THE JOB SEARCH IS BROKEN

Not having an AI assistant for your job search is a thing of the past. Today's market requires 300+ applications and 800+ hours of work - a workload that demands intelligent automation.

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The Reality

MATHEMATICALLY IMPOSSIBLE

Applications Required

Average to receive one offer

AI handles volume

Hours of Work

44 weeks at 20 hours/week

Parallel execution

Silence Rate

Complete non-response

ATS optimization

Weeks Average

Median search duration

Accelerated timeline

ATS Rejection

Before human review

Keyword matching

Ghosting Rate

After interviews

Persistent follow-up

Personalization Engine

v1.0

DESIGNED FOR YOU

Every career journey is unique. Our intelligent AI personalization engine analyzes your professional background, goals, and target market to craft a completely customized strategy with precision-tailored tasks that accelerate your path to success.

Resume Analysis

Multi-stage document processing

Processing Stages

Upload → Analysis → AI → Template → Storage

career.yaml

5+ years tech exp

strategy.yaml

TechCorp, InnovateCo, StartupXYZ

preferences.yaml

$120K-$160K range

Supabase Storage

Version control

Linear Integration

Template-driven task generation

Template Engine

160

Master Linear templates

RES-621

LinkedIn scraping

RES-622

Crunchbase analysis

OpenRouter

DeepSeek/Gemini AI

MCP Server

Workflow execution

Tracking Database

PostgreSQL/Supabase backend

Database Tables

15+

Real-time tracking

workflow_executions

Task state

job_discoveries

Found positions

application_submissions

Applied jobs

campaign_metrics

Success rates

Technical Implementation Flow

Resume Upload

useResumeAnalysisSimple() hook + streaming

Spec Generation

SpecGenerationOrchestrator 5-stage pipeline

Variable Building

TemplateVariableContext.ts maps 50+ vars

Linear Creation

LocalTemplateProcessor personalizeIssue()

Workflow Execute

MCP Server + coordination_key dedup

Results Storage

Supabase workflow_executions table

Example Task Tailoring

Before Task Tailoring

LinkedIn Company Database Builder

Title: "Research {{PRIMARY_INDUSTRY}} companies"

Description:

• Target role: {{USER_CURRENT_ROLE}}

• Experience: {{USER_YEARS_EXPERIENCE}} years

• Locations: {{PREFERRED_LOCATIONS}}

• Salary: ${{MIN_SALARY}}-${{MAX_SALARY}}

• Company sizes: {{COMPANY_SIZE_PREFERENCE}}

• Spec ID: {{SPEC_COLLECTION_ID}}

From: TemplateVariableContext.ts buildUserVariables()

After Task Tailoring

LinkedIn Company Database Builder

Title: "Research Technology Industry companies"

Description:

• Target role: Software Engineering Manager

• Experience: 5+ years

• Locations: Major City, State

• Salary: $120,000-$160,000

• Company sizes: ['medium', 'large']

• Spec ID: spec_user_default

User ID: a1b2c3d4-5678-41ef-890e-f1g2h3i4j5k6

Campaign ID: campaign_user_1734567890

Personalization by Archetype

Program Manager

Task: Portfolio Review

"Analyze 8 technology programs from your enterprise experience. Create case studies highlighting $10M+ budget management and 20% efficiency improvements."

Focus

Metrics & ROI

Duration

2-3 hours

Software Engineer

Task: Portfolio Review

"Prepare 5 code repositories showcasing full-stack expertise. Include documentation with architecture diagrams and performance benchmarks for each project."

Focus

Code quality

Duration

3-4 hours

Product Manager

Task: Portfolio Review

"Document 3 product launches with user acquisition metrics, satisfaction scores, and business impact. Create one-pagers showing 0-to-1 product development lifecycle."

Focus

User outcomes

Duration

2-3 hours

Linear Templates

160

RES-XXX issue templates

AI Models

DeepSeek + Gemini via OpenRouter

DB Tables

15+

PostgreSQL/Supabase

Strategic Architecture

DESIGNED FOR YOU TO BE AWAY

Built for complete autonomy from day one. Our 12-spec framework enables fully autonomous AI agents to manage your entire job search independently—steering files shape agent behavior, hook files trigger intelligent automation, and the system runs itself while you live your life.

