Your Team Does Not Need Eight AI Coding Tools

Tool sprawl is the new tab sprawl, and it is costing you the same thing: depth.

The hook

Last month I sat down to count the AI coding tools installed across our engineering org. I expected three. The number was seven. Copilot, Cursor, Claude Code, Windsurf, Cody, Devin running autonomously on a branch nobody asked for, and aider quietly doing production work from a principal engineer's personal dotfiles repo. Nobody chose this. It accumulated, one Slack thread at a time.

समीरणदृष्टी चवटेवरी साच जरी · Steady of Gaze upon the Brick

समीरणदृष्टी चवटेवरी साच जरी । तेथे माझे हरी । वृत्ती राहो. ॥ध्रु॥
आणिक न लगे मायिक पदार्थ । तेथे माझे आर्त नको देवा. ॥१॥
ब्रह्मादिक पदे दुःखाची शिराणी । तेथे चित्त क्षणी जडो नेसी. ॥२॥
तुका म्हणे त्याने कळले आम्हा वर्म । जे जे कर्मधर्म नाशवंत. ॥३॥
The person who grasps that all prizes are impermanent stops chasing them and focuses on the one thing that matters.

What I keep seeing

Each tool arrived the same way. A demo that looked magical. A two-week honeymoon. Then the next tool dropped, and the honeymoon started again. I have watched this cycle four times now, and I am starting to think the honeymoon is the product.

The real cost was not the seat licenses, though those added up to something I would rather not say in writing. The real cost was that nobody on the team had gone deep on any single tool's configuration, context management, or prompt patterns. Everyone was a tourist everywhere. Seven tools, zero muscle memory.

The mechanics

Underneath the UI chrome, these are all retrieval-augmented generation systems with different context windows, embedding strategies, and tool-calling architectures. Copilot uses a Fill-in-the-Middle model tuned on your open tabs. Cursor builds a codebase index and lets you @-reference files into a chat context. Claude Code operates in your terminal with full shell access and calls tools in a loop. Windsurf layers multi-step agent "Flows" on top of a similar context engine. Devin runs in a cloud sandbox with its own browser and terminal.

Each of these has different strengths. But those strengths only surface after you learn how the context window fills, what gets truncated, and how to shape your project files (.cursorrules, CLAUDE.md, .github/copilot-instructions.md) to steer the model. That learning takes weeks of daily use with feedback loops. You watch what the tool gets wrong, adjust your context files, watch again.

When engineers switch tools every two weeks, they never reach the part of the curve where the tool becomes genuinely useful. They stay in the "autocomplete is pretty good" zone. In that zone, every tool looks identical and none of them justify their cost.

Where Tuka comes in

Tukaram is not arguing for asceticism. He is making a mechanical observation: the act of chasing is itself the loss. Each new object of desire, each "मायिक पदार्थ" (illusory substance), does not just fail to satisfy. It actively displaces the one practice that would.

This is the exact structure of the tool-sprawl problem. The engineer who opens a Cursor tab while Claude Code is mid-generation is not evaluating. They are fragmenting their own learning signal. They will never develop the instinct for when Claude Code's terminal-first approach beats Cursor's indexed-chat approach, because they never stayed with either long enough to feel the edges.

"जे जे कर्मधर्म नाशवंत" (whatever actions and rituals are perishable) is a statement about attention budgets. Every tool evaluation that does not convert into committed depth is a perishable act. It felt productive. It produced nothing.

What I would actually do

Pick one AI coding tool per team, not per org, because teams have different workflows. Commit to it for a full quarter. Invest the first two weeks writing project-level context files and team-specific prompt patterns. If you are a CLI-heavy backend team, that is probably Claude Code with a well-maintained CLAUDE.md. If you are a React frontend team living in the editor, Cursor with a tuned .cursorrules is a defensible choice. Sunset everything else. Your team is running five AI tools and shipping nothing. Pick one. Delete the rest. The learning compounds only when the tool is the same tool tomorrow.

Chetan Dhandal