"I've spent most of my career fighting against the "short memory" of chatbots. This week, however, I finally saw the pieces of the puzzle fall into place: we are no longer talking about chat, but about persistent architectures."
I've spent a large part of my career fighting against the "short memory" of chatbots. You build a perfect flow, the user switches devices or asks a question off-script, and everything collapses. This week, however, I finally saw the puzzle pieces fall into place: we aren't talking about chat anymore, but about persistent architectures.
Here is what I noted in my logs this week and why it changes the way we build automations.
The news that made me jump out of my chair comes from Salesforce. I analyzed their new architecture for Agentforce and, finally, I see the end of forgetful bots. They introduced a "shared context" layer that solves the problem at the root: maintaining conversation state across different channels.
For those like me who design workflows, this is the missing piece. I can build an agent that "remembers" an abandoned cart on mobile and proposes it contextualized on desktop without having to write complex synchronization scripts. Agentic Commerce becomes an operational reality. It is no longer just a buzzword, but a technical specification that enables measurable ROI. If you are interested in understanding how these flows will change business, I dove deeper into the topic speaking about agentic AI.
We can have the best algorithms in the world, but if inference costs too much, they remain toys. Nvidia has just changed the math of my work with Vera Rubin. The data speaks of a 90% reduction in inference costs.
This means I can stop obsessively optimizing token counts to save pennies and focus on "reasoning". I can run complex chains of thought and multi-agent architectures without burning the client's budget in a week. Furthermore, the increase in compute density opens incredible doors for on-premise hardware, bringing us closer to that vision of AI on the edge that I have supported for some time for privacy and speed.
Another novelty that I marked with a double red circle is the launch of CTRL by Central. For years we have built precarious "scaffolding" around LLMs to force them to act. CTRL promises a native runtime for agents.
The difference is subtle but fundamental: we move from probabilistic generation (AI that "guesses" the next word) to deterministic action. To integrate AI into core business processes, I need certainty, not creativity. This runtime could become the standard for those who, like me, want to build systems that execute tasks without hallucinating.
I close with two practical applications that directly impact my daily productivity:
The direction is clear: less chat, more infrastructure. If you want to start building your flows, take a look at my complete list of AI tools and start experimenting with tools that allow orchestration, not just generation.
The classic conversational interface is a bottleneck for serious coding. The real revolution is not talking to a bot, but letting it act directly in the terminal.
This week, the market broke two critical barriers simultaneously: price and latency. AI is shifting from a "magic cost" to a high-efficiency engineering commodity.
This week automation closed the loop, moving from digital to physical via human APIs. It's no longer just about generating text, but total operational orchestration.
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AI Solutions Architect
As an AI Solutions Architect I design digital ecosystems and autonomous workflows. Almost 10 years in digital marketing, today I integrate AI into business processes: from Next.js and RAG systems to GEO strategies and dedicated training. I like to talk about AI and automation, but that's not all: I've also written a book, "Work Better with AI", a practical handbook with 12 chapters and over 200 ready-to-use prompts for those who want to use ChatGPT and AI without programming. My superpower? Looking at a manual process and already seeing the automated architecture that will replace it.