Aakash GuptaShe Gets 5 Job Offers a Week on LinkedIn with Claude Code
CHAPTERS
- 0:00 – 3:49
Basia’s LinkedIn flywheel: five inbound offers a week
Basia explains how LinkedIn directly drove her to leave her full-time job, showing the kind of inbound DMs she receives. Aakash frames the episode as a complete playbook for PMs and creators to turn LinkedIn into an opportunity engine using Claude/Claude Code.
- •Inbound offers and role-creation outreach via LinkedIn DMs
- •0→50K (later 70K) followers as proof the system scales
- •Episode promise: profile + content + networking, plus Claude tooling
- •Positioning LinkedIn as a primary channel for job search and credibility
- 3:49 – 4:25
The three-part system: profile as landing page, content as passive networking, active networking
Basia outlines the full system she teaches: optimize your profile, publish content to attract the right people, and proactively network via comments and DMs. The key reframe is that a LinkedIn profile is not a resume—it’s a conversion-focused landing page.
- •Three components: profile, content, active networking
- •Profile should be treated like a landing page, not an online resume
- •Content creates discoverability; active networking creates direct access
- •Roadmap set for the rest of the episode
- 4:25 – 7:01
How hiring managers and recruiters actually find you (and why tagline is everything)
Basia breaks down three distinct discovery paths—content discovery, active outreach to hiring teams, and recruiter keyword search. In all three, your photo + headline/tagline are the first ‘above the fold’ conversion lever before anyone reads your experience.
- •Three discovery journeys: content → profile, active networking → profile, recruiter Boolean search → profile
- •Common denominator: tagline + profile must convert quickly
- •Profile needs both persuasion (humans) and keyword matching (search tools)
- •Choose a coherent job target so keywords can align
- 7:01 – 10:16
Live demo: mining job descriptions for high-overlap keywords with a Claude Code skill
Basia demonstrates a ‘JD keyword miner’ skill that ingests multiple job descriptions, checks keyword overlap, and outputs ranked terms and phrasing. The goal is to ensure the target roles share enough common requirements to justify a focused profile rewrite.
- •Use 5 similar job descriptions to keep keyword set coherent
- •Skill enforces a ‘focus check’ (e.g., stop if overlap is too low)
- •Outputs: keyword categories, repeated phrases, role expectations, gap flags
- •Target: ~75%+ keyword overlap to feel ‘made for the role’
- 10:16 – 13:27
Inside the JD Keyword Miner: simple markdown skill design + focus diagnosis
Aakash asks to see how the skill is built; Basia shows it’s a straightforward markdown-based workflow in VS Code. The key differentiator is the ‘diagnose focus’ step that prevents pursuing overly divergent roles.
- •Skills live as MD files and run inside Claude Code
- •Workflow: extract terms → normalize/rank → diagnose focus → output brief
- •Hard stop when role targets are too scattered
- •Keywords become the source of truth for rewriting the profile
- 13:27 – 21:57
The LinkedIn Profile Writer skill: turning keywords into a truthful, results-based narrative
Basia walks through her profile rewrite skill, which takes the keyword brief plus the current profile and then asks clarifying questions. The emphasis is on mapping keywords to real accomplishments and quantifiable outcomes—what you delivered, not what you owned.
- •Inputs: keyword brief, current profile, plus additional context if missing
- •‘Map keywords to truth’ to avoid hollow keyword stuffing
- •Profiles should be optimized for outcomes and measurable impact
- •Optional ‘edge pass’ to address and flip perceived weaknesses/red flags
- 21:57 – 32:43
Reviewing outputs: headline, banner, About hooks, Featured, and experience rewrites
They review Claude’s suggested headline options, banner copy, and multiple About-section formats, discussing what to edit manually. Basia emphasizes skimmability, strong first three lines, and showing proof (case studies/demos) in Featured while keeping experience quantified and aligned to the target roles.
- •Headline/tagline must be targeted; shorten and prioritize signal
- •Banner is ‘hero section’—sell value even without keywords
- •About section: first 3 lines must hook; make it easy to skim
- •Featured: use one-page case studies + demos that show product thinking
- •Experience: quantify results; align bullets to JD keyword intent
- 32:43 – 35:17
Profile polish extras: skills loading, Premium considerations, and clean URLs
Basia covers tactical LinkedIn settings that improve discoverability: skills sections, endorsements, and recruiter filtering behavior. They also discuss when LinkedIn Premium is worth it and small polish items like Open Profile and a clean custom URL.
- •Add skills in multiple places (About, role skills, Skills section)
- •Recruiters filter by skills—load relevant keywords heavily in Skills
- •Avoid bloating individual job entries with dozens of skills
- •Premium benefits: InMail, Open Profile, job-search perks (use during active search)
- •Custom URL and small settings improve professionalism and access
- 35:17 – 38:05
When content fails: Basia’s first six months, feedback sting, and why PMs can learn it
Basia tells the story of posting for months with little traction and receiving blunt feedback that her posts felt spammy. Instead of quitting, she invested in learning from people who had cracked the system, leading to a sharp growth inflection.
