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Latest Posts
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SDLC - QA
The QA role is quietly transforming from testing interfaces to evaluating agent behavior and reasoning. Instead of pass/fail scripts, testers now focus on behavior coverage, feedback loops, and system observability. Quality is no longer just about functionality — it’s about understanding why an AI system acted the way it did. -
SDLC - Agile to Agentic
Agile gave us structure, but startups are now exploring agentic workflows where AI contributes directly to planning, estimation, and execution. Core practices like backlog grooming, story pointing, and burndown tracking are being reimagined — with agents assisting, suggesting, and sometimes completing tasks. This shift isn’t just about speed, but about redefining how teams work and who’s doing the work. -
Motion Meaning Metrics
As AI transforms how we work and think, it’s critical to understand who does what—between humans and machines. This framework maps roles across physics, philosophy, and business using RACI and the 4 A’s of AI (Assist, Automate, Augment, Autonomy). It’s a guide to help you define the boundaries between motion, meaning, and machine. I got to do some deep and theoretical work on my flight back from Europe over the weekend (nothing better for than no WiFi, limited in-flight infotainment).
Other
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Advisory Sessions
Startups don’t need formal structures to engage customers—they just need the courage to show up. ... -
Demo Early, Demo Often
Early demos are more than a way to test features — they’re a tool to validate your idea, sharpen ... -
Find your Community
You can learn almost anything online—but true acceleration happens in community. Being part of lo...