DevDynamics

CTOs keep asking the same question: “Is AI actually making us faster?” We built the AI Adoption Dashboard to answer that with data from your team. It connects with tools like GitHub Copilot and Cursor and shows adoption broken down by team and time period in one place. It also shows individual level AI usage data for understanding gaps on the ground. So instead of hearing “this team loves Copilot,” you can see whether increased usage translates into faster delivery or fewer regressions, and where it doesn’t. See AI adoption & impact in your engg org by starting a trial here -> devdynamics.ai

2025 Rewind: DevDynamics edition! 🚀 Looking forward to 2026! 🎉

One of the most common challenges engineering managers face is staying aligned with their team’s availability—especially during critical releases. DevDynamics introducing HR tool integration to bring leave insights directly into your engineering analytics. Now, managers can see leaves, overlapping vacations, and overall team capacity—all in the same dashboard where they track commits, pull requests, and incidents. No more back-and-forth with HR tools or spreadsheets. Just one view that keeps engineering and HR data connected, helping leaders plan better and ensure smoother delivery cycles. #HRTech #EngineeringAnalytics

One of the most common challenges engineering managers face is staying aligned with their team’s availability—especially during critical releases. DevDynamics introducing HR tool integration to bring leave insights directly into your engineering analytics. Now, managers can see leaves, overlapping vacations, and overall team capacity—all in the same dashboard where they track commits, pull requests, and incidents. No more back-and-forth with HR tools or spreadsheets. Just one view that keeps engineering and HR data connected, helping leaders plan better and ensure smoother delivery cycles. #HRTech #EngineeringAnalytics

One of the key challenges we faced with DevDynamics MCP was invoking it effectively in LLM chats. We had to be very explicit each time — reminding the model to perform basic steps like login before calling an API. With Claude Skills, this problem is largely solved. Its guideline-based skill approach ensures that whenever a query fits the defined criteria, the right MCP gets invoked automatically — following the provided steps seamlessly. This design pattern has broader implications. It can be leveraged by Agentic chatbots to move beyond rigid workflows. Most chatbots today struggle to maintain natural conversation flow because they’re built around predefined, inflexible logic. A skills or guidelines-driven approach enables chatbots to act more human-like — invoking the right tools at the right moment. The best part is that guidelines can evolve as agents learn new behaviors, without changing any underlying code. #AI #LLM #Agents #MCP #Chatbots #AIDesign

Many engineering leaders want to measure how much code their teams are generating with AI. It feels like a good indicator of AI adoption. But if you look at code generation in isolation, it’s no better than tracking lines of code — it doesn’t tell the full story. To make it meaningful, you need to look at how AI is influencing the rest of your SDLC: 1. Are automation tests increasing? 2. What’s the impact on your DORA metrics? (More code could mean faster releases—or more failures.) 3. How is your defect escape rate changing? Without connecting these signals, AI adoption becomes a vanity metric. That’s exactly what we’re solving at DevDynamics — helping teams see the complete picture of engineering performance, not just output.

We’ve just launched the DevEx Survey module in DevDynamics — one of our most requested features. With this release, DevDynamics becomes a truly holistic platform to understand your engineering organization — combining system metrics like DORA and SPACE with team sentiment from DevEx surveys. Leaders can now see not just what is happening in their engineering process, but why. From delivery performance to collaboration and developer well-being — all in one place. This launch brings us closer to our mission of helping teams build healthy, high-performing engineering organizations with data that actually tells the full story. #DevDynamics #DevEx #DORA #SPACE #EngineeringLeadership #DeveloperExperience

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🚀 We’re Hiring: Marketing Intern at DevDynamics We’re growing fast. There’s more work than hands. And honestly, we’re excited to bring in someone fresh who’s ready to learn, experiment, and make an impact. This isn’t a “get coffee and take notes” kind of internship. You’ll plan, create, and execute real campaigns, work across marketing, sales, and product teams, and see your ideas go live. 📍 Location: Pune (Full-time, In-office) 🕒 Duration: 6 months | Paid Internship If you want to learn a lot, ship a lot, and be part of building something meaningful - this is your chance. 💡 Tag someone who should see this or apply yourself.

[Feature alert] - Goals for Engineering teams Most engineering goals fail because - They are abstract Most teams set goals like “ship faster” or “improve quality” but they weren’t tied to real, trackable metrics like PR cycle time or bug rate. - Tracking & Reporting is manual and scattered Even when specific metrics existed, teams tracked them across a mix of Notion pages, Google Sheets, and ad-hoc dashboards with no shared view or automation. Reporting progress meant someone had to pull data from Jira, GitHub, or DORA tools often just before a review or leadership meeting. If no one did it, the goal went dark. - By the time you get the updates, its already late. You donot get an opportunity to course correct. We built DevDynamics Goals to change that. ✅ Tie your goals to actual delivery outcomes ✅ Progress updates live based on PRs, reviews, deploys ✅ You see what’s stuck, what’s moving, and what’s at risk while its time to course-correct. This is to keep engineering and business truly aligned while the work is still happening. 📌 Book a demo to see it live - https://lnkd.in/dZHcVFvj