May 2025 — March 2026 ·
203 applications ·
68 companies ·
2 offers ·
2,710 GitHub contributions
In dendrochronology, every ring tells a story — drought, fire, abundance, resilience.
You can't fake a tree ring. This is a cross-section of 10 months.
Applications
203
Across 68 companies
Interview Rate
14.7%
10 of 68 companies
Apps Per Offer
101.5
34 companies per offer
Ghost Rate
50%
34 companies, zero response
GitHub Contributions
2,710
From zero · Nov '25 → Mar '26
Products Shipped
6
Live domains · Built with AI
The Funnel
Conversion Funnel
Outcome Distribution
The Dual Track — Applications vs. GitHub Commits
Nov '25: Claude Code
Where the Effort Went
Top 15 Companies by Applications
Effort vs. Outcome
Key Insight
Volume didn't predict success. 5 single-application companies yielded interviews — the same number as all multi-application companies combined.
Single-app companies35 companies
→ Got interviews5 (14.3%)
Multi-app companies (2+)33 companies
→ Got interviews5 (15.2%)
The takeaway: Applying to 50 roles at one company produced the same interview rate as applying once. The first application either works or it doesn't — persistence only paid off at Microsoft.
What if the hours spent on apps 2-50 went to building instead? After November, they did. The shift from volume-applying to volume-shipping changed the trajectory.
Company Tier Breakdown
FAANG+
40%
interview rate
5 companies · 64 apps
Big Tech
8%
interview rate
12 companies · 41 apps
AI Frontier
20%
interview rate
5 companies · 24 apps
Mid-Market
13%
interview rate
46 companies · 74 apps
Tier Performance Analysis
FAANG+ Detail
MicrosoftOffer50 apps
GoogleInterview7 apps
AmazonRejected1 app
MetaGhosted3 apps
NVIDIAGhosted3 apps
FAANG+ had the highest interview rate at 40% — but it's skewed by Microsoft's 50-app persistence campaign. Without Microsoft, FAANG+ interview rate drops to 25% (Google only).
The Ghost Problem
Top 10 Ghosters Applications Wasted
The Ghost Economy
Half of all companies contacted — 34 out of 68 — never responded at all. Not a rejection, not a "we'll keep your resume on file." Nothing.
Ghosted
34 companies
Rejected
23 companies
Interviewed
8 companies
Offer
2 companies
Referral
1 company
62 applications (30.5% of all apps) went to companies that ghosted entirely. OpenAI and Atlassian each ate 5 applications with zero acknowledgment.
While they weren't responding, I was shipping. During the months with the highest ghost volume, I pushed 1,525 commits and launched 4 products. Their silence became build time.
What Actually Worked
Referral vs. Cold Apply +36.4pts
Referral
50%
interview rate (1 of 2)
Cold Apply
13.6%
interview rate (9 of 66)
Referrals converted at 3.7x the rate of cold applications. Two referral connections (Microsoft, Home Depot) generated 58 applications — 28.6% of all activity.
24.6% of all applications went to one company. The offer didn't come from the ATS — it came from direct outreach. The lesson: sometimes the system isn't the path. Relationships are.
The portfolio helped. By the time I made that direct outreach, I had a patent-pending mobile app, an AI SaaS product, a community platform, a gaming engine, and a workshop tool — all live, all built with AI. The resume said "PM." The GitHub said "builder."
LinkedIn Easy Apply vs. Direct/ATS
LinkedIn Easy Apply
14.3%
interview rate (1 of 7)
Direct / ATS
14.8%
interview rate (9 of 61)
Nearly identical conversion. The channel didn't matter — the signal was whether the role was a fit, not how you got in the door.
The Cost of Each Outcome
Applications per interview20.3
Applications per offer101.5
Companies per interview6.8
Companies per offer34
Interview → Offer rate20%
Total rejection emails76
Once past the resume screen, 1 in 5 interviews converted to an offer. The hardest part wasn't the interview — it was getting in the room.
The Numbers Behind the Rejection Emails
Who Rejected the Most
Role Diversity — Companies Where Multiple Roles Were Tried
Per-Company Breakdown
Company
Status
Applications
Rejections
Interviews
Referrals
Emails
The Builder Narrative
While Job Searching, I Was Shipping GitHub
In November 2025 — month 6 of unemployment — I picked up Claude Code via a $1,000 API credit. I'd never made a single GitHub contribution before. In the 5 months since, I went from zero to 2,710 contributions across 33 repositories. While 34 companies ghosted me and 76 rejection emails piled up, I was shipping real products — an AI SaaS, a community platform, a patent-pending mobile app, a gaming engine, and a workshop tool — all live, all with custom domains, all built with AI.
AI-powered home inventory. Snap a shelf photo, AI IDs every item in seconds. Expiration alerts, receipt scanning, voice updates. Android early access, AES-256 encrypted.
AI workshop companion. Photo or describe furniture → validated blueprints, optimized cut lists, shopping lists, 3D-printable connectors, OpenSCAD export. <60s to blueprint.