Specification Files

The "What" - Core requirements and preferences

requirements.yaml

Target roles, compensation, timeline, KPIs

tasks.yaml

180-day execution plan with phases

discoveries.yaml

Job sources and discovery parameters

Steering Files

The "How" - Agent personality and logic

career.yaml

Professional narrative and goals

ethical.yaml

Immutable guardrails and rules

strategy.yaml

Decision logic and heuristics

Hook Files

The "When" - Event-driven automation

discovery.hooks.yaml

New job found triggers

application.hooks.yaml

Application status changes

monitoring.hooks.yaml

Performance alerts and optimization

How Agents Stay on Course

Parse & Profile

SvelteKit backend parses resume and generates initial profile using "lite" AI services

Generate Specs

Heavy generation service creates 12 specification files based on profile data

User Review

You review and approve specs, especially ethical.yaml for guardrails

Generate Tasks

AI Task Generator creates 500+ personalized tasks from Linear templates

Agent Execution

AI agents execute tasks while reading specs and writing to Living Memory

Continuous Learning

All outcomes feed back into Living Memory for strategy optimization

Automated Scheduling

DESIGNED FOR THE LONG HAUL

From launch to offer acceptance, our AI orchestrates every strategic move autonomously— intelligently scheduling, dynamically prioritizing, and flawlessly executing hundreds of tasks based on real-time market conditions and your evolving career trajectory.

Your First 30 Days

	Monday	Tuesday	Wednesday	Thursday	Friday
Week 1	Setup Resume analysis Spec generation Linear setup	Discovery • LinkedIn scraping • 50 companies	Discovery • Indeed parsing • Role matching	Application • Resume tailoring • 5 applications	Network • LinkedIn outreach • 10 connections
Week 2	Application • 10 applications • ATS optimization	Analytics • Response tracking • A/B testing	Network • Recruiter msgs • Coffee chats	Application • Cover letters • 10 applications	Interview • Prep session • Mock interview
Week 3-4	50 Applications sent 200+ Companies analyzed 30 Network connections 3-5 Initial screens

Daily Workflows

2-3 hours/day

Morning Discovery

RES-621: LinkedIn job scraping

30 min • Auto-executed

Application Sprint

RES-652: Submit 5 applications

90 min • Semi-automated

Network Outreach

RES-673: Connect with 5 people

30 min • AI-assisted

Response Tracking

RES-690: Update pipeline

15 min • Manual review

Weekly Workflows

10-15 hours/week

Market Analysis

RES-622: Crunchbase research

2 hours • Friday PM

Portfolio Updates

RES-645: Code projects

3 hours • Weekend

Interview Prep

RES-680: System design

4 hours • Scheduled

Strategy Review

RES-695: Metrics analysis

1 hour • Sunday

Monthly Workflows

Strategic planning

Geographic Expansion

RES-701: New markets

Month 2+ • Research phase

Resume Overhaul

RES-715: A/B testing

Month 3 • Data-driven

Comp Negotiation

RES-740: Market research

Month 4+ • Offer stage

Campaign Pivot

RES-750: Strategy shift

If needed • AI-guided

6-Month Campaign Phases

Foundation

25 applications

550 companies

Tools setup

Acceleration

60 applications

First interviews

A/B testing

Optimization

120 applications

Final rounds

Geo expansion

Multi-Channel

100 apps/week

200 outreach

First offers

Focus

60% interviews

2-4 offers

Negotiations

Close

Decision matrix

Final terms

Transition plan

Linear Master Templates

Total Templates 200+

Categories 10

AI Agent Prompts 200+

Template Categories:

• Company Sourcing (40+)

• Cold Outreach (30+)

• Application Pipeline (25+)

• Interview Prep (20+)

• Network Development (15+)

• Performance Analytics (10+)

