Applying for jobs used to be hard.
Now it is absurd.
You can spend hours refining your resume, writing a thoughtful cover letter, polishing your portfolio, and trying to make a real case for yourself, only to get rejected almost immediately. In many cases, nobody ever really looked at your application. Not a recruiter. Not a hiring manager. Not a future teammate. A machine looked at it first, and the machine said no.
That is the reality now.
The hiring process has become a system of filters, scoring, keyword matching, automated ranking, and AI-assisted screening. Before a human ever gets involved, software is already making decisions about whether you are worth a closer look. That means the game has changed. The first challenge is no longer just presenting yourself well. The first challenge is getting past the automated gatekeeper.
That is exactly why I built Human, Actually.
I built it to help real people make a stronger, more truthful, more strategic case for themselves in a hiring environment that increasingly treats them like data instead of humans.
What it is
Human, Actually is a free app that helps job seekers create tailored application materials for a specific role.
You give it:
- your resume
- your website or portfolio
- the job description
- optional notes about experience that may not be represented well yet
- optional writing samples if you want the output to sound more like you
From there, the system analyzes all of that and determines how well your current materials actually match the role.
That part matters.
A lot of tools in this space stop there. They'll give you a score, toss out a few generic suggestions, maybe tell you that you are missing some keywords, and then ask for your credit card. I wanted to build something that goes much further than that.
This app does not just tell you where the gaps are. It helps you close them.
The core idea
The big insight behind this project is simple.
A lot of people are more qualified than their application materials make them look.
They did the work. They led the project. They shipped the feature. They solved the problem. They worked across teams. They improved the process. They drove the outcome.
But not all of that made it into the resume.
Some of it is buried on an old portfolio page. Some of it lives in a forgotten case study. Some of it is hiding in a personal website. Some of it was never written down at all because people are tired, discouraged, underselling themselves, or simply trying to survive.
So when an ATS or AI system evaluates the application, it is not judging the whole person. It is judging a partial, incomplete representation of that person.
That is a huge problem.
Human, Actually is built to fix that.
How it works
Once you upload your resume, add your website or portfolio, and paste in the job description, the app looks at all of it together and asks a very practical question:
Based on the evidence available right now, how strong is the match?
Not fantasy. Not fluff. Not wishful thinking. Evidence.
Then the system identifies what is missing, weak, unclear, or underrepresented.
Maybe the job description emphasizes leadership, but your resume mostly highlights individual contributor work.
Maybe the role calls for cross-functional collaboration, but your materials do not make that visible enough.
Maybe the company wants someone with strong systems thinking, stakeholder communication, experimentation, mentoring, or domain expertise, and the evidence you provided does not surface that clearly.
This is where the app gets interesting.
Instead of just saying, "You are missing X," it starts asking targeted questions designed to uncover real experience that may not be represented yet.
Things like:
- Did you lead a team, even informally?
- Did you mentor other designers or engineers?
- Did you influence product direction without having direct authority?
- Did you build systems, frameworks, or reusable patterns?
- Did you improve a workflow, reduce complexity, or create leverage?
- Did you solve the exact kind of problem this job is asking for, but fail to spell it out clearly in your resume?
And that is where people often realize: Oh right. I actually did do that.
Maybe it was in a past role. Maybe it was buried in a project. Maybe it never made it onto the resume because there was no room, or it seemed obvious at the time, or it just got forgotten.
The app gives people a way to recover that missing signal.
It helps you strengthen your evidence, not invent a story
This part is important to me.
I did not build this to help people lie.
I did not build it to invent qualifications they do not have.
I did not build it to generate polished nonsense full of buzzwords and fake confidence.
The system is designed to work from evidence. It helps people surface what is true, organize what is relevant, and present it in a way that maps better to the role they are applying for.
If the user adds information that is false, obviously no tool can fully prevent that. But the app itself is not built to embellish. It is built to uncover, clarify, and optimize what is already real.
That distinction matters.
There is a big difference between:
- manufacturing a fit that does not exist
- helping someone articulate a fit that is already there but poorly represented
I am interested in the second one.
