Alongwise: Career Coaching and Application Management Platform

From isolated application tasks to a coherent process

Career applications are often handled as disconnected tasks: comparing opportunities informally, adapting a static resume, drafting each cover letter from scratch, and tracking decisions elsewhere. That fragmentation makes it difficult to apply consistent criteria or reuse evidence without losing the context behind it.

I created Alongwise to bring those activities into one working system. It combines career decision support, application-material generation, opportunity management, and human coaching around a persistent user profile.

My role

I designed and developed Alongwise end to end. My work covered product definition, interaction and data design, full-stack implementation, prompt orchestration, application architecture, administrative controls, billing, deployment, and the operating workflows for applicants and coaches.

The platform uses a React and TypeScript interface with a FastAPI and PostgreSQL backend. I followed a schema-first approach so that profiles, criteria, application evidence, permissions, and product configuration have explicit representations rather than being embedded only in interface logic.

What I created

Users begin by recording their experience, strengths, goals, constraints, and weighted decision criteria. They then build a reusable body of resume evidence through manual entry, document extraction, or optional import from RecomAid, another platform I have developed.

Jobs, academic programs, schools, and scholarships can be captured in a common workflow. Alongwise uses the user’s profile and criteria to generate match-likelihood and career-alignment assessments. These scores are intended to support reflection and comparison; they are not predictions of application outcomes.

For opportunities a user chooses to pursue, the platform generates tailored resumes and cover letters from the stored evidence, profile, and opportunity context. Documents can be rendered as PDFs on demand while the editable source remains stored as structured text.

Alongwise also supports human coaching. Coaches can work with assigned clients, maintain session and accountability records, and use a dedicated dashboard. A single account may carry applicant, coach, and administrator roles while preserving access to the underlying application workflow.

Configurable product and prompt architecture

A central design decision was to separate roles, subscription plans, and feature entitlements. Role-based access determines which product surfaces a person may use; the subscription layer records what has been purchased; and configurable entitlements determine whether a particular combination can access a feature. This allows plans and product behavior to evolve without treating billing status as an application role.

The language-model layer is similarly configurable. Prompt templates, model selections, limits, and feature settings are managed as product data rather than being scattered through the application code. Prompts are assembled from administrator-defined settings, the user’s profile, and the relevant opportunity. The same orchestration layer supports criteria development, opportunity scoring, tailored materials, and resume-file extraction.

Administrative tools expose these settings alongside user invitations, role requests, plans, feature mappings, and other operational controls. Stripe Checkout, the Customer Portal, and webhooks provide the billing layer for Premium and Coach plans.

Current status and limits

Alongwise is live at alongwise.com and remains under active development. The supplied materials establish an implemented product and operational architecture, but they do not yet establish adoption, application success, coaching outcomes, or comparative generation quality. Those measures will be reported separately when reliable evidence is available.