Personalized Task Generation

Read Specs

AI Task Generator reads all 12 approved specification files

Fetch Templates

Pulls 200+ master templates from Linear API

Personalize

Customizes each template with user's specific context

Generate Tasks

Creates 500+ personalized tasks with AI agent prompts

Sync to Linear

Pushes tasks to user's Linear project for visibility

6-Month Campaign Targets

250

Applications

Strategic, personalized submissions

25-30

Opportunities

Interview and discussion stages

3-5

Offers

Competitive compensation packages

180

Days

Fully automated execution

Autonomous Memory Architecture

SELF-EVOLVING INTELLIGENCE

Beyond traditional databases—our AI develops genuine understanding of your career journey, autonomously connecting patterns, anticipating opportunities, and evolving its strategy with every interaction. Enterprise-grade cognitive architecture that thinks like your personal career strategist.

Core Memory Principles

Everything is a Learning Opportunity

Every application, rejection, and interview becomes data to refine strategies

Context is King

Memories linked to resume variants, companies, stages, and market conditions

Relevance Decays, Insight Persists

Job postings expire but learned patterns about companies remain

User-Correctable Memory

Directly view, correct, and reinforce the agent's learned insights

Three-Layer Memory Architecture

Episodic Memory

The Campaign Logbook

Perfect timestamped record of every event

Stores:

• Every application with resume variant ID
• All communications (emails, LinkedIn)
• Interview schedules and feedback
• ATS status changes
• User feedback and corrections

EVENT_ID: 4501
TYPE: 'INTERVIEW_COMPLETED'
COMPANY: 'TechCorp Inc.'
ROUND: 'Technical Screen'
NOTES: 'Strong on core concepts, needs system design practice'

Semantic Memory

Professional & Market Brain

Nuanced understanding of roles and preferences

Maintains:

• Professional skill vectors
• Ideal job clusters in n-dimensions
• Company knowledge graphs
• Cultural fit scores
• Skill ontology relationships

Vector Update:

User liked "mission-driven" company
→ Strengthen weight: +0.15
→ Cluster adjustment: Complete

Procedural Memory

The Strategy Playbook

How-to knowledge for successful job search

Optimizes:

• A/B tested resume strategies
• Communication templates
• Negotiation scripts
• Learned heuristics
• User-defined hard rules

fintech_impact_resume_v4: {
callback_rate: 0.22,
interviews: 18,
offers: 3
}

Memory Operations in Action

CREATE

+
Resume Ingestion

Build skill vectors
+
Job Liked

Add to ideal cluster
+
Application Sent

Log with full context

READ

→
Hourly Sourcing

Query ideal vectors
→
Resume Tailoring

Best strategy lookup
→
Interview Prep

Company dossier

UPDATE

↻
Positive Response

Boost strategy score
↻
Pattern Detected

Refine preferences
↻
User Correction

Override with weight

Your Memory Control Panel

Correct This Insight

Click any AI insight to mark as incorrect and update knowledge base

Find More/Less Like This

Primary feedback to reinforce or discourage opportunity types

View Company Dossier

See complete multi-source research profile for any company

Explain This Decision

Get natural language explanation of any agent action

Run a Simulation

Test "what if" scenarios like salary or location changes

Data Control

Export, archive, or permanently delete all campaign data

2,847

Events/Day

487

Preference Vectors

+18%

Success Rate

24/7

Learning Cycles

Live System

AUTONOMOUS COMMAND CENTER

Twelve specialized AI agents operate independently around the clock, executing your entire job search strategy without supervision. No monitoring required—just watch your career opportunities multiply as the system works autonomously in the background.

Active Agents

Running 24/7

Tasks/Day

847

Automated actions

Companies

2.5k

Tracked & analyzed

Success Rate

89%

Task completion

Resume Parser

active

127

tasks

Job Discoverer

active

892

tasks

Application Bot

processing

294

tasks

Live Activity

System Performance

Applications/Hour 42

ATS Match Rate 85%

Interview Rate 12%

Success Probability 94%