What We Built and Why It Had to Exist

Typify exists because the software industry has a broken pipeline. Not a talent shortage. Not a skills gap. A recognition gap. Companies cannot tell who is good, and engineers cannot prove it. We built an entire platform to fix both sides of that problem at once.

This is the story of what we built, how it works, and why every piece of it exists.

The Problem Is Structural

Hiring in tech runs on proxies. Resumes. Years of experience. University names. GitHub stars. These are not measures of engineering ability. They are measures of circumstance. A developer with ten years of copy-pasting Stack Overflow looks identical on paper to one who has shipped distributed systems from scratch. The resume cannot tell the difference.

On the other side, talented engineers (especially those from non-traditional backgrounds or underrepresented regions) have no credible way to signal their ability. Open source contributions help, but not everyone has the luxury of unpaid labor. Certifications are pay-to-play checkboxes. Coding bootcamps vary wildly in quality, and their certificates carry the reputation of their weakest graduates.

The result: companies keep hiring the wrong people, and the right people keep getting overlooked.

We decided to build the thing that should have existed all along: a system that trains engineers rigorously, evaluates them honestly, and connects the ones who prove themselves directly with companies that need them.

Training That Actually Changes How You Think

Most developer training teaches you a framework. Typify teaches you how to think.

Our training program is built around Haskell and functional programming. Not because we think everyone should write Haskell at work (though we would not complain), but because learning Haskell forces you to confront the things most languages let you hide from. Mutation. Implicit state. Unhandled errors. Ambiguous types. Haskell does not let you ignore these. It makes you deal with them, and in doing so, it rewires how you approach every engineering problem for the rest of your career.

Engineers who come through our program and go on to write Python, TypeScript, or Java do not write those languages the same way they did before. They write smaller functions. They think about edge cases before they happen. They reach for composition instead of inheritance. They reason about data flow instead of control flow. The language changes. The thinking stays.

Our curriculum is structured around progressive exercises, video lessons with full transcriptions, and real projects. Not toy apps. Not tutorial-grade TODO lists. Real systems that require you to make architectural decisions, handle failure, and work with other people's code. The projects scale in complexity:

1. CLI Todo app
2. CLI Tic Tac Toe
3. Twitter Clone
4. Chat Server

By the time someone finishes the Chat Server, they have built a networked application that handles concurrency, state management, and real-time communication. That is not a bootcamp certificate. That is evidence.

Mock Interviews That Mirror Reality

We run structured mock interviews. Not whiteboard puzzles. Not "reverse a linked list on a timer." Real technical conversations that test whether an engineer can reason about a system, explain their decisions, and adapt when the problem shifts.

Each mock interview generates a detailed report. Not a pass/fail grade. A breakdown of what the candidate demonstrated: problem decomposition, communication clarity, depth of understanding, ability to handle ambiguity. Reviewers assess six dimensions that we have found to be predictive of actual engineering performance, not just interview performance.

These reports serve two purposes. For the engineer, they are a diagnostic tool. You learn exactly where you are strong and where you need work, with specific feedback you can act on. For companies, they are a trust signal. When we recommend a candidate, the recommendation comes with evidence. Not "this person seems smart." Evidence. Structured, comparable, and grounded in observed behavior.

Code Challenges That Go Beyond LeetCode

We built an in-browser coding environment where engineers solve challenges that test real engineering judgment, not just algorithmic recall. The platform compiles and runs Haskell code, evaluates it, and tracks progress over time.

There is a leaderboard. Not because we believe engineering is a competition, but because visible progress motivates people. When you can see yourself climbing from challenge 12 to challenge 40, and you can see that the problems are getting harder and you are still solving them, that builds the kind of confidence that shows up in interviews and on the job.

The challenges are curated, not scraped from a problem bank. Each one is chosen because it tests a concept that matters in production code: recursion, type-level reasoning, data transformation, error handling. If a challenge does not teach something transferable, we cut it.

A Community, Not a Content Feed

Typify has a built-in chat system with channels, direct messages, and group conversations. This is not a social network bolted onto an LMS. It is the connective tissue of the platform.

Engineers in our program help each other. They debug together. They discuss problems from the curriculum. They share what they are learning and challenge each other's understanding. The best learning happens in conversation, not in isolation. We built the infrastructure to make that conversation happen naturally, inside the same platform where the training and evaluation live.

What we have seen emerge is something we could not have designed: a community where people who started as beginners are now the first to help newcomers. They explain concepts in ways we never would have thought of, because they remember what it was like not to understand. That feedback loop, where learning leads to teaching leads to deeper learning, is the real product. The platform just makes it possible.

A Job Board Built on Trust

Most job boards are broadcasting tools. You post a listing. Hundreds of strangers apply. You spend weeks filtering. The signal-to-noise ratio is terrible, and the best candidates often never apply at all because they have seen too many postings that waste their time.

Our job board works differently. Companies post positions. Engineers who have been through our training program, who have mock interview reports, who have demonstrated their ability through code challenges and community participation, can browse and apply with a profile that actually means something. There is no keyword stuffing. No inflated titles. The profile is backed by the work they have done on the platform.

And we curate from both sides. When we know a company's needs and we know our engineers' strengths, we make introductions. Not in a mass-email, spray-and-pray way. In a "this specific person is ready for this specific role, and here is the evidence" way.

We Built the Platform the Way We Train

Typify itself is a full-stack Haskell application. The frontend compiles to JavaScript through GHCJS. The backend runs on Servant and Snap. The database layer uses Beam with automatic migrations. Real-time features run over WebSockets via Rhyolite. The styling system is type-safe through ClasshSS, meaning CSS class errors are caught at compile time, not discovered by a user squinting at invisible text in production.

We did not build it this way to be clever. We built it this way because these are the same principles we teach. If types matter for application code, they should matter for styling. If correctness matters for business logic, it should matter for the platform that delivers that business logic. We eat our own cooking.

The result is a platform that moves fast without breaking. We deploy with confidence because the compiler has already caught the classes of bugs that would plague a dynamically typed system. This is not theoretical. This is how we ship, every day, across 18 countries and over 100 client companies.

Why This Matters Now

The gap between companies that can identify engineering talent and companies that cannot is widening. Companies that rely on resume filtering and LeetCode screens will continue to miss exceptional engineers. Companies that invest in curated pipelines, where candidates are trained, evaluated, and recommended based on demonstrated ability, will build teams that outperform.

We have seen it happen. Engineers who came to Typify with no formal CS degree, from countries where the tech industry barely has a foothold, are now writing production Haskell (and TypeScript, and Python, and Rust) for companies that never would have found them through a job board. That is not an anecdote. That is the system working as designed.

Typify is not a recruiting agency. It is not a bootcamp. It is not a job board. It is the infrastructure that connects rigorous training to meaningful employment, with evidence at every step. We built it because the industry needed it, and nobody else was going to.

What Comes Next

We are expanding the training curriculum. We are deepening the evaluation system. We are building new tools for companies to understand not just who a candidate is today, but how fast they are growing and in what direction. And we are scaling the community, because the best version of Typify is one where every engineer on the platform makes every other engineer on the platform better.

If you are an engineer looking for training that will actually change how you think and a direct path to companies that value what you can do over where you went to school, join us.

If you are a company tired of sifting through noise and ready to hire engineers who have already proven themselves, let's talk.

We built Typify to close the gap between potential and opportunity. The gap is still wide. We are just getting started.