Exactly a decade ago, on 19th January 2014, I published my first post on this website (Kaggle beginner tips). In most of the following years, my tagline was Data Science and Beyond. While the beyond bit gave me an excuse to write about various topics, most posts were indeed around data science – an area that also became broader (arguably to the point of uselessness).
While I’ve never abandoned my software engineering roots, the broadening of data science means that many data scientists can no longer be assumed to possess solid engineering skills. Therefore, I changed the tagline last year to Engineering Data Science & More. However, this didn’t feel quite right – some people now have an adverse reaction to any mention of data science, after negative experiences of failed projects.
Recently, I switched the tagline to be both broader and narrower: Data & AI for Nature. However, upon reflection and given some feedback, I realised that the Nature bit may be off-putting to some people who do impactful work in the space but have different motivations. Therefore, I decided to go with Data & AI for Impact (for now…).
More importantly, I’m planning to revitalise my approach to publishing and audience engagement:
- Post more frequently – aiming for weekly from February onwards.
- Use the mailing list to email full posts, and as a two-way avenue for comments and conversations (as opposed to public comments, which are now closed).
- Still publish both technical and high-level posts on Data & AI.
- Produce content that’s specifically useful for startups and scaleups that are early on their Data & AI journey.
- Showcase positive-impact applications of Data & AI tech – especially by startups in the climate and nature-positive space.
With more frequent posts, what I publish should be quicker to produce and consume. This means I may lean more heavily on showcasing other people’s work – possibly through interviews. Other than that, here are some rough post ideas for the immediate future:
- Series on a minimum viable data stack
- Best practices and opinions on a startup’s first data hire
- Answering questions people ask on the future of data science
- My experience as a Data Tech Lead with Work on Climate
- Use cases for ChatGPT and other LLMs
- Catching up on different aspects of LLMs / AI tech
- Opportunities for Data & AI professionals in the energy transition
Historically, for each post I’ve published, about 5-10 ideas went unpublished. I hope that by aiming for shorter and lower-friction publishing, more posts will see the light of day.
My long-term aims are to learn by publishing, apply my Data & AI skills towards more positive impact, and help others in the space. Rather than sinking into doom and gloom, I’d like to focus on positive applications of Data & AI tech that make our world better (in the spirit of publications like Volts).
Call to action:
- If this all sounds uninteresting to you, you’re welcome to unsubscribe – no hard feelings.
- If you know people I should talk to and feature in future posts, I’d appreciate an intro.
- If you have any suggestions, please send them by replying to any of my emails, or contact me through other means – I’d love to hear from you.