- Even works well on mobile.

- Embedding images and videos also works flawlessly.

Have you considered moving to open source / Chinese models?

If gemini-2.5-flash-lite is good enough for your application, you will find even lower cost options with better performance outside of the Google ecosystem.

So, technically, you can do deep traversals quicker. A few notes:

1. Few use cases truly need low-latency deep traversal on realtime data (>5 hops). There are some well known ones like fraud detection in payment processing and, possibly, social media recommendation engines. But I am not even sure how latest social media engines work, and whether they still rely on graph DBs.

2. However, in practice the advantage is often marginal. With modern analytical databases, or even an optimized PostgreSQL (ltree, materialized views, pgrouting, pg_duckdb, etc), you often get more than good enough performance. In addition those traditional SQL DBs scale with hardware more easily than graph databases. So, you can always use the lever: "Throw more hardware at it."

3. Even Graph DBs don't get good traversal performance under all conditions without hand tuning. For example, there is the "super node" issue, a node with an abnormally high number of connections (edges). And if you still need hand-tuning, you might as well choose something more versatile.

4. The ecosystem of a PostgreSQL and other popular DBs is just unbeaten. With graph DBs, you often prematurely put yourself in a corner that you don't want to be in.

Hence, my recommendation. Unless you are really sure that a graph DB is the right fit for your use case, start with something else, and go the graph db way when you have established a true need.

https://github.com/SharifIsmail/tendril

Feel free to give it a try. Agents can also directly interact with it.

It’s time for leaner structures, smaller teams, faster decisions, and shorter development cycles. Volkswagen, like no other company, symbolizes the lethargy of the German economy and business environment.

Hopefully, the seven years with barely any economic growth will end soon.

Is that true? My understanding is that the subagent only returns the result of the request without the main agent consuming its entire transcript.

That is the important part.

I see the same for slide decks. The bar has changed. Expectations are higher, but the high quality decks are still heavily edited, reviewed, and created by humans.

Having worked in regulated and very sensitive industries (banking and semiconductor), I can tell you adoption is slower but AI is still everywhere. Because those industries have many constraints, they have to think hard how to adopt it. So, you will encounter AI initiatives everywhere.

If you want to be part of those adoption initiatives but just want more thoughtful and slower adoption, such industries might be a good fit. If you want to avoid AI initiatives in general, I am not sure whether software engineering is the right function.

Or shall I also put the “onesmartphone” in the cupboard?

I agree that weather data should be public but I don’t see why we should restrict innovation in the private market if there is demand for it.

Also more generally, I see no issue in the government outsourcing work to a competitive private market wherever possible.

At that time, LLMs weren't as proficient in coding as they are today. Nowadays, the decorator approach might even go further and not just wrap LLM calls but also write Python code based on the description in the Docstring.

This would incentivize writing unambiguous DocStrings, and guarantee (if the LLMs don't hallucinate) consistency between code and documentation.

It would bring us closer to the world that Jensen Huang described, i.e., natural language becoming a programming language.

And one cannot simply substitute an optical lithography with a nano imprint machine without redesigning some part of the process (etch, metrology etc.).

Investing R&D resources for a (best case) 10% reduction in costs while still having a decent probability of failure in a big but declining node is not worth it.

Hence, buy $GOOG.