How To Get Your Next Interview Calls In Next 7 Days (USING AI)

Bonus: Step-by-Step Plan To Get Ahead of 99% Of Software Engineers with AI Prompts

What if you could learn new programming skills faster, build projects with ease, and ace job interviews—all with a smart assistant by your side 24/7. This is not science fiction; it’s the reality unfolding in today’s tech world.

In fact, 84% of developers are now using or planning to use AI tools in their development process.

Why such a surge?

Because those who embrace AI are reaping big rewards. A recent study by Microsoft found that AI helps developers complete tasks about 55% faster on average. That means what used to take a week of coding might now take just a few days.

If you’re a beginner software developer, leveraging AI isn’t just a cool trick—it can be a game-changer for your learning and career growth.

However, simply having an AI tool doesn’t automatically make you a better developer.

One report noted that while 75% of engineers use AI tools, many teams see no measurable performance gains. The key is knowing how to use AI effectively.

In this guide, we’ll share exactly that.

We’ll explore how AI can become your personal coding mentor, pair programmer, and career coach guiding you from learning the basics all the way to landing a job.

Every section below packs actionable tips and example prompts you can start using today to get ahead. Let’s dive in!

The exact way to use AI so it actually teaches you

Learning to code can feel like drinking from a firehose—there’s so much to absorb.

This is where AI shines as a personal tutor. You can ask an AI-powered assistant (like ChatGPT, Perplexity or Gemini) to explain complex programming concepts in simple terms, provide examples, and even quiz you. The result? You grasp new topics faster and with less frustration.

In fact, 62% of developers say AI tools help them learn faster. Even those just learning to code have caught on – roughly 80% of coding beginners are already using or planning to use AI to boost their learning. AI can break down a tough concept step by step or give you analogies that make it click. It’s like having a patient teacher on call at any hour.

Here’s the prompts to learn faster:

Don’t just passively read tutorials—actively engage with an AI.

For example, if you’re confused about how recursion works or how a Python loop operates, you can prompt the AI to walk you through it. You can also ask for learning roadmaps (for instance, “How do I go from zero to hero in web development?”) and even get the AI to generate practice exercises.

The key is to treat the AI as an interactive learning partner.

Below is a premium prompt that you can try right now to turbo-charge your learning:

Project:
[PROJECT NAME] using [TECH]

Objective:
I want to create a [PROJECT NAME] using [TECH], but I am unsure how to structure it. I want you to guide me like a professional [TECH] developer.

Your Role:
Act as a professional [TECH] developer and help me approach this project the way an expert would.

How I Want the Guidance:

1. Pseudocode & Structure First – I don’t want the actual code immediately. Instead, I need a structured approach and a clear breakdown of sections and elements.
2. Thinking Process Explanation – Explain how a professional would plan and structure the page before writing any code.
3. Step-by-Step Tutorial Format – Guide me through the process in a structured, tutorial-like manner.
4. Conversational Assistance – Give me 1-2 tasks at a time. Once I complete them, I’ll return for the next step.
5. Code on Request – If I need actual code, I will explicitly ask you for it. Otherwise, just provide the structural approach.

Now, guide me step by step as a professional would.
What’s the first thing I should do?

By using prompts like these, you’ll not only get answers but also learn how to learn more effectively. The AI can point you to important topics, explain the “why” behind solutions, and reinforce your knowledge through Q&A. Over time, this constant guidance can significantly shorten the time it takes to go from novice to competent coder.

You can check more such prompts here: Prompts!

Debug in Seconds, Not Hours—with this AI Prompt

Once you have the basics down, the next challenge is implementing them:

• Writing code.

• Building Projects.

• Solving Real Problems.

This is where AI becomes your pair programmer, sitting right next to you (in a virtual sense).

AI coding assistants like ChatGPT, Perplexity or Gemini can generate snippets of code, suggest improvements, and help debug errors. The impact on your productivity can be dramatic.

Developers using ChatGPT, Perplexity or Gemini, for example, often see code tasks completed much faster than usual.

One study observed code getting merged around 50% faster when AI assistance was involved. Another team saw a 59% decrease in time spent searching the web for solutions once they started using AI for coding help.

Think about the time you save when you don’t have to do back-and-forth through dozens of Stack Overflow posts because the answer pops up instantly with an AI assistant!

Here’s your ultimate prompt:

Think of the AI as an ever-ready coding buddy.

Starting a project? Ask it to create a boilerplate or outline for your code.

