A data-driven retrospective of one month of high-intensity AI-assisted engineering: 466 sessions, 55,224 turns, 1,772 decisions extracted from raw chat logs into a durable knowledge graph. Built the day before Anthropic announced 'dreaming' as a feature.
If your Lens recaps come out cluttered with reasoning preambles or hallucinated detail, the fix is almost always upstream of Lens. A field guide to picking a model and configuring LM Studio for clean daily snapshots.
I gave a year of Adafruit Clue environmental data to Gemini, GPT-5.4, GPT-5.5, and Claude Opus 4.7. Same prompt, same dataset, four very different answers — and only one of them asked for more data.
I spent most of a day in a stalled debug loop with one AI model before opening a fresh session with another. The lesson wasn't about which model is smarter — it was about going upstream.
Apple just put two hardware engineers at the top of the company. The cloud labs are quietly losing money on their best customers. From inside a hybrid practice, here's what the local share looks like and why it's growing.
I assumed a specialized vision model would win. I was wrong. A head-to-head on a hard handwriting corpus ended with the general-purpose MoE on top.
How I run a multimodal LLM on four-year-old hardware to read a family archive without sending anything to the cloud.
I have three collections of family letters spanning a century. Until recently, reading them properly would have taken years. Now it takes an afternoon.
Vannevar Bush described the memex in July 1945. It took 80 years to become buildable, because it required two things that didn't coexist until now: cheap private AI, and the conviction that data ownership is the last real moat.
Frameworks are inevitable. They emerged for Ruby, Python, and PHP. Now they're emerging for agentic development. Here's the one that evolved on my workbench — and what it taught me about working with AI.
AI agents are only as good as the information they can find. Context architecture is the skill of building structured environments where agents reliably retrieve exactly what they need.
The highest-demand AI skill in 2026 isn't coding. It's writing instructions so precise that a machine can't misinterpret them.
Six months of surviving as a one-person engineering team produced something I didn't expect: a layered AI operating system that grew organically from daily necessity.