A step-by-step guide to building a cost-efficient multi-agent AI stack by routing planning tasks to Astra and execution tasks to DeepSeek V4.1-Flash via codex-router.
Adapted from @sairahul1# How to Run a 24/7 AI Company for $50/Month (GPT-6 Astra + DeepSeek V4.1 Flash - Full Setup Guide) I was burning $100 in a single night. 9 AI agents. All running at once. All talking to each other. Paying frontier model prices for robot small talk. Then DeepSeek V4.1-Flash dropped. 98% of GPT-6 Astra's score. 1.4% of the cost. So I rebuilt everything. $20 ChatGPT Plus. $30 DeepSeek API credits (and/or a $10 Opencode Go if needed). One clean system that runs 24/7. Here is exactly how. ## The benchmark that changed everything OpenDesign Arena tested 11 models on real everyday tasks. And 11 models scored lower than Flash AND cost more. Only Astra scored higher. But Astra costs 70x more per task. The question stopped being "which model is best." It became "which model do I actually need for each job." ## The $50/month stack I would also suggest to use OpenCode Go for Deepseek, as they seems to provide $60 of usage for just $10 (https://opencode.ai/go) The rule: Astra thinks. Deepseek Flash executes. Astra is the CEO. It reads the goal, breaks it into pieces/tickets, delegates. Flash is the team. It does the actual work at 1/70th the cost. Your job: explain the goal to Astra once. It runs the rest. ## Step 1 — Install codex-router https://github.com/duolahypercho/codex-router One command installs everything and opens the dashboard: The dashboard opens automatically after install. From the dashboard: → Paste your DeepSeek API key (get it at platform.deepseek.com) (or from Opencode) → Enable the DeepSeek provider → Select deepseek/deepseek-v4-flash as an available subagent model → Keep Astra as the Codex root model — do not set Flash as the default for new tasks → If routing is not enabled automatically, run ./bin/model-router codex enable from the router directory → Done — Flash is now available as your explicit implementation subagent ## Step 2 — Unlock Astra godmode in Codex Add this to ~/.codex/config.toml (or just ask Codex): Then keep ~/.codex/AGENTS.md concise and focused on project guardrails. How the two models actually connect: You type your goal in Codex. That is the only place you command it. → Codex runs Astra as the brain — reads your goal, makes a plan → Astra explicitly spawns a bounded subtask with deepseek/deepseek-v4-flash → codex-router routes that subagent call to DeepSeek Flash → Flash executes, result comes back to Astra → Astra reviews and returns the final answer to you Important: if Astra does not explicitly spawn the subtask with the DeepSeek model, the work stays on Astra. The router does not auto-classify tasks. This is why the system prompt in Step 3 matters. What the config settings do: → reasoning_effort = "low" — Astra's benchmarks ran at max. You rarely need that for everyday tasks. Start low, raise per task if needed. → experimental_mode = true — keeps notes across context windows, retrieves relevant earlier messages automatically, reduces wasted tokens, keeps Astra coherent during long refactors and debugging sessions. Restart Codex and start a fresh task after enabling. Verify before you rely on the split: → Root model picker shows gpt-6-astra → Router status reports integrated/routed mode, not native-only → A small delegated test task shows deepseek/deepseek-v4-flash in router activity ## Step 3 — Set your default Astra prompt This is the system prompt that makes Astra behave as an orchestrator and explicitly delegate to Flash. Paste this in Codex settings under System Prompt (just ask Codex): ## Step 4 — The 80/20 routing rule Flash handles 95% of daily tasks at 1/70th the cost when explicitly delegated: 3 things making your agent expensive Most people hit these within the first week. 1. Context bloat Every file injected globally costs tokens on every single call. → Keep AGENTS.md under 800 tokens → Keep SOUL.md under 500 tokens → Keep MEMORY.md under 2,000 tokens → Move project details to per-project files that load on-demand 2. Heartbeats and cron on frontier models A heartbeat just needs to check if there is work to do. Running that check on Astra 48 times per day = expensive robot insomnia. → Configure each heartbeat and cron job to explicitly use the routed Flash model → Same result. 70x cheaper. 3. Breaking the prompt cache DeepSeek caches your system prompt prefix automatically. One cache hit = 1/50th the price of a fresh call. One thing breaks it every time: volatile values in the prefix. → No timestamps in your system prompt → No session IDs in the prefix → Keep structure consistent call to call Codex handles caching automatically when the config is stable. This is why keeping AGENTS.md concise and the config unchanged between sessions matters. ## DeepSeek V4.1-Flash — what actually changed This is not just a cheaper model. The architecture is different. The KV cache reduction is why this works for agents specifically. Cache-hit charges are a huge share of agent costs. Flash's smaller cache means those charges are dramatically lower even when you run it constantly. ## Watch the Astra price cliff (API users) If you ever call Astra directly via API instead of through ChatGPT Plus: The fix: use ChatGPT Plus ($20/month) to access Astra through Codex. No per-token pricing. No cliff. Fixed monthly cost. Full month budget And with Opencode Go, it would be even more cheaper. The setup checklist □ Install codex-router (one curl command) □ Add DeepSeek API key in dashboard □ Enable deepseek/deepseek-v4-flash as explicit subagent model □ Keep Astra as root model — not Flash □ Add config.toml settings for Astra godmode □ Keep AGENTS.md concise and focused □ Paste system prompt in Codex settings □ Configure heartbeats and cron to use Flash explicitly □ Keep system prompt structure consistent (no timestamps) □ Restart Codex and verify router activity shows Flash on delegated tasks That is it. $20 ChatGPT Plus. $30 DeepSeek API. One routing rule. 24/7 AI company for $50/month. Stop paying frontier prices for everything. Start routing intelligently. Resources: DeepSeek API: platform.deepseek.com Opencode Go: opencode.ai/go codex-router: github.com/duolahypercho/codex-router ChatGPT Plus: chat.openai.com If this was useful: → Repost to share it with every developer paying too much for AI → Follow @sairahul1 for more systems like this → Bookmark this — the config and default prompt are the two things you need right now I write about AI, building products, and systems that work while you sleep.
