40 Best DeepSeek Prompts in 2026: Templates for the Open-Source Powerhouse

Solve this step by step. Show every step of your reasoning — don't 
skip to the answer.

Problem:
[STATE THE PROBLEM]

Instructions:
1. Restate the problem in your own words to confirm understanding
2. Identify what information is given and what's being asked
3. Plan your approach before calculating
4. Execute each step, showing work
5. Verify your answer by checking it against the original constraints
6. State the final answer clearly

If you're uncertain about any step, flag it and explain why.

Prove the following statement. Use a rigorous mathematical proof.

Statement: [THEOREM OR CLAIM TO PROVE]

Requirements:
- State all assumptions explicitly
- Use standard proof techniques (direct, contradiction, induction — 
  whichever is most appropriate)
- Justify each step — no "it's obvious that..." leaps
- If multiple proof strategies exist, use the most elegant one and 
  briefly mention alternatives
- Write the proof so a math undergraduate could follow it

After the proof: explain the intuition behind WHY this is true in 
plain English (2-3 sentences).

Solve this probability/statistics problem rigorously.

Problem:
[DESCRIBE THE SCENARIO AND QUESTION]

Steps:
1. Define the sample space and events
2. State which probability rules or distributions apply (and why)
3. Set up the calculation with clear notation
4. Solve step by step
5. Interpret the result in plain English
6. Sanity check: does this answer make intuitive sense?

If assumptions are needed (independence, distribution type, etc.), 
state them explicitly and note how the answer changes if 
assumptions are violated.

Solve this optimization problem.

Objective: [WHAT TO MAXIMIZE OR MINIMIZE]
Variables: [WHAT I CAN CONTROL]
Constraints:
- [CONSTRAINT 1]
- [CONSTRAINT 2]
- [CONSTRAINT 3]

Steps:
1. Formulate the problem mathematically
2. Identify the type of optimization (linear, convex, NP-hard, etc.)
3. Choose an appropriate solution method
4. Solve step by step
5. Verify the solution satisfies all constraints
6. Analyze sensitivity — how does the answer change if constraints shift by 10%?

Present both the mathematical solution and a practical interpretation.

Solve this logic puzzle. Show your complete deduction chain.

Puzzle:
[STATE THE PUZZLE — constraints, clues, relationships]

Method:
1. List all given constraints
2. Make initial deductions from each constraint alone
3. Combine constraints to narrow possibilities
4. Use elimination to resolve ambiguities
5. Verify the solution satisfies ALL original constraints
6. Show that the solution is unique (or identify all valid solutions)

Format: use a grid or table to track possibilities as you eliminate them.

Estimate [QUANTITY] using first-principles reasoning.

The question: [WHAT YOU WANT TO ESTIMATE]

Approach:
1. Break the problem into smaller, estimable components
2. State your assumption for each component (with reasoning)
3. Calculate step by step
4. Identify which assumptions contribute most uncertainty
5. Provide a range: lower bound, best estimate, upper bound
6. Sanity check against any known reference points

Show your work at each step. The reasoning matters more than 
the exact number.

Analyze the time and space complexity of this algorithm.

Algorithm:
[DESCRIBE OR PASTE THE ALGORITHM]

Analysis:
1. Identify the input size variable(s)
2. Count operations for best, average, and worst cases
3. Express complexity in Big-O notation (with justification)
4. Analyze space complexity separately
5. Compare to the theoretical lower bound for this problem type
6. If it's suboptimal: what algorithm would be better, and why?

Show the mathematical derivation, not just the final Big-O answer.

Analyze this strategic situation using game theory.

Scenario:
[DESCRIBE THE SITUATION — players, choices, payoffs]

Analysis:
1. Model as a formal game (payoff matrix or extensive form)
2. Identify dominant strategies (if any)
3. Find Nash equilibrium/equilibria
4. Determine if the outcome is Pareto optimal
5. Analyze how the game changes with repeated play
6. Practical recommendation for each player

Explain the game theory concepts as you use them — I want to 
understand the framework, not just the answer.

Design an algorithm to solve this problem.

