Analysis of AI strategy, technology leadership, and what actually works versus what sounds good in a deck. LinkedIn posts, articles, conference talks, and media appearances.
Ed Zitron argues demand for AI tools would collapse if users paid the real cost. But for knowledge workers whose output is scalable, the math suggests otherwise, even after accounting for subsidies, competition, and the possibility that AI is becoming less of an edge and more of an expectation.
AI coding tools write fast, plausible, and often quietly wrong code — and they won't tell you which. A look at SlopCodeBench, a god class I didn't read, the Claude Code source leak, and what it actually means to keep a human in the loop.
Three things converged in December — better models, better harnesses, and developer holiday time — to make coding agents genuinely useful. The bottleneck has moved from 'can the agent complete the task?' to whether humans can write clear specifications and verify output.
Apple glasses, Meta's facial recognition, OpenAI's screenless device -- the hardware is arriving faster than the norms. What happens to trust, consent, and exploratory thinking when the default shifts to capture?
I watched someone automate their entire car negotiation with an AI agent—it spent three days playing dealerships against each other while they went about their life. Dealerships had no idea they were negotiating with a machine, which tells you everything about where AI agents are headed next.
57% of companies now run AI agents in production, yet quality metrics are sobering. The path to coherent software at scale runs through orchestration and human oversight.
10x cheaper inference changes the math on AI use cases. Teams can stop rationing tokens and start designing for longer context and multi-step workflows.
88% of companies now use AI, workers save 5.4% of hours weekly, and AI professionals command a 56% wage premium. The real shift: AI as superpowers that expand what becomes worth attempting.
AI uncertainty keeps users actively thinking. The most useful AI assistant might be one that's good enough to help, but imperfect enough to keep me honest.
Many organizations create AI plans in controlled environments that fail when confronted with operational complexities. Building flexible, adaptive approaches matters more than rigid strategies.
Discussion on AI strategy and technology leadership
How generative AI is transforming software development across the entire lifecycle
CIO.com demo of how Haiven integrates AI beyond just coding