Stuck on a bug? Show the AI your error message or a problematic code snippet.

Need to refactor or optimize something? The AI can propose cleaner, more efficient code.

It can often pinpoint the issue or suggest a fix and while it accelerates your work, studies show this doesn’t mean lower quality—in controlled trials, teams using AI did not sacrifice code quality for speed. You still review and test your code, of course, but the heavy lifting and grunt work are eased by AI assistance.

Use the below AI prompt into your development workflow to fix real issues:

Project/Feature: [name or brief]
Tech Stack: [language/framework + versions]
OS/Env/Package Manager: [e.g., macOS 14, Node 20, pnpm]
Repo/Path (optional): [link or local path]

Objective:
I want to diagnose and fix a real issue (or ship a small feature) in [TECH]. Guide me like a professional [TECH] developer would—fast, precise, and verifiable.

Your Role:
Act as my AI pair programmer. Prioritize clarity, speed, and correctness.

How I Want the Guidance:
1. Structure First (no code yet):
Give me a brief diagnosis hypothesis (2–4 bullets).
Propose 1–2 surgical steps to test the hypothesis.
List exact commands (copy/paste), files to inspect, and where.
2. Professional Planning (concise):
Explain how an expert would approach this (high-level rationale, not step-by-step internals).
3. Tutorial Flow (turn-based):
Give me only 1–2 tasks per turn. Wait for my results before moving on.
4. Code on Request:
Only provide code/diffs when I say: “Code please.”
5. Verification First:
For every task, include how to verify (command, expected output, test).
6. Fail-Forward Rule:
If results differ, tell me exactly what to capture next (logs, stack trace, file snippet) and the next best probe.

Context I’ll Provide (prompt me for what’s missing):
1. Error message / stack trace: [paste]
2. Relevant file snippet(s): [paste path + code]
3. What I already tried: [bullets]
4. Constraints (time, libraries, style): [notes]
5. Interaction Format (each turn you send):

Hypothesis: (2–4 bullets)
1. Why this next step: (1–2 bullets, concise)
2. Tasks (1–2 only): numbered, reproducible
3. Commands / Paths: fenced block
4. Verify: exact check + expected signal
5. If not resolved: what to collect next

Start Now — What’s First?
Ask me for the minimum info you need (logs, file paths, versions), then give me the first 1–2 actions.

By using an AI pair debugger, you’ll not only write code faster but also learn better ways to code.

The AI might introduce you to new functions or libraries, show you best practices, and help you avoid common pitfalls. It’s like having an experienced developer reviewing every line you write. Over time, you’ll notice your own coding skills improving by imitation and practice.

And whenever you hit a roadblock, you have a partner to brainstorm solutions with—available 24/7.

Again, you can check more such prompts here: Prompts!

A 7 Day Step-by-Step AI Plan For Your Job Hunt

The ultimate goal of all this learning and building is to land that software development role.

Here too, AI can give you a serious edge by making AI as your career coach and interview partner.

You can practice coding interviews, get help polishing your resume, and even simulate common interview questions with an AI. This kind of preparation can dramatically boost your confidence and performance when it’s time to talk to real hiring managers.

Here’s how to use this 7 day plan:

• Time: 60–90 min per weekday, 2–3 hours on the weekend.

• Tools: Any LLM (ChatGPT/Perplexity/Gemini), LinkedIn, GitHub, a resume editor, Loom/ScreenRec, Notion/Google Sheets.

• Rule: Never invent experience. Use AI to clarify, tailor, and present your real work better.

Day 1: Set up the system and target roles

Goal: Build your funnel and calibrate exactly what “fit” looks like.

Deliverables:

• A tracker (Notion/Sheet).

• One master resume draft.

• Keyword map for 2 target roles.

Steps

1. Create a tracker with columns: Company | Role | Job Description (JD) link | Keywords used | Resume file | Cover letter file | Applied date | Status | Last touch | Next action.

2. Pick 2 roles (e.g., Junior Software Engineer, Frontend Developer). Gather 3–5 JDs for each.

Prompts

• Extract the hiring signal (paste 3–5 JDs):

You are my ATS and hiring-signal analyst. 
From these job descriptions, extract and group the top 25 unique keywords into:
- Must-have hard skills
- Nice-to-have hard skills
- Tools/frameworks
- Soft skills and behaviors
Return as a compact table with frequency counts. [PASTE JDs]

• Build a baseline resume from raw notes:

You are my resume editor for [Designation] role. 
Turn these raw notes into a one-page resume with metric-leaning bullets, past-tense for past roles, present-tense for current, and no fluff. 
Output plain text I can paste. 

