Gapmap.dev's answer

Gapmap grew out of our own interview prep. The standard routine - reread everything, grind questions, hope - wastes most of its time on topics you already know. The tool we wanted didn't exist: something that would honestly tell you what you don't know, then check that you can actually explain it out loud. So we built the grading engine first, and the map grew around it.

Topolog's answer:

Built by a solo founder with 14 years across Meta, Media.net, Amazon and others. After watching countless projects miss deadlines, not from incompetence but from tools that gave one fake date, I set out to build a planning engine that takes uncertainty seriously. The result is Topolog: a formally total scheduling language, a deterministic Monte Carlo engine, and a Bayesian self-tuning scheduler. Built entirely solo with Claude Code and Devin as AI engineering partners. Zero VC, zero team, 100% ownership.

Gapmap.dev's answer

Mid-level and senior software engineers preparing for technical interviews - frontend, backend, DevOps, system design - who have limited prep time and need to spend it on real gaps, not on rereading everything. It also fits engineers returning to the job market after years at one company who no longer know where they stand.

Topolog's answer:

Anyone running a goal with real dependencies and real stakes: technical project managers, engineering managers, founders, and ambitious individuals planning complex personal projects like home renovations, album productions, or marathon training. The unifying characteristic is feeling the pain of planning tools that lie about deadlines. Topolog is for people who want to know their actual odds, not a false sense of certainty.

Gapmap.dev's answer

Mock-interview platforms and question banks answer "how do I practice?" but leave "what exactly should I practice?" to you. Gapmap answers that question first and keeps re-answering it: the map re-prioritizes after every graded answer. The entire study library - 200+ topics written to senior depth - is free with no signup; you pay only for measurement and mock interviews.

Topolog's answer:

Every other planning tool gives you one deadline, the one you'll miss. Topolog gives you the full picture: a dependency graph that knows what blocks what, a Monte Carlo completion spectrum showing your real odds, a critical path that updates as you execute, and a budget tracker tied directly to your probability of success. MS Project has critical path but no probabilistic engine. Monday and Asana have boards but no complete dependency model. AI tools hallucinate dates. Topolog computes them.

Gapmap.dev's answer

Most interview prep starts with practice. Gapmap starts with measurement: a short conversation about your goal draws a personal map of topics, and a 15-minute adaptive diagnostic scores your actual level on each one - so you only study what's actually weak. A topic counts as closed when you've explained it out loud to an AI interviewer that asks follow-up questions and grades your reasoning against per-question rubrics - not when you tick a checkbox.

Topolog's answer:

Topolog treats every plan as a program. Plans are written in TOL (Total Orchestration Language), a formally total, decidable language where the scheduler and Monte Carlo engine compute dates and probabilities deterministically. The AI drafts structure but never touches the maths. You get a completion spectrum (a probability distribution over outcomes), honest deadline ranges (a floor and a ceiling, never one date you'll miss), and a Bayesian self-tuning scheduler that learns your real pace from timestamps alone. The planning language is public, you can author plans with any AI and run them through Topolog's engine.

Gapmap.dev's answer

Next.js (App Router), TypeScript, Tailwind CSS, PostgreSQL (Supabase), Drizzle ORM, deployed on Vercel. The grading, interview and voice layer runs on Anthropic's Claude models.

Topolog's answer:

Topolog is a TypeScript-first web app built around a custom stochastic-planning engine:

Frontend: Next.js 15 (App Router) with React 18 and TypeScript, styled with Tailwind CSS. The interactive plan canvas uses dagre / ELK (elkjs) for graph layout.

Core engine: an in-house DSL ("TOL") plus a Monte Carlo stochastic-forecasting engine, written in pure isomorphic TypeScript so it runs identically on the server and in the browser.

Backend & data: Supabase (PostgreSQL, auth, and SSR), with the API layer on Next.js route handlers. Stripe handles billing.

AI authoring: a model-router layer that calls GPT (OpenAI), and Mistral for plan authoring and review.

Infra & quality: deployed on Vercel (Analytics + Speed Insights), error monitoring via Sentry, and tested with Jest + Playwright.

Gapmap.dev's answer

Individual developers preparing for interviews - Gapmap is a personal tool, not a company subscription