SAT, AUGUST 01, 2026
Independent · In‑Depth · Practitioner‑Tested
DeepSeek Coding

Best DeepSeek V4 Flash Prompts for Agentic Coding (2026) — After 0731 Official Release

DeepSeek V4 Flash 0731 at $0.14/$0.28/M is the cheapest capable agentic coding model after its July 31 official release. Terminal-Bench 82.7% (up from 61.8% preview) puts it within 0.6 points of Grok 4.5 at 14× the price difference. The model supports Responses API natively, runs in OpenCode, and is Codex-compatible — making it a drop-in for most OpenAI-based agent harnesses. These prompts are optimised for the DeepSeek API (model: deepseek-v4-flash) and self-hosted 0731 weights. Note: migrate from deepseek-chat and deepseek-reasoner before October 24, 2026.

⌨️ 6 prompts 🕐 Updated Aug 1, 2026
💡 How to use these prompts: Replace everything in [BRACKETS] with your specific details before sending. Click Copy to copy any prompt to your clipboard instantly.
1
Run a Coding Agent Loop
Run an autonomous coding agent loop on DeepSeek V4 Flash at $0.14/M
[DEEPSEEK V4 FLASH 0731 — RESPONSES API FORMAT]
[Set model to deepseek-v4-flash]

Act as a coding agent. Complete the following task autonomously. Use tools as needed. When you reach a decision point where user input would be helpful, state it clearly rather than stopping — make your best judgment and flag the assumption.

Task: [DESCRIBE THE CODING TASK IN PLAIN ENGLISH]
Stack: [LANGUAGE AND FRAMEWORK]
Repository structure: [DESCRIBE OR PASTE]
Definition of done: [HOW TO KNOW THE TASK IS COMPLETE]

Work through the task step by step. At the end of each step, state what you did and what comes next. If you find a bug or design issue while working, fix it rather than flagging it.
2
Tool-Calling Agent: Multi-Step Data Pipeline
Build a multi-step tool-calling data pipeline autonomously
[DEEPSEEK V4 FLASH 0731 — TOOL CALLING ENABLED]

Build a multi-step data pipeline that completes the following task using the tools available.

Task: [DESCRIBE WHAT DATA GOES IN, WHAT SHOULD HAPPEN TO IT, WHAT SHOULD COME OUT]
Tools available: [LIST YOUR TOOLS — e.g. read_file, write_file, call_api, run_sql]
Input: [DESCRIBE THE DATA SOURCE]
Output: [DESCRIBE WHAT THE FINAL OUTPUT SHOULD LOOK LIKE]
Error handling: [WHAT TO DO IF A STEP FAILS]

Work through each step, call the relevant tool, and proceed to the next step based on the result. Do not stop for confirmation unless a step fails.
3
Debug an Agent That Is Failing Mid-Task
Diagnose and fix any agent that fails mid-task with root cause analysis
An agent is failing on the following task. Help me diagnose and fix it.

Agent task (what it should do): [DESCRIBE]
Agent output / failure point: [PASTE THE ERROR OR THE POINT WHERE IT FAILS]
Agent code: [PASTE THE AGENT CODE OR RELEVANT SECTION]
Stack: [LANGUAGE AND AGENT FRAMEWORK]

Diagnose:
1. What is causing the failure? (Be specific about the code location)
2. Is this a logic error, a tool call error, or a context/state management error?
3. What is the fix?

Output the fixed code. Run through the task mentally after fixing to confirm it would succeed.
4
Generate CLI Commands for a Scripted Task
Generate a complete CLI command sequence for any scripted task with safety warnings
Generate the complete CLI command sequence to complete the following task. Include every command in order. Add a comment above each command explaining what it does and why.

Task: [DESCRIBE WHAT YOU NEED TO DO — e.g. set up a new project, deploy to a server, reset a database]
OS: [LINUX / MAC / WINDOWS]
Current state: [WHAT IS ALREADY SET UP OR INSTALLED]
Target state: [WHAT SHOULD EXIST WHEN THE SCRIPT IS DONE]

After the commands, tell me: if any of these commands are destructive or irreversible, mark them with a WARNING comment and explain what they will delete or change permanently.
5
Code Review Focused on Performance
Identify performance bottlenecks in any code with concrete optimisation steps
Review the following code for performance issues. I am not asking about style or correctness — only about speed, memory usage, and scaling behaviour.

Language: [LANGUAGE]
Expected scale: [HOW MUCH DATA / HOW MANY USERS / WHAT THROUGHPUT]
Current performance: [ANY METRICS YOU HAVE — e.g. slow on 10K records, times out at 500 concurrent users]

For each issue found:
1. What the bottleneck is
2. Why it slows down at scale
3. The specific optimisation (code, query, or architectural change)
4. The expected improvement in concrete terms (e.g. "reduces O(n²) to O(n log n)")

Code: [PASTE CODE]
6
Scaffold a New Project From a Spec
Scaffold a complete project from a plain English spec with all files working
Scaffold a new project from the following specification. Output the full directory structure and the content of every file.

Project: [NAME AND PURPOSE]
Stack: [LANGUAGE, FRAMEWORK, DATABASE, ETC.]
Core features to implement: [LIST THE 3-5 MAIN FEATURES]
Non-functional requirements: [TESTING / LOGGING / AUTHENTICATION / ERROR HANDLING]

Output:
1. Full directory tree
2. Each file with complete content (no stubs or placeholders)
3. A README.md with setup and run instructions

Do not output partial files. Every file should be working code.