Problem:
[DESCRIBE THE PROBLEM]

Input: [FORMAT AND CONSTRAINTS]
Output: [EXPECTED FORMAT]
Performance requirement: [TIME/SPACE CONSTRAINTS]

Steps:
1. Analyze the problem structure (what type of problem is this?)
2. Consider 2-3 algorithmic approaches with tradeoffs
3. Choose the best approach and justify why
4. Write pseudocode first
5. Implement in [LANGUAGE]
6. Analyze complexity (time and space)
7. Write test cases covering edge cases
8. If applicable, describe how this scales to larger inputs

Optimize this code for performance. I need it significantly faster.

Code:
[PASTE CODE]

Current performance: [METRICS — runtime, memory, throughput]
Target performance: [WHAT "FAST ENOUGH" MEANS]
Language: [LANGUAGE]
Constraints: [WHAT I CAN'T CHANGE]

Analysis:
1. Profile the code — identify the actual bottleneck (don't guess)
2. Explain the algorithmic complexity of the current approach
3. Propose optimizations ranked by expected impact:
   a. Algorithmic improvements (better approach entirely)
   b. Data structure changes (more efficient storage/access)
   c. Implementation-level optimizations (caching, loop unrolling, etc.)
4. Implement the top optimization with benchmarks
5. Estimate the improvement factor for each change

I need to choose the right data structure for this use case.

Operations I need to perform frequently:
- [OPERATION 1 — e.g., lookup by key, ~10,000 times/sec]
- [OPERATION 2 — e.g., range query, ~100 times/sec]
- [OPERATION 3 — e.g., insert, ~1,000 times/sec]

Data characteristics:
- Approximate size: [NUMBER OF ELEMENTS]
- Key type: [STRING / INT / COMPOSITE]
- Value type: [DESCRIPTION]
- Sorted access needed: [YES / NO]
- Concurrency: [SINGLE THREAD / MULTI-THREADED]

Compare at least 3 candidate data structures:
1. Time complexity for each operation
2. Space overhead
3. Cache performance
4. Implementation complexity
5. Your recommendation with reasoning

Implement [FEATURE] end-to-end.

Stack:
- Frontend: [FRAMEWORK]
- Backend: [FRAMEWORK/LANGUAGE]
- Database: [DATABASE]
- Auth: [AUTH METHOD]

Requirements:
[LIST FUNCTIONAL REQUIREMENTS]

Deliver:
1. Database schema/migration
2. Backend API endpoints (complete, with validation and error handling)
3. Frontend components (complete, with loading and error states)
4. Tests (at least: happy path, validation errors, auth failures)
5. One thing that's easy to get wrong and how to avoid it

Write production code, not tutorial code. Handle edge cases. 
Include error messages that help debug issues.

Audit this code for security vulnerabilities.

Code:
[PASTE CODE]

Context: [WHAT THIS CODE DOES AND WHERE IT RUNS]
Language: [LANGUAGE]
Threat model: [WHO MIGHT ATTACK THIS — external users, internal, etc.]

For each vulnerability found:
1. Severity (Critical / High / Medium / Low)
2. What the vulnerability is (CWE reference if applicable)
3. Exact line(s) affected
4. How an attacker would exploit it
5. The fix (with corrected code)
6. How to test that the fix works

Also check for:
- Input validation gaps
- Authentication/authorization bypasses
- Injection vulnerabilities (SQL, XSS, command)
- Secrets or sensitive data exposure
- Race conditions or TOCTOU issues

I have this code that works but is getting messy. Suggest the right 
design pattern(s) to improve it.

Code:
[PASTE CODE]

Problems I'm experiencing:
- [e.g., "adding new payment methods requires changing 5 files"]
- [e.g., "testing is nearly impossible because of tight coupling"]
- [e.g., "the same logic is duplicated in 3 places"]

For each suggested pattern:
1. Which pattern and why it fits this specific problem
2. Before/after code comparison
3. What it makes easier going forward
4. What it makes harder (tradeoff)
5. When this pattern would be WRONG to use

Don't suggest patterns for the sake of patterns. Only suggest 
changes that solve my actual problems.

Write a robust API integration with [SERVICE/API].

