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What’s the one programming concept you wish you had learned earlier?
https://www.reddit.com/r/programming/comments/1n2amrg/whats_the_one_programming_concept_you_wish_you/

<!-- SC_OFF -->I’ve been coding for a while now, and something I’ve realized is that there are always concepts you wish you understood earlier—whether it’s clean code practices, debugging tricks, algorithms, or even version control. For me, it was understanding time complexity. Once I got a proper grip on Big O, my entire approach to problem-solving changed. Curious to know—what’s that one concept, tip, or habit in programming that you wish someone had told you about when you started? <!-- SC_ON --> submitted by /u/AsleepChildhood6085 (https://www.reddit.com/user/AsleepChildhood6085)
[link] (https://skyappzsoftware.in/) [comments] (https://www.reddit.com/r/programming/comments/1n2amrg/whats_the_one_programming_concept_you_wish_you/)
Real-World Case Study: Optimizing PostgreSQL Queries with Functional Indexes
https://www.reddit.com/r/programming/comments/1n2xlf4/realworld_case_study_optimizing_postgresql/

<!-- SC_OFF -->We at Mafiree recently published a case study on query optimization in PostgreSQL using functional indexes. It’s based on an actual production scenario where query performance was improved by rethinking indexing strategy. I’d love to hear how others here approach: Functional indexes in production environments Balancing index overhead with performance gains <!-- SC_ON --> submitted by /u/DbOpsNinja (https://www.reddit.com/user/DbOpsNinja)
[link] (https://www.mafiree.com/readBlog/optimizing-postgresql-queries-with-functional-indexes--a-real-world-case-study) [comments] (https://www.reddit.com/r/programming/comments/1n2xlf4/realworld_case_study_optimizing_postgresql/)
Using git as a memory layer for AI code assistants
https://www.reddit.com/r/programming/comments/1n30oo9/using_git_as_a_memory_layer_for_ai_code_assistants/

<!-- SC_OFF -->Hey everyone, I've been exploring an interesting pattern: using git as a queryable memory for AI coding assistants. The problem: AI assistants like Claude have no memory between sessions and every debugging session means re-explaining your entire codebase burning lot of tokens. My approach: Auto-commit every file save to a parallel local hidden git repository, then expose git operations to the AI via MCP. Instead of feeding Claude my entire codebase, it now runs git commands directly on this hidden repo (which contains the full evolution of my codebase). The interesting part is that AI already speaks git fluently. It knows exactly which commands to run for different scenarios. Tradeoffs I'm seeing: - Pros: Massive token reduction, AI can trace bug introduction, perfect undo history - Cons: Disk usage (~12MB per 10k commits), another process running in background Has anyone else tried giving AI assistants access to version control? Thank you!
Alessandro <!-- SC_ON --> submitted by /u/Apart-Employment-592 (https://www.reddit.com/user/Apart-Employment-592)
[link] (https://github.com/blade47/shadowgit-mcp) [comments] (https://www.reddit.com/r/programming/comments/1n30oo9/using_git_as_a_memory_layer_for_ai_code_assistants/)
Self-Healing Systems: Architectural Patterns
https://www.reddit.com/r/programming/comments/1n39yxo/selfhealing_systems_architectural_patterns/

<!-- SC_OFF -->Every self-healing system operates on three core principles that work in continuous loops: Detection: The System's Nervous System Modern self-healing relies on multi-layered health signals rather than simple ping checks. Netflix's microservices don't just monitor CPU and memory—they track business metrics like recommendation accuracy and user engagement rates. Circuit Breaker Integration: When a service's error rate crosses 50%, circuit breakers automatically isolate it while healing mechanisms activate. This prevents cascade failures during recovery. Behavioral Anomaly Detection: Systems learn normal patterns and detect deviations. A sudden 300% increase in database query time triggers healing before users notice slowness. Decision: The Healing Brain The decision engine determines the appropriate response based on failure type, system state, and historical success rates of different recovery strategies. Recovery Strategy Selection: Memory leaks trigger instance replacement, while network issues trigger retry with exponential backoff. Database connection exhaustion triggers connection pool scaling. Risk Assessment: Before taking action, the system evaluates potential impact. Restarting a critical service during peak hours might cause more damage than the original problem. Action: The Healing Hands Recovery actions range from gentle adjustments to aggressive interventions, always prioritizing system stability over perfect recovery. Graceful Degradation: Instead of complete failure, systems reduce functionality. YouTube serves lower-quality videos when CDN nodes fail rather than showing error pages. Progressive Recovery: Healing happens incrementally. One instance restarts at a time, with health verification before proceeding to the next. <!-- SC_ON --> submitted by /u/Extra_Ear_10 (https://www.reddit.com/user/Extra_Ear_10)
[link] (https://systemdr.substack.com/p/self-healing-systems-architectural) [comments] (https://www.reddit.com/r/programming/comments/1n39yxo/selfhealing_systems_architectural_patterns/)