TTC Global launches Test Lab: Innovation Research Series

🌟 New Blog Just Published! 🌟 📌 The Future of Coding: How AI Agents Are Reshaping Software Development 🚀 ✍️ Author: Hiren Dave 📖 Agent-driven development denotes a paradigm in which autonomous AI agents generate, test, and refactor code without direct human invocation. In contrast , traditional automation relies on static...... 🕒 Published: 2025-10-24 📂 Category: Tech 🔗 Read more: https://lnkd.in/dWED9V56 🚀✨ #aicoding #aiagents #softwaredevelopmen

Did you know that development activities may account for only 30-50% of the time spent in the software engineering lifecycle? This statistic, noted in our latest perspective paper on Generative AI, highlights its transformative potential. We dive into how integrating Generative AI can streamline processes across various roles, from Product Owners to Developers, allowing teams to automate tasks and enhance the quality of software delivery. By fostering collaboration and focusing on value-added activities, we can elevate performance and drive innovation in software engineering. Download our perspective paper here: https://lnkd.in/gVFaBWkR #IrisSoftware #GenAI #GenerativeAI #SoftwareEngineering #Innovation #Collaboration

Generative AI is changing the game for software engineering — helping teams move faster, build smarter, and focus on what truly drives value. At Iris Software, we’re already seeing GenAI unlock new efficiencies and innovation across Insurance IT — from modernization to intelligent automation. The future of engineering is here — and it’s powered by GenAI. #IrisSoftware #GenAI #Innovation #SoftwareEngineering #InsuranceTransformation

Very interesting point of view. I believe it. As AI start integrating on the development process, you will see changes and adjusted roles on process of software development. Engineers should see AI as a new paradigm in how apporach problems and not as enemy. https://flip.it/kbGNbx

This week, Brandon Whichard, Michael Coté and Matt Ray discuss Claude’s new Excel skills, whether AI is augmenting or automating humans, and the latest developer surveys. Plus, AI making the command line cool again. https://lnkd.in/g4Z-G6BF

When AI writes most of the code, monitoring code health becomes critical! In our November's editing of Hangar DX off-the-record sessions, we are bringing in Adam Bender from Google's DevEx team to discuss how large teams should manage their code health. We will discuss: - The Paradox of AI Velocity - The Decision-Making Nature of Software Engineering - Testing Philosophy Meets AI: The SMURF Framework - What Should We Demand from AI Tools Note that these virtual sessions are not recorded to ensure a candid conversation. When: Nov 14th, 2025 at 11am PST | 2pm EST RSVP: https://lnkd.in/gemgXp4H

AI is Changing System Design System design is evolving—no longer just about components and interfaces, but building systems that learn, adapt, and evolve. Key shifts: Adaptive Architectures: AI-driven decision-making in the core design. Composable & Agile: Dynamic, modular systems optimized by AI. Data & Feedback Loops: Systems learn in real-time from usage and telemetry. AI-Powered Documentation: Design stays synced with evolving code. The future is about designing systems that think, grow, and improve themselves. 💡 #SystemDesign #AI #MachineLearning #SoftwareArchitecture #TechInnovation #AdaptiveSystems #AIArchitecture #FutureOfEngineering

This new paper shows how AI can learn better by creating its own hard problems. #QueST, from the University of Zurich and Microsoft Research, trains models to invent tough coding challenges, then uses them to teach smaller models to think deeper. It starts from a few seed examples, maps how coding ideas connect, and builds combinations that include the rare, tricky ones we usually avoid. If several solvers disagree on a solution, the system knows it found a real challenge, and keeps it. These problems become training set. Smaller models fine tuned on them learn to reason more like humans who practice with difficult examples, not just easy drills. An 8B model trained this way beats its peers and gets close to the massive 671B #DeepSeekR1 671B. What’s interesting here is the philosophy. Instead of chasing scale, #QueST shows that intelligence grows through challenge. The same way we do, by struggling with problems that push us past comfort. Authors: Hanxu Hu and Jannis Vamvas from University of Zurich, Xingxing Huang, Furu Wei, and Rico Sennrich from Microsoft Research.

🚀 Launching My 8-Part Series on Building Production-Grade AI Systems Part 1: Orchestration & Engineering Principles I'm excited to begin a deep dive into the foundations of scalable, reliable AI systems. This series is designed for practitioners who care about robust architecture, deterministic behavior, and engineering excellence. In Part 1, I explore the critical role of orchestration—not just as a routing mechanism, but as a disciplined application of software engineering principles. Determinism, traceability, and modularity are not optional; they are the bedrock of production-grade AI. 🧠 We start with a pragmatic approach to routing and orchestration, where every decision is intentional and every outcome predictable. 📎 Read the full write-up here: https://lnkd.in/g3iqZfeX 📚 If you missed the series overview, catch up here: Build Production-Grade AI Solutions: https://lnkd.in/gAbYaEK9 Stay tuned for the next installment—where we’ll move from orchestration into agentic context modeling and stateful reasoning. 💬 I’d love to hear how you approach orchestration in your own systems. What principles guide your design? #AIEngineering #SoftwareArchitecture #Orchestration #Determinism #AgentSystems #ProductionAI #LinkedInSeries

We want our engineers to choose the tools that work best for them, and that extends to AI. Each engineer has a monthly budget they can allocate on AI tools, from Windsurf to Claude Code, and they can decide to spend that budget on any combination of tools. Hasan Afzal, one of our engineering managers, shares why we landed on that approach below!