Category: Data
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trippler contingencies
Planning to go from snow to surf in one day in an electric vehicle naturally meant planning for resilience. Planning a dawn-to-dusk schedule in 30-minute blocks also meant up-front planning for contingencies. Carnival of carving I recently descended from Mount Hotham to Cape Conran, with one one of my teenage children, snowboarding in the morning…
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trippler at PyConAU
I was thrilled to be back for my second PyCon AU – with a wonderfully diverse and inclusive group of technologists – presenting on trippler in a talk titled An EV Trip Planner for Australia. I got a great feedback, including a suggestion to incorporate the many very (but not uniquely) Australian BIG things we…
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trippler for Aotearoa New Zealand
Planning to present my PyCon AU talk to an internal audience at MYOB, I realised the title An EV trip planner for Australia, while entirely appropriate for an Australian conference on Python, wasn’t as inclusive as it could be for the members of a technology organisation encompassing Australia and Aotearoa New Zealand. So trippler now…
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GenAI in Data Platforms
I was part of a panel on the Impact of GenAI on Modern Data Platforms recently, hosted by the Data Engineering Melbourne meetup. It was great to chat with MC Ryan Collingwood and fellow panellists Rahul Trikha, Peter Barnes and Tony Nicol in front of a large and curious crowd. Like the crowd, I felt…
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Team Topologies x EMLT
To provide more resources around the excellent conversation we had with Matthew Skelton on the Stream of Teams podcast in late 2024, we collaborated on an article summarising our chat, which was based on the final chapter of Effective Machine Learning Teams (EMLT). The article titled Team Topologies in action: Effective structures for Machine Learning…
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22 rules of generative AI, 2 years on, Ghibli intermission
This update comes at the peak of the Ghiblification fad. There’s nothing new here and yet I found the release of and response to GPT 4o image generation, including mechanistically crushed and artificially reconstituted Ghibli, particularly shocking. So here’s a retrospective case study for the recent review of rule #10 (labelling ingredients) and a longer…
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Waste not Programmable
Programmable 2025 Melbourne featured a fantastic program, heavy on practical data & AI in an apt reflection of the times. It was also a great chance to catch up with many in the Melbourne tech community. I presented my 7 Wastes of Data Production talk. In the spirit of continuous improvement, I made some minor…
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22 rules of generative AI, 2 years on, part 1
How has my original post on 22 rules of generative AI aged in a period of rapid change? Are these solution considerations as enduring as I thought? Let’s reflect on the original advice and developments in the meantime. Apologies again for minimal references as I timeboxed the writing. In general, evidence should be discoverable/verifiable with…
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Charger hopping
While it’s nice to make good time, when in remote areas, sometimes any route will do. For EV road trip planning in trippler, I first found the direct route, then chose chargers along the route. This approach can fail when there aren’t enough chargers close to the route, as in remote areas. Charger hopping is…
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AI conversations for every role
We always envisaged Effective Machine Learning Teams (EMLT) speaking to multiple roles. Recently we’ve spoken to 4 distinct audiences about ML development, and you can listen in too. Whether you identify with: there’s a podcast* for you with popular presenters – see more below. Product We joined a Product Tank Melbourne event, along with Ana…