API: [API NAME AND DOCUMENTATION URL]
Language: [LANGUAGE]
Use case: [WHAT I'M BUILDING]

Requirements:
- Authentication handling
- Rate limiting (respect the API's limits)
- Retry logic with exponential backoff
- Error handling (distinguish between retryable and fatal errors)
- Response parsing and validation
- Logging (request/response for debugging, no secrets in logs)

Write a clean, reusable client class/module. Include:
- Usage example
- How to handle the 3 most common error scenarios
- Suggested tests (what to mock, what to test)

This database query is slow. Optimize it.

Query:
[PASTE SQL OR QUERY]

Table schema:
[PASTE RELEVANT TABLE DEFINITIONS]

Current performance: [EXECUTION TIME, ROWS SCANNED]
Data volume: [TABLE SIZES]
Database: [PostgreSQL / MySQL / MongoDB / etc.]

Analysis:
1. Explain the query execution plan (or what it likely is)
2. Identify why it's slow (missing indexes, full scans, joins, subqueries)
3. Propose optimizations:
   a. Index recommendations (with CREATE INDEX statements)
   b. Query rewrites
   c. Schema changes (if needed)
4. Estimated improvement for each change
5. Any tradeoffs (write performance, storage, maintenance)

Write a technical blog post about [TOPIC].

Audience: [DEVELOPERS / DATA SCIENTISTS / ENGINEERS]
Their experience level: [BEGINNER / INTERMEDIATE / ADVANCED]
Length: 1,500-2,000 words

Structure:
1. Hook: a specific problem the reader has encountered
2. Background: just enough theory (don't over-explain basics the 
   audience already knows)
3. Implementation: actual code with explanations
4. Results: what this achieves (benchmarks, screenshots, output)
5. Gotchas: 3 things that tripped you up
6. Conclusion: when to use this, when not to

Every code example must be complete and runnable. No pseudocode 
in a technical blog post.

Summarize this research paper for a practitioner audience.

Paper:
[PASTE ABSTRACT, KEY SECTIONS, OR FULL TEXT]

Provide:
1. One-sentence summary (what they found)
2. Why it matters for practitioners (not other researchers)
3. Methodology in plain English (3-4 sentences max)
4. Key findings (numbered list)
5. Limitations the authors acknowledge
6. Limitations the authors DON'T mention (your analysis)
7. What this means for [MY FIELD/APPLICATION]
8. Should I read the full paper? (honest recommendation)

Write documentation for this system.

System description:
[PASTE CODE, ARCHITECTURE DETAILS, OR EXPLAIN THE SYSTEM]

Documentation should cover:
1. Overview: what this system does in 3 sentences
2. Architecture: how the pieces fit together (describe a diagram)
3. Getting started: step-by-step from zero to working setup
4. Core concepts: the 3-5 ideas someone needs to understand
5. API reference: every public function/endpoint with examples
6. Configuration: all options with defaults and what each controls
7. Troubleshooting: top 5 issues and how to fix them
8. Contributing: how to add to or modify this system

Write for a developer who is smart but has never seen this codebase.

Write a detailed comparison of [THING A] vs [THING B].

Context: [WHY SOMEONE WOULD BE CHOOSING BETWEEN THESE]
Audience: [WHO'S READING]
Length: 1,500-2,000 words

Structure:
- Introduction: when this choice matters (skip generic intros)
- Quick comparison table (features, pricing, strengths — scannable)
- Deep dive on 5-6 key differentiators
- Use cases: "Choose A when... Choose B when..."
- Deal-breakers for each
- The verdict (actually pick one for common scenarios)

Be opinionated. "It depends" is only acceptable if you then 
specify exactly what it depends on.

Write a technical proposal for [PROJECT/CHANGE].

Context: [WHY THIS IS BEING PROPOSED]
Audience: [WHO APPROVES THIS — technical leads, executives, etc.]

Structure:
1. Executive summary (one paragraph — problem, solution, impact)
2. Problem statement (specific, measurable)
3. Proposed solution (technical approach)
4. Alternatives considered (why they were rejected)
5. Implementation plan (phases, timeline, milestones)
6. Resource requirements (people, tools, infrastructure)
7. Risk assessment (what could go wrong + mitigation)
8. Success criteria (measurable outcomes)
9. Recommendation (clear ask)

Write to persuade, not just inform. The reader should finish this 
thinking "we need to do this."

Transform these raw git commits or release notes into user-facing 
release documentation.

