OpenCode brings an AI coding agent right into your terminal. Once you see it understand an entire project instead of just the file you’re currently editing, it’s hard to go back to a regular editor. I spend most of my day in the terminal, whether I’m debugging a systemd service on a RHEL server or writing Bash scripts for the Pro TecMint courses. So when I first tried OpenCode, I didn’t expect much. I had already used a few AI coding tools that felt like add-ons to an IDE and could only guess what was happening based on the file…
Author: drweb
Run a profiling pass on a messy table for the first time and the report reads like a doctor listing everything wrong with a patient who skipped a decade of checkups. Twelve thousand rows fail this check. Four hundred fail that one. Forty fail this other one. Not one line of it tells you which finding carries the most data quality risk.Your brain does the natural thing. It sorts by the biggest number.Please do not start with the twelve thousand.The row count and the risk almost never point at the same problem.The forty rows that mattered more than the twelve…
Full-Stack Developer (Laravel + Inertia/Vue)
Most beginning programmers default to the three largest tech channels on YouTube they can find. Although those channels do have their place, actual communities of programmers on Reddit and Discord frequently point students to less well-known creators. These lesser-known channels do not simply cover textbook definitions. They demonstrate how software actually works in production. Getting stuck on abstract coding ideas can slow your progress. When you are faced with tight deadlines or difficult tech tasks while learning programming in college, you may go as far as to seek help from an established essay writing online platform in order to complete…
Big, distributed computing systems seldom have visible failures. Most of them start without any bang, frequently with a health-check disconnection, a failed TCP connection or a service port that is no longer listening. Such signals are not too big when considered in isolation. However, in the scenario where systems are running with several hundreds of service instances spread across different regions, these small anomalies can be summed into a continuous flow of operational alerts. This alert traffic may eventually turn into a bullying powerhouse of notable operational noise within infrastructure platforms.In most production setups, port-down alerts constitute a significant percentage…
Traditional CI/CD pipelines were designed around deterministic software: The same input, configuration and dependency set should produce the same output. This assumption works for APIs, batch jobs and most containerized services. It does not hold cleanly for autonomous AI agents.An agent is a runtime composition of orchestration logic, prompt templates, tool schemas, retrieval context, model configuration, memory and external tool calls. A one-line prompt edit can change the reasoning path. A JSON schema update can make the agent choose a different tool. A retry-policy change can create an accidental loop. A model upgrade can shift behavior even when the application…
Three years ago, two days before a production push to Azure, I was working through a pull request on a Node.js service. Routine stuff. Then I spotted something in a commit that had been merged two weeks earlier. Already past review, already on the main branch. A Stripe secret key. Not obfuscated, not in a config file. Plain text, right there in the source. Build was green. Tests passed. Nobody had caught it.That incident changed how I think about CI/CD. The problem wasn’t that my team was careless. The problem was that our pipeline had no opinion about security. It…
Most developers use AI for system design in the weakest possible way: They ask one model for one architecture.That is useful, but incomplete.Real system design is not a single answer. It is a negotiation between scalability, cost, reliability, security, delivery speed, operational complexity and team capability. A good architect does not just propose a design. They defend it, attack it, simplify it and document why it prevails.This is where agentic multi-model design becomes powerful.Instead of asking Claude, Codex, GPT or any single model to “design a system,” we can automate a workflow where multiple AI agents debate the architecture and…
When delivery falls apart, the reflex is to blame the team. Missed dates, quality slips, a burned-out squad — leadership tends to reach for a personnel fix and quietly move on. The uncomfortable pattern in most enterprise organizations is that the system itself is the failure mode. Decision latency, priority misalignment, and layers of governance that were designed for a slower era grind against the very people leaders keep asking to grind harder. Talented engineers cannot outrun a delivery pipeline that is structurally set up to stall.Marnus Marx, founder and Delivery Confidence Coach at Elanvia Consulting, joined Alan Shimel to…
Site reliability engineering has been quietly buckling under its own success. The scope of what SRE teams are expected to own — observability, incident response, telemetry pipelines, capacity, cost, resilience — keeps growing while the tools underneath fragment further. AI is showing up as both the reason the workload keeps expanding and the most credible path to bringing it back under control, but only if agents get built on infrastructure that reliability engineers can actually reason about and trust.Tucker Callaway, CEO of Mezmo, sat down with Alan Shimel at PlatformCon 2026 to walk through how his team is trying to…