The AI Engineering Report Q3 2026 is now available! Read the latest research:
THE SPEED TRAP
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Platform
Overview

Monitor and measure what your teams + AI produce, optimize model routes and agent context for max efficienciy, and govern adoption AI across teams

Capabilities
Observe

Track token spend, outcomes, and AI engineering efficiency across your teams

Optimize

Model routing and context engineering that cut token waste, maximize outcomes

Govern

Comprehensive policies and guardrails to minimize AI adoption drisk

Solutions
Solutions
AI ROI

Maximize AI returns across development teams, tools, and outcomes

AI Spend Visibility

Track AI coding costs and uncover what drives your spend

AI Token Allocation

Allocate AI spend to team budgets and forecast what’s next

AI Governance

Enforce model, budget, and data policies across developers and agents

Developer Productivity

Understand AI's impact on delivery, quality, and productivity

Optimal Model Routing

Route tasks using model performance proven on your own code

Build Your Own Bench

Turn shipped work into benchmarks for smarter AI coding decisions

Cover of the Faros AI Engineering Report Q3 2026, The Speed Trap

AI Engineering Report Q3 2026: The Speed Trap is now available

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Engineering in the AI era

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Cover of the Faros AI Engineering Report Q3 2026, The Speed Trap

AI Engineering Report Q3 2026: The Speed Trap is now available

Read the Takeaways
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Cover of the Faros AI Engineering Report Q3 2026, The Speed Trap

AI Engineering Report 2026: The Speed Trap is now available

Read the Takeaways
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Shubha Nabar

Shubha Nabar

Shubha Nabar is the Co-founder of Faros. Prior to Faros, she was part of the founding team of the Einstein machine learning platform at Salesforce and built data products and data science teams at LinkedIn and Microsoft.

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Latest posts by Shubha Nabar

Research
6
min
3/3/26

Monorepo vs Polyrepo: What the PR benchmark data actually shows

Benchmark data from 320 teams comparing monorepo and polyrepo PR cycle times. What “good” looks like and why developer infrastructure matters, especially for AI agents.
monorepo lllustration
Platform Engineering
Metrics
Productivity
Managers
Developers
6
MIN READ
AI Industry
7
min
11/6/24

All you need to know about the DORA metrics, and how to measure them

All you need to know about the DORA metrics, and how to measure them. | Faros.ai
DORA Metrics
7
MIN READ
Product
5
min
6/27/23

Guiding The Way To Smarter EngOps With Lighthouse AI

Today we are very excited to reveal Lighthouse AI - the foundational artificial intelligence engine built into the Faros platform, designed to help engineering organizations make sense of the vast amounts of data that they produce every single day. Learn more...
Faros Announcements
5
MIN READ
AI Industry
15
min
9/1/22

It's Time to "Do More With Less"

Adding more headcount to an organization is an expensive band-aid fix that substantially increases the complexity of the system and often slows it down. Read this candid perspective to learn how software engineering teams can "do more with less".
Productivity
15
MIN READ
AI Industry
10
min
4/11/22

Lead Time for Software Delivery

Lead time measures the velocity of an engineering organization in delivering software — from idea to production. Shorter lead times mean shorter turnaround times for new feature requests, incident resolutions, bug fixes etc. In this blog post, learn more about lead time and cycle time for software delivery, and how to measure them.
Productivity
DORA Metrics
Platform Engineering
10
MIN READ
AI Industry
15
min
2/28/22

Towards EngOps: Scaling engineering orgs with data

With the right tools, engineering leaders can use data to identify bottlenecks, measure progress, better support teams and accurately assess impact over time.
Faros Announcements
15
MIN READ
Faros
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