[PASTE NOTES/EXPERIENCE]

• Close keyword gaps for ATS:

Compare this resume to the Must-have list below. Identify missing or weakly expressed skills and suggest honest wording that reflects entry-level exposure (courses, small projects). Do not fabricate. 

[PASTE RESUME] 

[PASTE MUST-HAVES TABLE]

Day 2: Ship a tiny proof-of-work project (aligned with your JD)

Goal: A small, JD-relevant project with a README and 60–90s demo.

Deliverables:

• Repo with README, screenshots.

• Loom demo link in README.

Steps

1. Choose the smallest feature set that mirrors the JDs.

2. Build, document, record quick demo.

Prompts

• Scope a minimal, JD-aligned app:

Act as a staff engineer. 
From this JD, design the smallest possible project that proves fit in 6–8 hours max. Include features, acceptance criteria, a stretch goal, and a simple test plan. 

[PASTE JD]

• Scaffold and reasoning notes:

Generate a step-by-step build plan for the above scope in [STACK]. Include folder structure, commands, and a brief “why” for key choices (db, auth, API). 
Return as a checklist I can follow.

• README and demo script:

Create a compelling README with sections: 
Problem, Solution, Key decisions, How to run, Tests, Screenshots, Next steps. 
Then write a 60–90 second narration script for a Loom demo that highlights outcomes before tech.

Day 3: Tailor resume and cover notes per JD

Goal: Produce tailored PDFs for 2–3 roles today.

Deliverables:

• 2–3 tailored resumes and short cover notes.

• ATS cross-check.

Steps

1. For each JD: tear down → map to bullets → ATS pass.

2. Export a unique PDF per application.

Prompts

• JD → checklist of what to mirror:

Turn this JD into a requirements checklist. Label each as Core or Secondary. 

[PASTE JD]

• Rewrite bullets to mirror the JD honestly:

Rewrite 6 resume bullets to align with the Core items. Use my real experience only. Add small measurable outcomes where true. One line each, strong verbs first.
 
[PASTE CURRENT RESUME OR MASTER PROFILE] 

[PASTE CHECKLIST]

• ATS sanity scan:

Compare the tailored resume to the JD. List critical keywords missing or underemphasized. Propose natural phrasing that fits my background without exaggeration. 

[PASTE TAILORED RESUME] 

[PASTE JD]

• Short cover note (5 lines max):

Write a concise cover email for this JD. Reference 2 JD specifics, link my demo, and state availability. Tone: plain, confident, no clichés. 

[PASTE JD] 

[PASTE PROJECT/LOOM LINK]

Day 4: Precision outreach for referrals

Goal: Start 3–6 warm conversations at target companies.

Deliverables:

• Personalized connection notes.

• One short DM per target.

• A structured follow-up.

Targets: 1 engineer, 1 team lead, 1 recruiter per company.

Prompts

• Harvest personalization nuggets:

From this LinkedIn profile and their recent post text, extract 2 specific details I can reference (shared tech, talks, repos, articles). Return as bullets. 

[PASTE PROFILE TEXT + 1–2 RECENT POSTS]

• Connection request (140 chars):

Write a 140-character connect note referencing the above nuggets. Goal: earn a brief chat about their team’s workflow. No job ask yet. 

[PASTE NUGGETS]

• First DM (3–4 lines):

Draft a 3–4 line message: acknowledge their work (use nugget), share a 60–90s demo link relevant to their stack, and ask for a 12-minute chat about how juniors add value on their team. No resume attachment.

• Post-chat referral ask:

After a positive 10-minute chat, write a polite message asking if my background fits [ROLE]. Include 1–2 specific JD matches and link to the demo again. Tone: grateful, non-pushy.

Day 5: Interview prep sprint (coding, behavioral, design)

Goal: Practice like it’s real. Capture feedback. Iterate.

Deliverables:

• One timed coding problem with review.

• Two STAR stories refined.

• One junior-level design drill.

Prompts

• Timed coding rehearsal:

Give me one medium [LANGUAGE] problem. Timebox to 25 minutes. After I submit, score me on correctness, readability, complexity, and communication. Provide an optimal solution and 2 follow-ups that test edge cases.