- •Early low engagement and discouragement are normal
- •Blunt feedback (‘spammy’) nearly made her quit
- •She ‘threw money at the problem’ to learn faster
- •Content creation is iterative and learnable like product management
- 38:05 – 42:11
ToFU vs MoFU vs BoFU: reach posts, authority posts, and what job seekers should prioritize
Basia teaches the funnel model for LinkedIn posts and why most people imbalance it. For job seekers, she recommends prioritizing authority (how I did it) while still mixing in reach posts (how to) for new exposure.
- •ToFU = reach/distribution; MoFU = authority/credibility; BoFU = leads (less relevant for job seekers)
- •Reach posts are shareable and generic; authority posts show your specific execution
- •Job seekers: aim ~3 posts/week, skew toward authority (e.g., 2 authority + 1 reach)
- •Hiring managers scan ‘Activity’ to judge how you think
- 42:11 – 57:37
Building an authority post live: research, templating viral structures, and iterating drafts
Basia demonstrates her workflow: find a proven post format, templatize it, then rewrite it with her own experience (e.g., vibe coding). She shows how Claude produces a first draft, and how she corrects misses (specific language, richer details) through targeted reprompting and human editing.
- •Use ‘user research’ on posts that already performed well
- •Templatize structure: hook → bridge/story → value/meat → mic drop → CTA/question
- •AI creates the first draft; humans refine hooks, specificity, and voice
- •Reprompt for missing keywords (e.g., ‘vibe coding’) and richer detail
- •Authority comes from real experiences + concrete lessons learned
- 57:37 – 1:01:56
Why this works best in Claude Code: the Story Bank as reusable context memory
Basia explains her Story Bank—an evolving repository of personal stories and details that Claude can pull from to write credible authority content. Claude Code enables a durable workflow where stories accumulate over time, rather than re-explaining context in every chat.
- •Story Bank stores life/work stories and details for content reuse
- •Claude can ‘grab’ relevant anecdotes per topic without re-briefing
- •Stories are added incrementally after posts via an ‘add to story bank’ step
- •Claude Code harness + files make the system persistent and scalable
- 1:01:56 – 1:09:20
Images and ethics: generating scroll-stopping visuals and drawing the inspiration line
Basia shows how she borrows visual concepts (with adaptation) to create compelling images, often generating them via ChatGPT while dictating prompts. They discuss what constitutes acceptable templating versus copying, and when to credit, ask permission, or do explicit content swaps.
- •Images are critical to ‘stop the scroll’ alongside the hook
- •Workflow: take inspiration → prompt a new analogous visual concept
- •Use voice dictation to speed up creative prompting
- •Credit/ask permission when reusing graphics; avoid word-for-word copying
- •Content swaps can be ethical when pre-agreed and mutually beneficial
- 1:09:20 – 1:15:39
Connecting Claude to LinkedIn via Apify: scraping posts, proxies, and performance signals
Basia explains there’s no official LinkedIn MCP, so she uses Apify actors and proxy-based scraping to collect post data without logging in. She then analyzes performance with metrics like ‘X Factor’ (post vs creator moving average) and similarity clustering using embeddings.
- •Apify provides third-party ‘actors’ for LinkedIn post scraping
- •Proxy approach reduces linkage to your account; no login needed
- •‘X Factor’ compares a post to creator’s 30-day moving average performance
- •Embeddings (text + image) enable similarity search and clustering
- •Use insights to find repeatable hooks, formats, and visuals
- 1:15:39 – 1:28:06
Active networking: finding hiring managers, commenting strategically, and DMing like a good citizen
Basia walks through a practical method to locate relevant people from a job post using company pages, filters, and keywords, then engage via thoughtful comments. The goal is to get noticed through notifications (where your tagline matters), then connect and request a short call after you’ve applied.
- •Start from job description: team name/location → company page → People search
- •Use role keywords (e.g., ‘developer platform’) to find peers and leaders
- •Comment with value + open-ended question; use first names to personalize
- •If target isn’t posting, reply to their comments elsewhere
- •Apply first, then DM to signal you’re real and make screening easier
- 1:28:06 – 1:32:27
Creator-style commenting vs targeted job outreach + closing wrap
Basia distinguishes between commenting for broad exposure (big accounts, early timing) versus targeted engagement with specific hiring teams. Aakash summarizes the masterclass and closes with where to find Basia and final show announcements.
- •Commenting on big creators works best when you’re early and insightful
- •For job switching, prioritize targeted engagement with relevant teams
- •Your tagline/profile are the conversion layer for every comment impression
- •Basia directs viewers to connect and DM her on LinkedIn
- •Episode wrap: recap + subscription/review requests + sponsor-style plugs
