A year of using AI in daily work. Concrete cases where it earned its keep, concrete cases where it didn't, and the pattern that explains the difference. Worth being honest about both halves of the practitioner experience.
The playbook for a single-tenant to multi-tenant migration done well, additive schema, identity backfill, dual-path policy enforcement, row-level security, observability for both paths, traffic shift, deprecation. What I wish I'd known on day 1.
Gemini 3.1 Pro and Sonnet 4.6 land inside a week, Alibaba slips Qwen3.5 out hours before Lunar New Year, the EU stretches its AI Act timeline, and Baker McKenzie cuts 600-1,000 attorneys citing AI. The cadence is compressed; white-collar is now in scope.
Enterprise AI governance frameworks don't scale down to a solo operator, and yet governance is one of the four positions I keep coming back to. Here's the lightweight-but-real version I actually run, and why each piece earns its keep when nobody else is going to ask.
Most teams design types ad-hoc and apologize for the shape later. The periodic-table layout, an ordering property, vertical families, horizontal periods, turns type design into a discipline that lets you see the missing types before you build the wrong ones.
Delhi hosts the first Global South AI summit, Chinese labs race to ship before Lunar New Year, OpenAI quietly retires GPT-4o and GPT-5 from ChatGPT, the Microsoft-OpenAI-AWS triangle gets rewired, and Block crosses the half-the-workforce mark on AI-cited cuts.
Three years after I sketched what a real training-data market would need, the structural pieces still aren't in place. The lawsuits stalled, the settlements happened, the tiny markets exist at the edges, and the actual marketplace at scale doesn't. Worth being honest about why.
A pragmatic playbook for small organizations adopting AI in 2026, where to start, what not to do, how to build governance early without grinding the work to a halt, and how to think about tools and data before vendor lock-in does it for you.
Super Bowl week. Anthropic ships Opus 4.6 with agent teams and takes a swing at OpenAI on national TV. Mistral pushes Voxtral and closes the open-weights audio gap. Block cuts headcount nearly in half. SB 53 is officially live and the first frontier safety frameworks are in the wild.
By early 2026, open-weights models are competitive with closed frontier on most workloads I actually run. The gap that remains is real but narrower than the keynote conversation suggests, and the practical case for owning your stack got stronger, not weaker.
A year after Anthropic shipped MCP, the protocol is everywhere. OpenAI's Apps SDK, GitHub Agent HQ, every major lab. Time to grade my earlier takes. Some held up. Some didn't. A few things genuinely surprised me.
Post-Davos week. The China open-weights flywheel is the most consistent shipping story in AI right now. Kimi K2.5, Qwen wired into Taobao, Tencent dropping cash for Lunar New Year. Plus Yahoo Scout on Claude, three different bets on agentic commerce, and the AI-cited layoff playbook hardening.