Plus games, demos, and research tools. Full portfolio → brokenbranch.dev
The Toolkit
What I Built With Stack
Every product was built with Claude Code as the primary development partner. I didn't learn to code in the traditional sense — I learned to direct code. The PM skills (requirements, architecture thinking, user stories, edge-case paranoia) turned out to be the exact skillset AI-assisted development rewards.
Claude Code
AI pair programmer — the $1K credit that started everything. Went from "what's a commit" to 33 repos.
Next.js / React
Frontend framework for all web products. App Router, Server Components, the works.
Supabase
Auth, database, storage, edge functions. The backend for Scouts+, Visual Inventory, and more.
Vercel
Hosting & deployment for every web product. Git push → live in seconds.
React Native / Expo
Mobile framework for RoadTripper.ai and Visual Inventory's Android app.
Tailwind CSS
Design system backbone. Every UI, every product, consistent design language.
TypeScript
Language of choice across the entire portfolio. Type safety for AI-generated code was non-negotiable.
Stripe
Payments & subscriptions for SaaS products. Checkout, webhooks, subscription management.
Electron
Desktop app framework for Exp-lore.ai's screen capture and gameplay analysis engine.
The meta-insight: None of these tools required a CS degree. They required taste — knowing what good looks like, what users actually need, and where the complexity budget should go. Those are PM instincts. Claude handled the syntax.
Growing an Audience
LinkedIn as a Build Log Distribution
While most job seekers use LinkedIn to apply, I started using it to publish. Two longform posts about the AI development experiment — "The $1K Claude Code Credit" and "If You Can Read a Recipe, You Can Now Be a Developer" — turned the job search narrative from "looking for work" into "building in public."
Published articles4
LinkedIn engagement shiftBuild → Share → Repeat
PCF whitepaperPublished on-site
The articles did more for visibility than 203 applications. People who read them reached out. The Microsoft offer came from someone who saw the portfolio, not someone who saw a resume in an ATS.
Products as Proof of Work Signal
Each shipped product became a conversation artifact. Instead of "I can manage AI products," it was "here's one I built, here's the live URL, here's the GitHub." That shift — from claiming to demonstrating — was the real unlock.
Unemployment is a creativity accelerator if you let it be. Every "we've decided to move forward with other candidates" email freed up mental bandwidth. Instead of wondering why Anthropic didn't respond to 12 applications, I built an AI SaaS product. Instead of refreshing my Salesforce application status, I filed a patent. The constraint — no income, shrinking runway, mounting pressure — forced ruthless prioritization. Only ideas that could ship fast survived. Only features users actually needed made the cut.
May – Oct
The Grind
165 applications. Optimizing resumes, tailoring cover letters, tracking in spreadsheets. Diminishing returns. The ATS void.
Nov – Dec
The Pivot
Claude Code arrives. First commit Nov 14. 15 repos in month one. The energy that went into applications redirected into products. Still applying, but now also building.
Jan – Mar
The Compound
Peak output: 559 commits in January alone. Products launching weekly. Articles getting traction. The portfolio is the resume. Offers arrive.
The creative pattern: Constraint breeds invention, but only if you redirect the energy. The months with the most rejections (Jan: 35 apps) were also the most productive build months (Jan: 559 commits). The frustration didn't paralyze — it fueled. Every "no" was a permission slip to go build something nobody could reject.
What I Learned
10 Rings, 10 Lessons Dendrochronology
Ring 01
The ATS is a black hole
50% of companies ghosted completely. The system isn't broken — it was never designed for you. Treat applications as lottery tickets, not conversations.
Ring 02
Volume is a vanity metric
Single-app and multi-app companies had identical interview rates (~14-15%). The first application is the signal. After that, you're just generating noise.
Ring 03
Referrals are 3.7x multipliers
50% interview rate vs. 13.6% cold. The best ROI on your job search time isn't optimizing resumes — it's maintaining relationships.
Ring 04
The hardest part is getting in the room
Once past the resume screen, 1 in 5 interviews converted to an offer. The bottleneck is visibility, not ability.
Ring 05
Build in public, not in silence
LinkedIn articles about the AI development experiment generated more warm interest than 200+ applications through official channels.
Ring 06
Ship > Study
I didn't take a bootcamp or certification course. I shipped 6 live products. Deployed code teaches you more than any tutorial, and it compounds into a portfolio.
Ring 07
AI-assisted dev rewards PM instincts
Requirements clarity, edge-case thinking, architecture decisions, user empathy — these are the skills that make Claude Code productive. Syntax is the easy part.
Ring 08
The channel doesn't matter
LinkedIn Easy Apply: 14.3%. Direct/ATS: 14.8%. Identical. The signal is fit, not delivery mechanism. Stop optimizing the envelope.
Ring 09
Constraint breeds invention
No income, no team, no design resources. The constraint forced fast iteration, ruthless scope, and genuine creativity. The best products came from the tightest months.
Ring 10
Relationships close. Portfolios open doors.
The Microsoft offer came from direct outreach backed by a live portfolio — not from application #50 through the ATS. Build the proof, then show the people who matter.