(DISCUSSION) The Future Economy of AI

TL;DR:
AI is splitting into front-ends, LLMs, and data/tools. True winners will focus on one layer—interface, model, data, ads, security, or memory. “Agentic” “bridge” systems are just a temporary hack.

I wanted to spark a discussion about where the AI economy is heading. Here’s my take:

1. Decoupling Layers:

- **Interface Layer:** Chatbots, voice UIs, and visual prompts—think plug-and-play front-ends. - **Core LLM Layer:** The reasoning and generation engines (GPT, LLaMA, etc.). - **Data/Tool Layer (MCP/OpenAPI):** Standardised access to news feeds, stats, search, and specialised tools. 

1. Value Streams to Watch:

- **AI first Ressources:** High value standardised and AI first data sets (e.g. token optimised and well maintained legal documents, https://github.com/marv1nnnnn/llm-min.txt). - **AI Data:** Specialised high value and strongly reliable data sources to enable the hallucination reduced usage. Includes Search for data (e.g. Statista) or physical places (e.g. Google Places) and provides the necessary reliabillity of the AI first usage. - **AI-Native Tooling:** A new Tool stack which allows for a seamless handover between AI and Human. The current tool stack with Microsoft / Google is technically to complex to provide a good way to have AI first workflows. This includes things like On-demand video generation, AI-driven docs, ai-slide deck software, Excel... - **Monetization:** Contextual (semantic) ads and content recommendations to fund free tiers. Basically new generation of Adsense / Adwords. Probably the next holy grail and the way to get absurdly rich. - **UI/UX Giants:** Browser-like shells for AI that swap back-ends without a hitch and consistently inovative on the interaction layer.Probably the nicest area and will provide the backbone to the actual AI-first company generation. - **AI Security:** While previously security was primarily aginst external bad actors we are no having the risks of AI deciding to make major harm through tools without any bad intention. This will need to be considerd and will provide a significant effort and invest in the AI first companies of the future. Furthermore, the cyberattacks will ramp up to a new level. - **Memory & Context:** Personalised memory systems and individualized context will be a broad topic both in B2B and B2C and are one of the unsolved issues so far. While we can store the data the actual relevancy evaluation and context prioritisation needs to be figured out. First approaches like Mem0 are a starting point but htis will be an area with the heighest lock-in. 

1. Why “Agentic” Systems Are a Red Flag:

   Agentic/”multi-agent” frameworks that glue together static prompts, LLM, and tools are just a stopgap. They add complexity and vendor lock‑in, and they’ll vanish once true modular decoupling matures while the individualised prompting need is removed by LLM training optimisation.

2. Open Questions for the Community:

- Do you agree or disagree with me? What is your stand on the future of Agents? - Which specialised layer are you betting on? Interface or data? Model or memory? - What standards besides MCP could push true interoperability? 

Let’s discuss! Upvote if you agree that modular AI is the future, or roast my assumptions 😄