Implementing LLM-Native Architecture in Software

📚 New Tutorial on SYUTHD: Implementing Agentic Mesh: Designing Scalable Multi-Agent Workflows in 2026 🏷️ Category: Software Architecture 📖 Read it here → https://lnkd.in/gY-T8EYm 💬 Telegram: https://t.me/nisethtechno 👍 Facebook: https://lnkd.in/gsKv3Dyn #SoftwareArchitecture #Tech #Tutorial #Programming #2026

📚 New article just published on SYUTHD! 🔖 Architecting the Agentic Mesh: Designing Scalable Multi-Agent Systems for 2026 🏷️ Category: Software Architecture 📖 Full article → https://lnkd.in/gj68sexM 👉 Follow our page for more tech tutorials: https://lnkd.in/gsJDptPM 💬 Telegram: https://t.me/nisethtechno 👍 Facebook: https://lnkd.in/gsKv3Dyn #SoftwareArchitecture #Tech #Tutorial #Programming #TechBlog #2026

The resurgence of Functional Programming - A deep dive into the core concepts and real-world applications. #tech #softwareengineering Read the full article on Techidevs: https://lnkd.in/eCDmrYGa

Ever merged modulo with dynamic programming and watched the problem shrink instantly? In competitive programming, the difference between a good solution and a great one is often not speed alone, but state reduction. This is learned from CodeForces itself. This problem is a clean example: instead of thinking in terms of all subset sums, we only care about the remainder after division by k. That shift matters in contests because it saves both time and mental bandwidth and some key ideas that can help you- • Read the problem as a subset-sum divisibility check, not as a full-sum enumeration problem. • Recognise that modulo preserves addition and other operations, so every number can be replaced by its remainder. • Analyse constraints early: a full combinatorial DP is too large, but a remainder-based state fits. • Select the right approach: dp[r] tells whether a remainder r is reachable. • Implement with state compression: update from dp[i][r] to dp[r] carefully. • Debug edge cases like r = 0, repeated values, and transitions that wrap around k. Try solving this problem for instance - https://lnkd.in/gJBE8Qdi What most people miss is that CP improvement is rarely passive practice. It is pattern recognition under pressure. The same mindset appears in real engineering: reduce the state, constrain the search space, and optimize what truly matters instead of brute-forcing every possibility. How often do you pause and ask whether the problem can be redefined before you try to solve it? Follow Vishu Kalier for more such insights. #CompetitiveProgramming #DynamicProgramming #ModuloDP #DSA #Algorithms #ProblemSolving #Coding #SoftwareEngineering #cfbr #Eternal #Leetcode #Codeforces

Unpopular opinion: Documentation and source code are better teachers than 10-hour tutorial videos. I’ve recently been spending more time diving into open-source repositories like this one, and the clarity you get from seeing how senior engineers structure real-world logic is unmatched. Don't get me wrong, videos are great for getting started. But if you want to understand: How complex types are actually handled How to structure a library for scale The "why" behind design patterns ...nothing beats opening the lib folder and reading the implementation yourself. What’s one repo that taught you more than a course ever did? 👇 #SoftwareEngineering #OpenSource #WebDevelopment #CleanCode #LearningToCode #100daysofcode

Many people use LLM coding agents to hyperthread 67 improvements at the same time. That's useful. The other thing you can do is challenge yourself to build more ambitious stuff than you could have before. And in that case, it becomes even more important that you get your architecture right, and that you set your core goals for the project very clearly. At Framer, we ship projects of a complexity I only really know from open source work, and of a scale that most companies rarely dare to touch on existing products. This was true before the advent of LLMs, and is still true today. And we do this pretty much on a regular basis. We have multiple examples of such projects already going on and just started another one about future-proofing our Content Management System, which is growing to host larger and larger enterprise sites. Even with a strong team, projects like this will take months, but if you get the goals and architecture right, you'll know what parts to start with and what decisions to defer. And some things don't change: To be able to handle these projects at all, we use RFCs where needed, and are very conscious about cutting down to reach intermediate milestones and iterate on learnings. If you feel like after years in the industry your IC growth is stalling and you want to be challenged, check https://lnkd.in/dXXuRRWR and drop one of us a DM.

Dependency count is easy to measure. Dependency importance is not. Two projects can have the same number of dependencies and completely different risk profiles. Because structure is what drives impact. Not all nodes in a graph are equal. Some are replaceable. Some are load bearing. We just don’t have good ways to surface that yet. That is the problem space I’ve been exploring recently. #opensource #devtools #softwareengineering #architecture #programming

Just wrapped our CSE314 Custom Compiler Project at DIU! 🚀🎓 We engineered a complete C-based compiler frontend from scratch, processing a custom "mini-language" defined by a 24-production Context-Free Grammar. 🛠️ To achieve $O(1)$ tokenization, we built a zero-string-matching Lexical Analyzer using a purely table-driven 85x43 DFA transition matrix—compressing 256 ASCII characters into 43 equivalence classes. 🔢✨ For syntax, we implemented an LL(1) Predictive Parser featuring specific LL(2) lookahead logic to seamlessly distinguish complex structural components. 🧠 We also designed a custom interactive terminal UI for real-time code testing, which outputs both the generated token stream and a step-by-step trace of the predictive parsing stack. 💻📉 Incredibly proud of the team for building this deep architecture! Check out the code on my GitHub! 🔗👇 https://lnkd.in/gR3NF45T #CompilerDesign #CProgramming #SoftwareEngineering #DIU #ComputerScience #Lexer #Algorithms #TechStudent

Anybody else getting excited about language oriented programming in connection with coding agents? If so, I am in dire need of some sparring :). Latest experiment is creating a targeted DSL for architecture in Langium with a LSP server serving Opencode - its a way of forcing a coding agent to speak a particular language, in this case my opinionated take on the software architecture of a given software project. Anyone up for challenging this?

TriAttention looks like it could be a big deal for local coding assistants. If you haven't seen it the TLDR is it significantly reduces the memory LLMs require for caching at inference time. But doing a great job at caching the most important tokens also makes it easier for the model to remember the most important bits when reasoning over long sequences. For coding assistants the reduced memory makes it easier to use medium sized models on a single GPU and the long sequence reasoning makes it better for coding. Paired with a good open source harness like OpenCode or Pi, that may make for much more cost effective coding agents.