Why AI Coding Tools Must Adopt a Cache‑First Mindset

Cost of AI coding tools

About 80 % of the expense comes from repeatedly sending the same context. In a 20‑turn refactor each turn can contain 40 000‑50 000 input tokens, of which roughly 35 000 tokens are identical to the previous turn. Using Claude Sonnet 4.5 a 30‑60 minute session costs $1‑4, which scales to $200‑800 per month for 200 tasks.

Cache‑First Loop (Reasonix)

DeepSeek prefix cache

DeepSeek’s Context Caching charges only about 10 % of the normal rate when the new request’s byte prefix exactly matches the previous request; any byte difference invalidates the cache.

Typical agent loop

Round 1: [system] + [tools] + [user_prompt_1] → response_1
Round 2: [system] + [tools] + [user_prompt_1] + [response_1] + [user_prompt_2] → response_2

Most agents rebuild the system prompt and tool definitions each round, resulting in cache‑hit rates below 20 %.

Reasonix three‑zone context

Immutable prefix : system prompt + tool specs + few‑shot examples (fixed for the whole session, eligible for cache hits).

Append‑only log : assistant / tool turn sequence (monotonically increasing, never overwritten).

Mutable scratch : temporary thoughts and plans (reset each round, never sent upstream).

Three iron rules enforce the separation:

Prefix is computed once at session start and never changed.

Log entries are only appended.

Scratch is distilled before entering the log.

Real‑world users report a 99.82 % cache‑hit rate. One user on 2026‑05‑01 processed 435 million input tokens for $12, whereas the same workload without caching would have cost $61.

Five‑dimensional comparison

Design philosophy

Claude Code – Model‑First (strongest model + rich ecosystem) – optimises inference quality and Skills ecosystem.

Cursor – UX‑First (IDE integration) – optimises in‑editor AI assistance.

OpenCode – Open‑First (open‑source agent) – optimises community‑driven replacement.

Codex – Platform‑First (OpenAI integration) – optimises enterprise platform integration.

Qoder – Workflow‑First (multi‑agent collaboration) – optimises agent orchestration.

Reasonix – Cache‑First (economics of caching) – optimises productivity per unit cost.

Cost comparison

Medium refactor (≈30 min): Claude Code $1‑4 vs Reasonix $0.10‑0.40 → ~10× cheaper.

200 tasks / month: Claude Code $200‑800 vs Reasonix $20‑80 → ~10× cheaper.

Long debug (2 h): Claude Code $8‑20 vs Reasonix $0.50‑2.00 → 10‑16× cheaper.

Batch migration (full day): Claude Code $30‑60 vs Reasonix $3‑8 → 8‑10× cheaper.

Cheaper models may need more retries on hard tasks; even when accounting for per‑task cost the advantage remains around 60‑70 % for typical work.

Technical architecture

Language : Claude Code TypeScript (closed‑source); Cursor closed‑source; Reasonix Go (open‑source, MIT).

Model backend : Claude Code Anthropic only; Cursor OpenAI + Anthropic; Reasonix DeepSeek only.

Cache strategy : Claude Code passive API‑level caching; Cursor not applicable; Reasonix active engineering with three‑zone isolation.

Tool‑call repair : built‑in in Claude Code and Cursor; Reasonix uses a four‑stage pipeline.

Parallel tool execution : supported by Claude Code and Cursor; Reasonix provides declarative parallelSafe execution.

IDE integration : Claude Code VS Code + JetBrains; Cursor native IDE; Reasonix terminal‑first with a pre‑release desktop client.

Killer features

Tool‑Call Repair Pipeline : flatten → scavenge → truncation → storm → clean tool‑call.

Model self‑report upgrade : the model emits <<<NEEDS_PRO>>> when the task exceeds Flash’s capability; the system automatically retries with the Pro model.

Real‑time cost panel : each round is colour‑coded by cost (green < $0.05, yellow $0.05‑0.20, red ≥ $0.20).

Use‑case matrix

High‑risk production code, complex architecture decisions → Claude Code (highest inference quality, mature Skills ecosystem).

IDE visual diff & debugging → Cursor (best editor experience).

Batch refactor, code migration, long sessions → Reasonix (maximum cost advantage, >99 % cache hit rate).

Multi‑model flexibility → Cline / OpenCode (model‑agnostic).

Multi‑agent workflow → Qoder / OpenClaw (workflow orchestration).

Daily bug fixes, tests, small refactors → Reasonix (fast, cheap, terminal‑first).

Quick start (≈5 minutes)

Installation

# macOS (brew)
brew install esengine/reasonix/reasonix
# npm (cross‑platform)
npm i -g reasonix
# try without installing
cd /path/to/project
npx reasonix code

Configuration

reasonix setup   # generates reasonix.toml and prompts for DeepSeek API key

Minimal reasonix.toml:

default_model = "deepseek-flash"

[providers]
name = "deepseek-flash"
kind = "openai"
base_url = "https://api.deepseek.com"
model = "deepseek-v4-flash"
api_key_env = "DEEPSEEK_API_KEY"

Basic usage

reasonix                     # start interactive session
reasonix run "Implement TODO in main.go"   # one‑off task
reasonix run --model deepseek-pro "Design module architecture"   # use Pro model
/pro                         # next round uses Pro
/preset max                  # whole session uses Pro
/preset flash                # switch back to Flash
/model flash                 # change model
/help                        # list commands

Real‑world case: 20‑round refactor

Task: migrate 15 Express routes to Fastify.

Total rounds: 20
Total input tokens: ~3.8 M
Cache hit rate: 99.6 %
Cache‑hit tokens: ~3.78 M (billed at 10 %)
Cache‑miss tokens: ~0.02 M (full billing)
Actual cost: $0.35
Claude Code estimate: $3.50‑5.00

The case shows an order‑of‑magnitude cost reduction.

FAQ

Do Reasonix and Claude Code conflict? No. They address different priorities; mixing them can yield the best result.

Why only DeepSeek? Binding to a single backend preserves stable prefix caching; supporting multiple models would break the cache.

Is DeepSeek’s inference quality sufficient? For ~80 % of routine tasks it matches Claude Sonnet within noise; difficult tasks can upgrade to Pro, and rare high‑risk tasks can fall back to Claude.

How is data security handled? DeepSeek’s hosted endpoint runs in mainland China; sensitive code can be self‑hosted or routed through partners.

What changed between Reasonix 0.x (TS) and 1.0 (Go)? Version 1.0 is a rewrite in Go, delivered as a single binary with zero dependencies and faster startup.

Decision diagram