A cheap, flexible AI coding setup: VS Code + Kilo Code + Gemini CLI

Published on: 20-Sep-2025
Author: Trisect

Estimated read time: 7–9 minutes

Self-taught developers and solo teams don’t need expensive subscriptions to get real leverage from AI in day-to-day coding. The combo that’s been most effective: VS Code as the base, Kilo Code for agentic coding with bring-your-own-key flexibility, and Gemini CLI as a lightweight, often-free assistant in the terminal.

This write-up explains why this stack works, how to control cost without losing quality, and how to weave it into a practical workflow without turning the craft into prompt babysitting. The goal is predictably faster progress with fewer stalls, not magical one-click builds.

TL;DR

• Use VS Code + Kilo Code to mix premium and budget models per task and keep costs under control with your own API keys.
• Add Gemini CLI in the terminal for free daily queries and quick clarifications without context-switching.
• Lean on AI for two things: getting unstuck with options and offloading repetitive grunt work that’s correct-by-construction.
• Treat models as interchangeable tools: flagship for hard tasks, cost-effective for boilerplate and transformations.
• Keep a simple cost rule: expensive model for the first 20% (direction), cheaper models for the next 80% (execution).

Why this stack

As a self-taught developer, speed of learning and speed of feedback matter as much as writing code, and the stack must stay affordable and flexible as project change. VS Code provides a stable editor base, Kilo Code layers agentic workflows on top (inspired by Cline/Roo Code), and Gemini CLI adds quick, sometimes free Q&A and utility in the terminal. Together, they reduce friction while keeping vendor lock-in low.

The key advantage is control: bring your own API keys, pick the right model per task, and switch providers as prices and quality evolve. That control translates directly into predictable costs and fewer unpleasant surprises on monthly bills.

Kilo Code in practice

Kilo Code builds on the agentic patterns popularized by Cline and Roo Code, then adds its own features while staying provider-agnostic.

In practical terms, that means selecting GPT/Claude/Gemini/Grok for hard reasoning, and swapping to Qwen/Kimi/GLM/DeepSeek for inexpensive scaffolding and repetitive edits. The agent runs inside a familiar VS Code flow instead of a walled IDE.

This is ideal for solo work: one project, one editor, multiple model lanes. The agent can propose plans, write boilerplate, refactor, and explain unknowns, while the developer stays in control of execution and merges. Think rubber duck that talks back and accelerates the routine parts.

Gemini CLI as the free helper

Gemini CLI complements the agent, not replaces it: quick “what does this error mean,” “summarize this doc,” or “draft a small snippet” without leaving the terminal.

It often includes daily free usage, which makes it a great fallback for small asks when premium credits are tight. Keeping it inside the integrated terminal minimizes context switching.

This division of labor keeps cost and attention in balance: the agent does heavier, structured coding tasks; the CLI handles quick clarifications and micro-tasks inline with the shell. Together they provide uninterrupted flow with fewer paid tokens burned.

Cost control: simple, effective rules

• Pick model by task hardness: flagship for ambiguous, multi-step reasoning and design; cheaper models for deterministic transforms, scaffolding, and bulk edits.
• Cap the expensive part to the direction-setting 20%: use top models to outline approach, architecture hints, or tricky algorithms, then switch to budget models for the 80% execution.
• Use short, structured prompts: provide the minimal file context, constraints, and acceptance criteria; avoid conversational padding that burns tokens without improving quality.
• Cache and reuse: create memory bank, which is used by models to have up to date state of the project.
• Measure: note down rough weekly token usage by model family; if costs creep, adjust ratios or raise temperature only when exploration is needed.

Two high-leverage use cases

Getting unstuck

• Ask for strategies, not just answers: “List 3 approaches, with trade-offs” then choose and implement.
• Have the model generate tests that demonstrate the approach; use passing tests as the acceptance gate.
• Keep ownership: treat outputs as drafts, integrate deliberately, and document the decision in a short note.

Clearing repetitive work

• Let the model handle boilerplate, conversions, and mass refactors with clear invariants and file scopes.
• Use smaller models for bulk edits; run linters and formatters to standardize results.
• Verify via diff+tests rather than rereading everything; spot-check a few samples and rely on CI for safety.

Setup notes and defaults

• VS Code: keep the integrated terminal visible and configure common tasks (test, lint, run) as shortcuts to avoid mode switches.
• Kilo Code: enable file-scoped operations and dry-run modes; store API keys in environment variablesl; or just use service like OpenRouter.”
• Gemini CLI: alias common commands, and use it for tiny clarifications or quick JSON transformations that don’t justify spinning up the agent.

A small amount of upfront configuration (presets, aliases, task bindings) pays back immediately in smoother day-to-day operations and fewer context swaps. This keeps the stack feeling like one tool, not three.

Guardrails and etiquette

• Don’t ship what isn’t understood: if a suggested solution can’t be explained in a paragraph, slow down and have the model justify the reasoning or simplify.
• Keep human taste in the loop: AI can propose many adequate solutions; choose the one that fits the codebase’s style and constraints.

The point is leverage without losing craft: augment judgment, don’t outsource it. These guardrails keep quality and credibility intact.

Final thoughts

AI tools are controversial in parts of gamedev, but, used wisely, they shorten the distance between idea and implementation without replacing human judgment or taste.

A cheap, flexible setup—VS Code + Kilo Code + Gemini CLI—lets solo devs and small teams move faster, learn faster, and spend less.