Think Forward.
Build Better.
Practical thinking on AI, software engineering, and technology leadership.
Why 1 Year of Agentic AI Production Is Already the Bar
One year of agentic AI in production is now a hiring filter, and most people who qualify learned by doing while organizations expected full delivery output and no room to experiment.
Forward Deployed Engineering Is Not Product Engineering on Location
FDE ships in weeks what product teams ship in quarters, but the difference is not speed. It is scope, ownership, and what happens after the work is done.
Forward Deployed Engineering Existed Before the Title Did
Forward Deployed Engineering is a new label for work that's existed for decades. The best technology leaders embedded with operators, stayed through production, and moved between strategy and implementation. AI increased the leverage; the model stayed the same.
The Token Trap
We stopped measuring engineers by lines of code, then built leaderboards around token usage. The metric changed. The incentive problem didn't. The engineers who will matter are still asking whether the code should exist at all.
AI Can't Staff a Project
Skills and schedules live in systems, but the factors that actually decide who should staff a consulting project—client fit, continuity, trust—usually do not. AI inherits fragmented data; people still route hard staffing calls through the expert who holds the full picture.
AI Infrastructure Is the New Bottleneck
AI progress is no longer constrained only by models. Data centers, permits, power, components, and chip supply now set the pace of deployment.
Broad Models, Narrow Problems
General LLMs and most business workflows are a poor fit. Narrow the problem before you call the model—RAG, fine-tuning, or smaller models—instead of paying in tokens and retries.
You Can Ship Software Without Understanding It
AI-assisted delivery can make a product look finished before the team understands how it fails. Speed helps, but a working demo is not the same as a trustworthy system.