Raw input:
[PASTE COMMIT MESSAGES, PR DESCRIPTIONS, OR JIRA TICKETS]

Create:
1. Version headline (what this release is about in one sentence)
2. New Features (user-facing language, not developer language)
3. Improvements (performance, UX, stability)
4. Bug Fixes (what was broken, now it works)
5. Breaking Changes (if any — with migration instructions)
6. What's Next (one-sentence teaser)

Translate developer language into user benefit. "Refactored auth 
middleware" → "Improved login reliability and speed."

I'm researching [TOPIC]. Provide a structured knowledge base.

Focus: [SPECIFIC ASPECT OR QUESTION]
My level: [BEGINNER / INFORMED / EXPERT]
Application: [HOW I'LL USE THIS KNOWLEDGE]

Deliver:
1. Core concepts (definitions and relationships)
2. Historical development (key milestones, 5-10 items)
3. Current state of the art
4. Open questions and active research areas
5. Key frameworks or models used in this field
6. Common misconceptions (what most people get wrong)
7. Recommended reading (5 foundational + 5 cutting edge)
8. Connections to adjacent fields

Flag any areas where your training data might be outdated.

Help me design a systematic approach to research [QUESTION].

Research question: [SPECIFIC QUESTION]
Purpose: [ACADEMIC PAPER / BUSINESS DECISION / PERSONAL LEARNING]
Time available: [HOURS/DAYS]

Create:
1. Search strategy (databases, keywords, inclusion/exclusion criteria)
2. Quality assessment framework (how to evaluate sources)
3. Data extraction template (what to pull from each source)
4. Synthesis method (how to combine findings)
5. Bias assessment (what biases to watch for)
6. Reporting structure (outline for the final output)
7. Known limitations of this approach

This should be rigorous enough for [ACADEMIC / PROFESSIONAL / PERSONAL] use.

Analyze [TOPIC] from first principles. Don't tell me what experts say — 
reason through it from the ground up.

Topic: [WHAT YOU WANT ANALYZED]
Current assumption I want challenged: [WHAT "EVERYONE KNOWS"]

Steps:
1. What are the fundamental truths (things that are definitely true)?
2. What assumptions are people making on top of those truths?
3. Which assumptions are unsupported or weakly supported?
4. If we removed those assumptions, what conclusions would we reach?
5. How does this first-principles view differ from conventional wisdom?
6. What would you build or decide if you only had the fundamentals?

I want genuine reasoning, not a reformatted Wikipedia summary.

Design a research methodology for studying [QUESTION].

Type of research: [QUANTITATIVE / QUALITATIVE / MIXED]
Population: [WHO/WHAT YOU'RE STUDYING]
Resources: [BUDGET, TIME, TEAM SIZE]
Constraints: [ETHICAL, PRACTICAL, DATA ACCESS]

Provide:
1. Research design (experimental, observational, survey, etc.)
2. Sampling strategy (how to select participants/data)
3. Data collection instruments (what tools/surveys/measures)
4. Variables and operationalization
5. Analysis plan (which statistical tests or qualitative methods)
6. Validity threats and how to address them
7. Sample size justification
8. Timeline with milestones

Flag any methodological weaknesses and how to mitigate them.

I need to evaluate [TECHNOLOGY CATEGORY] options for [USE CASE].

Options to compare:
1. [OPTION A]
2. [OPTION B]
3. [OPTION C]
4. [OPTION D — if applicable]

Evaluation criteria:
- [CRITERION 1 — e.g., performance]
- [CRITERION 2 — e.g., cost]
- [CRITERION 3 — e.g., community/ecosystem]
- [CRITERION 4 — e.g., learning curve]
- [CRITERION 5 — e.g., scalability]

For each option:
- Score 1-10 on each criterion with justification
- Best use case scenario
- Worst use case scenario
- Hidden costs or gotchas
- Community health and trajectory

Provide a weighted score matrix and a clear recommendation for [MY CONTEXT].

Based on what you know about [FIELD], project likely developments 
over the next [1-5] years.

