Monitor and measure what your teams + AI produce, optimize model routes and agent context for max efficienciy, and govern adoption AI across teams
Track token spend, outcomes, and AI engineering efficiency across your teams
Model routing and context engineering that cut token waste, maximize outcomes
Comprehensive policies and guardrails to minimize AI adoption drisk
Maximize AI returns across development teams, tools, and outcomes
Track AI coding costs and uncover what drives your spend
Allocate AI spend to team budgets and forecast what’s next
Enforce model, budget, and data policies across developers and agents
Understand AI's impact on delivery, quality, and productivity
Route tasks using model performance proven on your own code
Turn shipped work into benchmarks for smarter AI coding decisions
AI Engineering Report Q3 2026: The Speed Trap is now available
Engineering in the AI era
Reports on AI engineering
Upcoming and on-demand events
Playbooks that work
See who ships faster
What's new, what's next
Learn about Faros
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AI Engineering Report 2026: The Speed Trap is now available
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Chris is a founding engineer at Faros. Before Faros, he was a data engineer working on Salesforce Einstein.
Latest posts by Christopher Wu
