until some of the significant flaws of agents are addressed (hallucination, explainability, bias), I'm not really all that interested in extending this model further.
Agentic AI definitely works for software engineering because we have suitable mitigations for its limitations. It is unclear what those mitigations might be in other fields of application.
There are so many prompting guides at the moment. Personally I think they are quite unnecessary. If you take the time to use these tools, build familiarity with them and the way they work, the prompt you should use becomes quite obvious.
It reminds me that we had the same hype and FOMO when Google became popular. Books were being written on the subject and you had to buy those or you would become a caveman in a near future. What happened is that anyone could learn the whole thing in a day and that was it, no need to debate about whether you would miss anything if you didn't knew all those tools.
You’re only proving the opposite: there’s definitely a difference between “experienced Google user” and someone who just puts random words and expects to find what they need.
I think there are people for whom reading a prompt guide (or watching an experienced user) will be very valuable.
Many people just won't put any conscious thought into trying to get better on their own, though some of them will read or watch one thing on the topic. I will readily admit to picking up several useful tips from watching other people use these tools and from discussing them with peers. That's improvement that I don't think I achieve by solely using the tools on my own.
Many years ago there were guides on how to write user stories: “As a [role], I want to be able to do [task] so I can achieve [objective]”, because it was useful to teach high-level thinkers how to communicate requirements with less ambiguity.
It may seem simple, but in my experience even brilliant developers can miss or misinterpret unstructured requirements, through no fault of their own.
It's at least useful for seeing how other people are being productive with these tools. I also sometimes find a clever idea that improves that I'm already doing.
And documenting the current state of this space as well. It's easy to have tried doing something a year ago and think they're still bad.
I also usually prefer researching some area before reinventing the wheel by trial/failure myself. I appreciate when people share what they've discovered with their own their time, as I don't always have all the time in the world to explore it as I would if I were still a teen.
Thanks for sharing pmabanugo, a couple of those posts are new to me too. If you’re taking submissions, I’ve been exploring how to make the most of these tools for the past few months, here’s my latest post:
Great post, thanks for sharing. I wrote something similar a couple of years ago, showing just how simple it is to work with LLMs directly rather than through LangChain, adding tool use etc …
Thanks for sharing this. The field moves so yes, it's out of date, but it's useful to see how the tools concept evolved. Especially since I wasn't paying attention at that area of development back when you wrote your article. Very interesting.
Agreed, embeddings are a very useful tool. Started using them for article recommendations on our blog a few years ago, with a measured increase in engagement:
I’m working on a simple app that logs Karting activity and data. My son has been karting for a year or so, and there is so much data to collect - times, pressures, sprocket set up, track location, weather and more (about 30 datapoints a session)
Collecting the data helps with recording engine performance, tyre ages, best lap times but is also really useful for recalling how well each setup performed for future reference.
I’m deliberately doing this all in a very low-tech way as my son will be creating a more polished version for a school project. We’re front-running that a bit to give him a good dataset and explore various ideas.
On that note, they do Python in school. For the backend it will be SqlLite and Flask. Any suggestions for the front end tech? This will mostly be forms- and grids-based so nothing sophisticated needed, but some simple client-side logic (e.g. validation, geolocation, simple stop watch) would be good. Ideally this would be python as well. We could use WebAssembly but am wondering if there is a suitable framework that does the is out-of-the-box.
