AI automation at its peak. Maybe.
Jan 22, 26 • 4 min read
Hey Emma, perhaps it’s 2036 as you read this.
By now, you’re likely crafting applications merely by brainstorming, but software engineering wasn’t always this intuitive.
People used to code manually. That end-to-end robo deployment workflow application you built yesterday in mere seconds ? (you hardly know how it works) That used to demand weeks of exhausted focus from a team of developers pushing their cognitive limits.
Stack Overflow was a thing back then—a digital sanctuary, the savior of our souls…

But enough nostalgia. AI and agent-driven coding has been a reality since 2024. Today, I’ll walk you through how we transitioned from agonizing hours of debugging to the era of agent-driven development.
Well, as a software engineer in 2026, you mostly review and guide; you let the AI do the heavy lifting.
By 2026, the term “Coding” has largely been replaced by “Intent Orchestration” and “Architectural Oversight.” We no longer struggle with syntax errors, dependency hell, or library boilerplate. The role of a Software Engineer has evolved into that of a Systems Architect and Vibe Designer.
We spend our mornings defining the “vibe”—the core behavior, user experience, and ethical boundaries—and our afternoons auditing the autonomous agents that did the heavy lifting while we were away. It’s less about how to build (the “how” is a solved problem) and more about what and why.
We used to think Antigravity and Cursor were the endgame. They were incredible milestones—Cursor seamlessly brought AI into the editor, and Antigravity gave it unparalleled agency. But they were still fundamentally trapped in the “editor-first” mental model.
Enter Vibe-Kanban.
Vibe-Kanban isn’t just a project management tool; it’s a living execution engine. Instead of writing code in an IDE and then manually updating a ticket, the ticket is the execution. You drag a feature request from “Ideas” to “Vibe,” and a swarm of specialized agents—each capable of following its own specific, predefined workflow—starts working.
The beauty is in the flexibility: you can connect your favorite editor and view the diffs there through git worktrees, or simply review everything in the browser itself on the live port where the app is running. It treats the entire codebase as a fluid state, orchestrating multiple processes simultaneously. It doesn’t just suggest code; it understands the “vibe” of the entire product lifecycle. It makes the old IDE-centric workflows feel as archaic as using a typewriter in a world of neural links.
LLMs typically rely on outdated or generic information about the libraries you use. Context7 changes the game by pulling up-to-date, version-specific documentation and code examples directly from the source.
In 2026, you can paste accurate, relevant documentation directly into tools like Cursor, Claude, or any LLM via Context7. This ensures you get better answers, eliminate hallucinations, and work with an AI that actually understands your specific stack. The frustration of “outdated documentation” has been consigned to history.
The secret sauce that makes this ecosystem so potent is the MCP (Model Context Protocol) integration. By connecting Context7’s MCP server directly to the Vibe-Kanban execution engine, we’ve created a closed-loop intelligence system.
When you drag a ticket into the “Vibe” column, Vibe-Kanban doesn’t just look at your code; it analyzes your package.json or requirements.txt to identify the libraries in play. It then signals the Context7 MCP to provision a dedicated documentation stream. If you’re using a niche library or a brand-new alpha release, the agent receives a high-fidelity context injection of the exact documentation it needs, filtered for the version you’re actually running.
This means the agent never has to “guess” or “find” docs. The docs find the agent. It’s the difference between a library assistant searching the stacks and a telepathic link to the author’s latest draft.