Agentic AI has become a hot topic amongst software developers in recent months. As usage of LLMs has become increasingly popular, many developers are switching to agentic AI services to build projects. One point of contention with agentic AI is that productivity is always limited without proper context. Solid context is crucial in streamlining agentic AI tools, as it guards against things like hallucinations and inefficiencies with software development.
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I've spent 15+ years building across multiple tech ventures and cultures - starting in Vietnam, sharpening my craft in Japan and Singapore, then expanding to the U.S., Australia and Europe. Each stop taught me how different ecosystems turn constraints into capability: how to ship products under pressure, build companies from zero, grow talent pipelines and lead teams through the hardest execution challenges.
Peirce believed abduction was the starting point of thought. The origin of all insight. It's how new ideas enter the room. It's what lets a product team hypothesize why a metric dropped. What lets a designer anticipate confusion before it happens. What lets a researcher frame the right question - not just analyze the data.
Building this platform required solving extraordinarily complex engineering challenges. We're not just sending emails - we're orchestrating an entire ecosystem of domain management, inbox creation, deliverability optimization, and AI-driven decision making across multiple legacy systems with limited APIs.
95% of developers now rely on AI‑assisted tooling to accelerate their workflows and catch critical bugs before they ship, indicating a significant shift towards AI solutions in software development.
One of my colleagues raised his hand. He grew up in the Southern Hemisphere, where the seasons are opposite from those in the Northern Hemisphere. He pointed out that naming the updates Spring and Fall shows a Northern Hemisphere bias and is not inclusive of our customers in the Southern Hemisphere.