• Behavioral STAR bank from my history:

Create 6 STAR stories from these experiences for themes: Ownership, Debugging under pressure, Conflict, Learning fast, Ambiguity, Teamwork. Keep each to 5 tight bullet lines. 

[PASTE EXPERIENCE HIGHLIGHTS]

• Junior system design drill:

Run a 10-minute junior system design interview (pick from: URL shortener, rate limiter, notes app). Drive back-and-forth. Force me to state assumptions, data model, APIs, basic scaling, and a single tradeoff. Summarize my gaps and give a one-page improvement plan.

Day 6: Portfolio and profile polish

Goal: Make trust easy. Show proof first, tech second.

Deliverables:

• GitHub: 2–3 pinned repos with clean READMEs and demo links.

• LinkedIn: headline, About, and Experience updated.

• Resume header with GitHub + Loom.

Prompts

• GitHub README tightening:

Tighten this README to be recruiter-friendly. First 5 lines must show: Problem, Outcome, Tech, Live/demo link, How to run. Keep the rest scannable. 

[PASTE README]

• LinkedIn headline (5 options):

Rewrite my LinkedIn headline for a junior SWE role: Role + core stack + outcome proof (demo). 220 chars max. Provide 5 distinct options. 

[PASTE CURRENT HEADLINE/STACK/DEMO LINK]

• LinkedIn About (3 lines):

Write a 3-line About section focused on outcomes and proof. Mirror phrases used in these target JDs to increase search relevance. 

[PASTE 2–3 JD SNIPPETS]

• Experience bullets alignment:

Convert these experience bullets to be JD-relevant, one line each, outcome-first. Avoid buzzwords. 

[PASTE BULLETS]

Day 7: Apply smart, follow up, and review the funnel

Goal: Send tailored applications, follow up, analyze what worked, plan Week 2.

Deliverables:

• 5–7 tailored applications sent.

• Follow-ups scheduled in tracker.

• Funnel analysis and next-week experiments.

Prompts

• Concise cover note per application:

Draft a 5-line cover letter for this JD. Reference 2 specifics, link my demo, and name one next step I’m ready for (e.g., a 20-minute technical screen). 

[PASTE JD] 

[PASTE PROJECT/LOOM LINK]

• Post-apply LinkedIn nudge to recruiter:

Write a 3-line LinkedIn message to the company recruiter: mention the role, one JD match, and the 60–90s demo link. Tone: respectful, brief, confident.

• Funnel analysis from my tracker:

Analyze this week’s tracker data. Identify where the funnel leaks (views→replies, replies→screens). Recommend 3 experiments for next week with clear hypotheses and how to measure success. 

[PASTE TABLE OR SUMMARY]

• Thank-you note template:

Draft a concise thank-you email that references two specific topics we discussed in the interview and includes one follow-up artifact (link to improved README, small fix, or brief doc).

Daily 60-minute Workflow (Mon–Fri)

• 15 min: JD teardown → tailored bullets.

• 15 min: one targeted outreach.

• 20 min: one practice rep (coding or behavioral).

• 10 min: update tracker and schedule tomorrow’s “one thing.”

Success benchmarks and when to adjust

• Tailored apps/week: 10–15.

• Warm conversations/week: 5–8.

• Target conversions:

  • JD → phone screen: ≥ 15%

  • Phone screen → onsite: ≥ 30%

  • Onsite → offer: ≥ 20%

Prompt to diagnose slowdowns:

Given these weekly metrics, find the bottleneck and propose 3 targeted experiments. 
Label each by expected impact and effort, and tell me exactly what to change in resume, outreach, or project proof. 

[PASTE METRICS]

Take care of below things

• Do not fabricate experience, titles, or results.

• AI drafts; you verify and personalize.

• Keep artifacts consistent across resume, LinkedIn, GitHub, and how you speak in interviews.

Run this 7-day sprint again next week.

Improve one lever per loop. That’s how you compound into interviews and offers.

So that’s it for this time.

P.S. If this changed how you think about AI and software development, share it with one developer friend who needs to see this. The compound effect of AI adoption is real, but it only works if you start now.

If you have any doubt then please reply to this email, comment it below or you can directly DM me your doubt at my LinkedIn. Thanks for reading till the end and would love to hear something from your side now.

Okay then, bye! 👋🏻

Manas 🥂

Founder, Codexai

---

P.P.S. I help developers, creators and early stage founders find clarity, direction, and momentum with a 60 min consulting call.

Explore all sessions here: Book Your Breakthrough, NOW!!!