The Tech Blog

GPT-6(Astra) launched this week. It’s an insane step-up model. But one small part of the launch caught my attention more than the benchmarks. OpenAI showed Astra operating KiCad, taking a schematic, placing components and routing the PCB as well as a great intern would. We are on the cusp of massive takeoff.

I wrote about AI in electrical engineering almost two years ago, and my view has only become stronger. Over the next couple of years, I think conventional embedded product design will become heavily AI-assisted and to a great extent automated.

Give the system a product specification and it should be able to work backwards from it. What processor fits? Which sensors, regulators and interfaces make sense? What is in stock? Which alternatives reduce cost or supply-chain risk? It can read datasheets, compare trade-offs, build the architecture, create the schematic and eventually move into placement, routing and verification. Today’s models already help with several of these steps. I personally use them and it’s not too shabby.

After more than a decade working on embedded products, I know how much time goes into repetitive work: comparing parts, reading datasheets, creating symbols and footprints, checking reference circuits, updating BOMs and layouts. I think much of that will move to agents. Your value as an engineer shifts towards defining requirements, understanding trade-offs, spotting failure modes, validating the design and deciding what should actually be built.

I find that exciting. Most work will get displaced. The useful response is to learn these tools, change how you work and keep moving up the abstraction stack. Continuously upskill, or else you will be left behind.

My guess is that within 2-3 years, giving an AI a complete enough specification and getting most of a conventional embedded board back for engineering review will feel normal.

What do you folks think? Is 2–3 years too aggressive? Personally, I don’t think so. If anything, remember that the KiCad demo we are seeing today is likely the least capable version this technology will ever be.

Earlier this week, during a few discussions, I came across the concept of digital vaccines. I had never looked into it before, and the name sounded strange enough that I wanted to understand what was actually happening. It’s interesting enough to be worthy of a discussion today.

The project comes from CMU and FriendsLearn. Despite the name, this is not a biological vaccine. It is closer to a gamified digital therapeutic that tries to train healthier behaviour in children through repeated choices, rewards and implicit learning.

In one randomized trial, 104 children aged 10-11, played a game called Fooya. After two 20-minute sessions, they chose an average of 2.48 healthy food items versus 1.10 in the control group. A later 240-child school trial in Tamil Nadu tested nutrition, physical activity and hygiene. Early analysis found a 0.58-point improvement in infectious-disease prevention knowledge, with stronger effects in younger children.

AI alignment is interesting here. The game records how each child plays and what kinds of rewards influence their decisions. In principle, it can adapt the intervention to that child. Social-media algorithms already learn what keeps you hooked on their platforms. This explores a similar feedback loop with a different objective: reinforcing healthier decisions rather than maximizing watch time.

I do think the name “digital vaccine” is bit of a stretch. It is a clever marketing name, but today the strongest evidence is around learning and short-term behaviour change. Preventing diabetes, obesity or infectious disease is a much larger claim that still needs long-term clinical evidence. A current Type 1 diabetes trial is taking the next step by measuring HbA1c and CGM outcomes.

The bigger question is the engagement part. If children keep using an adaptive health game long enough for the learning to transfer into daily life, this could become a scalable form of preventive healthcare. If the novelty wears off quickly, it remains a good experiment in gamified education. Good that they are trying to put it to good use.