Current state:
[DESCRIBE WHERE THINGS ARE NOW]

Historical trajectory:
[KEY DEVELOPMENTS OVER THE LAST 3-5 YEARS]

Analysis:
1. Trends that are likely to continue (high confidence)
2. Inflection points that could change direction
3. Wild cards (low probability but high impact events)
4. What most predictions about this field get wrong
5. Contrarian prediction (something you believe that most don't)
6. What signals to watch that would confirm or invalidate these projections

Be honest about confidence levels. Distinguish between extrapolation 
and speculation.

Perform a cost-benefit analysis for [DECISION].

Proposed action: [WHAT YOU'RE CONSIDERING]
Alternative: [STATUS QUO OR OTHER OPTION]
Time horizon: [HOW FAR OUT TO ANALYZE]

Analyze:
1. Direct costs (itemized)
2. Indirect costs (opportunity costs, disruption, transition)
3. Direct benefits (quantified where possible)
4. Indirect benefits (harder to measure but real)
5. Risk-adjusted net benefit
6. Break-even point
7. Sensitivity analysis (what if costs are 20% higher? Benefits 30% lower?)
8. Non-financial factors (morale, reputation, strategic positioning)

Present a clear recommendation with a confidence level.

Analyze this business process and identify improvements.

Current process:
[DESCRIBE STEP BY STEP]

Pain points I've noticed:
- [ISSUE 1]
- [ISSUE 2]
- [ISSUE 3]

Constraints: [BUDGET, TOOLS, TEAM SKILL LEVEL]

Deliver:
1. Process map (describe the current flow)
2. Bottleneck analysis (where time/value is lost)
3. Root causes for each pain point
4. Quick wins (implement this week, immediate impact)
5. Medium-term improvements (implement this month)
6. Long-term transformation (if you could redesign from scratch)
7. Expected impact of each improvement (time saved, error reduction, etc.)
8. Implementation priority matrix

Estimate the market size for [PRODUCT/SERVICE].

Product: [DESCRIPTION]
Geography: [MARKET — US, global, etc.]
Target customer: [WHO]

Calculate using both approaches:
1. Top-down (total market → addressable segments → your share)
2. Bottom-up (customers × price × frequency)

For each approach:
- State every assumption
- Show the math step by step
- Provide ranges (conservative, realistic, optimistic)

Then:
- Compare the two estimates and explain any discrepancy
- Which estimate do you trust more and why?
- What would you need to research to improve accuracy?

Write a business case for [INITIATIVE].

Context: [WHY THIS IS BEING PROPOSED]
Sponsor: [WHO APPROVES AND FUNDS THIS]
Budget request: [AMOUNT]

Structure:
1. Executive Summary (one page max)
2. Problem Statement (what's broken, what it costs)
3. Proposed Solution (what you'll do)
4. Options Considered (why alternatives were rejected)
5. Financial Analysis (costs, benefits, ROI, payback period)
6. Implementation Plan (phases, timeline, resources)
7. Risk Assessment (probability × impact matrix)
8. Success Metrics (how we'll know it worked)
9. Recommendation (clear, confident ask)

Write to convince a skeptical executive who has seen too many 
business cases that overpromise.

Build a unit economics model for [BUSINESS].

Business type: [SAAS / E-COMMERCE / MARKETPLACE / SERVICE]
Price point: [AMOUNT]
Customer type: [B2B / B2C / ENTERPRISE]

Calculate:
1. Customer Acquisition Cost (CAC) — break down by channel
2. Lifetime Value (LTV) — with churn assumptions stated
3. LTV:CAC ratio (and what it should be for this business type)
4. Payback period
5. Gross margin per unit/customer
6. Contribution margin
7. Break-even customer count

Then:
- Which metric is the biggest lever for improvement?
- What happens to unit economics at 2x, 5x, 10x scale?
- Where does this model break?

Write a monthly investor update for [COMPANY].

Key metrics this month:
- Revenue: [AMOUNT] (vs last month: [AMOUNT])
- Users/Customers: [NUMBER] (growth: [%])
- Burn rate: [AMOUNT]
- Runway: [MONTHS]
- Key milestone: [WHAT HAPPENED]

Also include:
- Biggest challenge: [WHAT'S HARD]
- Biggest win: [WHAT WENT WELL]
- Ask: [WHAT YOU NEED FROM INVESTORS]

Tone: honest, transparent, confident but not delusional. Investors 
respect founders who share bad news early and clearly.

Structure: 2-minute read max. Bold the numbers. Lead with metrics.

