From the team building Progress

The Progress blog

Insights on shipping software, team visibility, and getting clarity across all your tools.

June 9, 202615 min read

Developer Burnout Detection: How Engineering Leaders Can Spot It Before It Costs Them

Developer burnout detection is a critical skill for engineering leaders, as burnout rarely announces itself but instead surfaces through subtle behavioral shifts like declining code quality, reduced communication, and disengagement. This guide helps startup engineering managers identify early warning signs before burnout becomes a costly delivery risk that stalls product launches or degrades long-term code quality.

June 8, 202614 min read

9 Best Code Deployment Risk Tools for Engineering Teams in 2026

Engineering teams can get ahead of production incidents and costly rollbacks by choosing the right code deployment risk tools—this guide evaluates nine leading platforms based on integration depth, signal quality, and real-world value for teams of all sizes, from AI-native intelligence platforms to static analysis engines and feature flag systems.

June 7, 202616 min read

Dev Team Health Metrics: What They Are, Why They Matter, and How to Use Them

Dev team health metrics go beyond simple activity tracking to give engineering leaders a diagnostic layer that reveals friction points, workload imbalances, and hidden codebase risks. This guide explains what these metrics are, why they matter for sustainable team performance, and how to use them to turn vague concerns into concrete, actionable insights.

June 6, 202616 min read

How to Improve Developer Productivity: A Step-by-Step Guide for Engineering Leaders

Engineering leaders looking to improve developer productivity will find a practical, step-by-step framework here that goes beyond tracking tickets and PRs to identify real friction points slowing teams down. This guide covers establishing baselines, reducing cognitive overhead, optimizing delivery pipelines, and building visibility systems that help managers and CTOs make meaningful, lasting improvements to how their teams actually work.

June 5, 202615 min read

9 Best Tools for Engineering Leaders in 2026

The best tools for engineering leaders in 2026 go beyond dashboards to surface real risk, align distributed teams, and improve delivery health across engineering intelligence, incident response, observability, and people management. This guide covers nine platforms that help technical leaders at startups and growing SaaS companies reduce friction, communicate clearly to executives, and lead with greater confidence.

June 4, 202613 min read

Code Review Bottlenecks: Why They Happen and How to Fix Them

Code review bottlenecks are a silent productivity killer that can stall sprints, block developers, and quietly derail release timelines without any single obvious failure point. This guide breaks down why these structural slowdowns happen in engineering teams and offers practical, systemic solutions to keep pull requests moving and delivery on track.

June 3, 202616 min read

How to Measure Developer Productivity: A Step-by-Step Guide for Engineering Leaders

Learning how to measure developer productivity requires moving beyond misleading vanity metrics like commit counts and lines of code. This step-by-step guide helps engineering leaders build an honest, actionable measurement framework that captures real team performance, identifies hidden bottlenecks, and supports better decision-making without reducing engineers to data points.

June 2, 202615 min read

Code Churn Analysis: What It Is, Why It Matters, and How to Act on It

Code churn analysis measures how much recently written code gets rewritten or deleted within weeks, revealing hidden inefficiencies that traditional velocity metrics miss. This guide explains how startup engineering teams can use code churn data to identify risk areas, reduce wasted effort, and turn surface-level progress into genuine forward momentum.

June 1, 202615 min read

9 Best Engineering Analytics Tools for Technical Leaders in 2026

This guide evaluates the best engineering analytics tools available in 2026, helping technical leaders—from CTOs to engineering managers—cut through development data noise to gain actionable insights on team health, delivery pace, and code quality. Covering nine platforms assessed on integration depth, AI capabilities, and scalability, it provides a practical framework for choosing the right solution whether you're tracking sprint performance, communicating progress to stakeholders, or identifying early burnout signals.

May 31, 202613 min read

AI-Powered Engineering Insights: What They Are and Why Your Dev Team Needs Them

AI-powered engineering insights transform raw development data from GitHub, CI/CD pipelines, and project trackers into decision-ready signals that eliminate manual analysis. Instead of stitching together metrics across multiple dashboards, engineering leaders get continuous, interpreted patterns that reveal sprint health, team burnout risks, and delivery bottlenecks—giving technical teams the clarity they need to lead proactively rather than reactively.

May 30, 202615 min read

How to Set Up Automated Engineering Reports: A Step-by-Step Guide for Dev Leaders

This step-by-step guide shows dev leaders how to set up automated engineering reports by connecting existing tools like GitHub and Linear to eliminate hours of manual data gathering each week. Learn how to build a reporting system that continuously surfaces risk, tracks initiative health, and delivers actionable insights to stakeholders — whether you're managing a small startup team or multiple engineering squads.

May 29, 202614 min read

9 Best AI Engineering Management Tools for Technical Leaders in 2026

This guide evaluates the 9 best AI engineering management tools available in 2026, helping technical leaders move beyond raw data to actionable insights about team velocity, deployment risk, and workflow bottlenecks. Each platform is assessed on integration depth, ease of adoption, and its ability to surface meaningful signals from commits, pull requests, and development activity in real time.