Rooms where the field is moving.

I attended YYC DataCon in Calgary. Three sessions filled most of my notes.

Pradeep Karpur spoke on investment discipline for the agentic era. What I wrote down: cost accountability for AI usage, held by a head of agent economics; token cost reporting; and an agentic circuit breaker — stop limits on usage or cost overruns.

Nathan McAuley and Abhi Pandey’s fireside chat followed Avenue Living’s journey — as presented, 23,000 units across the United States and Canada. The trade-off they described was speed to value against scalability, with data quality and data governance at its centre. Treating the work as a business project rather than an IT project meant an executive sponsor and a medallion architecture. One point from that conversation stayed with me: data governance needs a better word or better branding, because governance lowers enthusiasm.

Frank Bergdoll, AI Lead at SAIT, and Cherie Bowker spoke on higher education as the sector where AI arrived before the strategy did. I came away with three anchors: an AI policy; an AI strategy with a name, an owner and a budget; and participation and adoption numbers. The strategy steps, as I noted them: see it; set the floor with boundaries; change the work through workflow redesign; change the measure to outcomes and evidence; and a governance step.

Two of these land directly on my own agent work: cost limits that stop an agent before it overruns, and the reminder that AI is only as good as the data and the ownership underneath it.

I attended the National AI Summit in Calgary, drawn by the AI for Healthcare track: I wanted to see how AI is actually being used in clinical settings, how practitioners handle HIPAA and PII obligations around health data, and to collect new ideas for my own precision-health platform work.

Two speakers stood out. Dr. Gabriel F. T. Variane’s opening keynote on the AI-powered healthcare professional — telehealth practice, an intelligence database, smart glasses in the clinical workflow — showed how far daily clinical tooling has come. And Prof. Khorshid Mohammad, on moving from AI assistants to agents, left the strongest impression of the day: a clinician building genuinely creative agentic applications without a computer-science degree or a software-engineering title — developing with AI much the way I do.

That was the surprise worth writing down: healthcare professionals are doing serious AI-delivery work, some running their own homelabs, and in some cases accomplishing more with these tools than people I know with IT backgrounds.

The connection to my own practice was direct: clinicians doing AI-delivery work and standing up their own homelabs are walking the same road I am, from the other direction — and the healthcare track sent me home with new ideas for the precision-health work.

I attended the Precision Health and Longevity Summit — two days at the Hyatt Regency, organized by Calgary’s DIL Walk Foundation — for the same reasons that took me to the National AI Summit: how AI is being used in healthcare, how health data is handled responsibly, and ideas for my own precision-health platform. There was also a personal draw: Wish Bakshi, a data and AI systems engineer who guest-lectured in my Master of Data Science and Analytics, was speaking — the person I went to see.

The precision-medicine sessions gave me the most to write down. Dr. Ahmed El-Sohemy’s nutrigenomics talk — genetic testing feeding personalized nutrition, and the case for tracking waist circumference rather than body fat alone — left me with a literal action item in my notes: capture this data. Dr. Faisal Khan of OncoHelix made pharmacogenomics concrete with a question I hadn’t thought to ask: what type of metabolizer am I? One test, relevant to a lifetime of prescribing decisions. And Genieve Burley’s mindfulness workshop sent me home asking whether meditation belongs in my own routine.

The surprise came from the aging sessions: Denmark’s community-care model, with home-care visits beginning around ages 75–80 and, as presented, a smaller share of spending going to healthcare than Canada’s with better results — and simple instruments like walking scores and a frailty index doing serious predictive work. Also memorable: a 70-year-old retiree describing the AI-assisted system they had built to track their own investment trades.

What came home with me was a list of concrete additions for the precision-health work: new metrics to capture, a pharmacogenomics test worth taking once, and the reminder that longevity science keeps producing measures simple enough to automate.