Design a logically consistent [MAGIC SYSTEM / TECHNOLOGY / SOCIAL STRUCTURE] 
for a fiction project.

Genre: [FANTASY / SCI-FI / ALTERNATE HISTORY]
Core concept: [ONE-SENTENCE PREMISE]
Tone: [HARD SCIENCE / SOFT MAGIC / REALISTIC / MYTHIC]

Build:
1. Fundamental rules (what's possible and what isn't — and WHY)
2. Costs and limitations (every power has a price)
3. How it interacts with society (economics, politics, daily life)
4. Edge cases (what happens at the extremes of the rules)
5. Internal consistency check (do the rules create any contradictions?)
6. Three story-ready conflicts that arise naturally from this system
7. How a smart character would try to exploit the system

Use formal logic where possible. Flag any hand-wavy parts so I 
can decide whether to accept or revise them.

Create a [TYPE — logic, math, word, coding, escape room] puzzle.

Difficulty: [EASY / MEDIUM / HARD / EXPERT]
Audience: [WHO WILL SOLVE IT]
Context: [WHERE THIS WILL BE USED — game, interview, education, fun]

Provide:
1. The puzzle as presented to the solver
2. Hints (3 levels — subtle, moderate, almost-the-answer)
3. Complete solution with step-by-step explanation
4. Why this puzzle is satisfying (what makes the "aha" moment work)
5. One variation that changes the difficulty level

The puzzle should be solvable through reasoning, not trivia 
knowledge. No trick questions.

Design a course on [SUBJECT].

Students: [WHO — background, motivation, skill level]
Format: [SELF-PACED / LIVE / HYBRID]
Duration: [TOTAL HOURS]
Goal: [WHAT STUDENTS CAN DO AFTER COMPLETING]

Create:
1. Course description (what they'll learn and why it matters)
2. Prerequisites (what they need before starting)
3. Module breakdown (5-8 modules):
   - Title and learning objectives
   - Key concepts covered
   - Practical exercise for each module
   - Assessment (how they prove they learned it)
4. Capstone project (ties everything together)
5. Resources for each module (readings, tools, references)
6. Common misconceptions students develop (and how to prevent them)

Prepare me for a debate on [TOPIC].

My position: [WHAT I'M ARGUING]
Opposing position: [WHAT THEY'LL ARGUE]
Format: [FORMAL DEBATE / PANEL / DISCUSSION / WRITTEN]
Audience: [WHO'S WATCHING/READING]

Prepare:
1. Opening statement (60 seconds, sets my frame)
2. Core arguments (3, ranked by strength)
3. Evidence for each argument (specific, citable)
4. Anticipated counterarguments (5 most likely)
5. Rebuttals for each counterargument
6. Traps to avoid (questions designed to make me look bad)
7. Questions I should ask them (that expose weakness in their position)
8. Closing statement (30 seconds, memorable)

Steel-man the opposing view — my preparation should assume I'm 
facing the best version of their argument, not a strawman.

Walk me through this thought experiment with rigorous reasoning.

Scenario: [DESCRIBE THE HYPOTHETICAL]
Question: [WHAT YOU WANT TO EXPLORE]

Approach:
1. Clarify the premises (what are we assuming is true?)
2. Identify the key variables and how they interact
3. Trace the logical consequences step by step
4. Identify where intuition diverges from logic
5. Consider second and third-order effects
6. What analogies from reality illuminate this scenario?
7. What does this thought experiment reveal about [THE UNDERLYING QUESTION]?

Don't rush to a conclusion. The value is in the reasoning, not the answer.

Write an interactive fiction scene with meaningful choices.

Genre: [GENRE]
Setting: [WHERE AND WHEN]
Character: [WHO THE READER IS]
Situation: [WHAT'S HAPPENING]
Tone: [TENSE / FUNNY / MYSTERIOUS / REFLECTIVE]

Structure:
1. Scene setup (200-300 words — immersive, sensory)
2. The decision point (clearly presented stakes)
3. Three choices (each should feel genuinely different, not obviously 
   right/wrong)
4. Outcome for each choice (150-200 words each)
5. How each outcome changes what happens next

Each choice should have trade-offs. The "right" answer depends on 
what the character values, not what's objectively optimal.