting and fast resolution. Reliability isn’t just a metric anymore, it’s your competitive edge. 👉 Find out more here https://bit.ly/43ba1Rr

We document because AI can generate code—but only humans can preserve intent, context, and nuance. Good documentation isn’t just technical—it’s a legacy of decisions, tradeoffs, and vision. ProductOwnership #DocumentationDriven

AI is doing what CRMs promised years ago — giving time back to actually sell. The ones who figure out how to blend tech with real connection are going to dominate.

AI slop comes from trading control for convenience, faster output, emptier results. Quality use of #ArtificialIntelligence isn’t about clicking “generate,” but creating structure (repeatable processes) around the outcomes you want to create. #AIWorkflows #ProcessDesign #AutomationStrategy #IntelligentSystems

We moment we stop talking about AI and switch to virtual agents, the moment tech and non-tech can begin to converse. It is always the application, not the engine that bridges understanding.

Sometimes I think we’ve misunderstood what AI is for. Everyone’s busy talking to it, but what if it was never meant to talk back? What if the power of these models isn’t conversation, but reasoning: the ability to structure decisions, compress context, and move information toward an outcome? That’s how we use it at Intience. Not as chatbots or tools, but as reasoning engines: embedded systems that simulate thinking for the toughest problems.

Creating a product with AI is awesome—but only if you give it the right specifications. The more details you provide, the closer the AI gets to building exactly what you envision. Otherwise, you might end up spending weeks debugging and fixing features that didn’t turn out as expected. That’s exactly what we’re doing here at Codetech—being as specific as possible in our product roadmap and every detail, so AI becomes a true accelerator, not a headache.

Hex’s journey building AI features is full of lessons. Don’t over-engineer around model flaws. Kill projects faster. Retry failed ideas when new models drop. The ground is shifting and the best teams are learning to pivot fast. #aiindustry #productteams #techlessons #modelcapabilities #aiproducts #productleadership #dataengineering #failfast #techstrategy #aiapplications #productthinking #startuplessons https://buff.ly/BjRfwBc