Notes make the system smarter
One of the things I added that I really like is the ability for users to include extra notes.
These notes can be anything that strengthens the case:
- context around a project
- work that is not represented well on the resume
- accomplishments that were omitted
- links to supporting evidence
- details about how something was done
- outcomes, impact, constraints, or team structure
This matters because resumes are brutally compressed documents. People leave out all kinds of useful signal because they are trying to fit years of work into a page or two. That means a lot of important context never makes it into the document that gets screened.
The notes feature gives users a place to restore some of that lost context.
It can also sound like you
Another thing I cared about a lot was voice.
Most AI-generated cover letters are dead on arrival. You can smell them from a mile away. They have that polished, robotic, over-explained, generic tone that instantly makes them feel fake.
I hate that.
So Human, Actually lets users provide a writing sample if they want the cover letter to sound more like them. That could be an article, a personal essay, an email, a bio, whatever. The system uses that sample to better match tone, phrasing, rhythm, and personality.
I also put a lot of effort into the prompting and output behavior to avoid the usual AI tells. The goal was never to make the writing sound "AI good." The goal was to make it sound human, specific, believable, and natural.
That is part of the reason for the name.
The output is tailored to one job, not to "job seeking" in general
This is another major point.
The app is not trying to create one magical universal resume that works for everything. That is not how this works anymore.
The reality is that if you want to maximize your odds, you often need to tailor your materials for the specific role in front of you. Not by faking anything, but by emphasizing the parts of your actual experience that most directly map to what that job is asking for.
So the end result is not generic.
The system creates:
- a custom resume tailored to the specific role
- a custom cover letter tailored to the specific role
And because it has already analyzed the job description, found the gaps, asked follow-up questions, and incorporated additional evidence, the output is stronger than what you would get from a simple "paste in resume, press generate" tool.
It is not just rewriting. It is rebuilding the case.
You can steer it
I also did not want this to feel rigid or one-shot.
If the cover letter comes out and you want it to sound more technical, you can say that.
If you want it to emphasize a different project, you can say that.
If you want it to be a little sharper, a little warmer, more direct, more strategic, less formal, more aligned with your writing sample, you can say that too.
So instead of getting one static output, you can guide it. You can refine the result until it feels right.
That makes the system much more useful, because people do not just want "a generated cover letter." They want their cover letter, aimed at this job, written in a way that still feels like them.
It works with multiple AI providers
Another thing I wanted from the beginning was flexibility.
The app works with OpenAI, Claude, and Google Gemini.
That means it is not locked to a single provider, and users can work with whichever model ecosystem they already prefer or already have access to. I like that because it makes the tool more open and less dependent on the business decisions of any one company.
Why I made it free
This part is probably the most important.
I built this because I wanted to help people.
Not "help people" as a slogan. Actually help people.
There are already plenty of tools out there that charge job seekers money to get vague ATS advice, generic scoring, or watered-down resume suggestions. Many of them do less than this app does and still put the useful parts behind a paywall.
I did not want to build that kind of product.
People looking for work are often already under pressure. Financially. Emotionally. Mentally. They are applying and applying and hearing nothing back. They are dealing with rejection, uncertainty, and a process that often feels dehumanizing.
That is not the moment where I want to squeeze them for subscription revenue.
That feels wrong to me.
So Human, Actually is free.
The only catch is that you bring your own API key.
Why? Because I cannot realistically pay for everyone's OpenAI, Claude, or Gemini usage out of pocket. That is just the practical reality. But I can remove the subscription barrier, remove the gatekeeping, and make the tool itself available for free.
That tradeoff feels fair.
You use your own key. You use the app for free. If it helps you land something great and you feel like throwing a few bucks my way afterward, awesome. If not, that is fine too.
There is a donation link on the site, but there is no pressure. The point is to help.
Why the name fits
The name Human, Actually is a little playful, sure, but it also says exactly what I think is broken.
The hiring process has become increasingly machine-mediated. More automated. More detached. More focused on filters, matching, ranking, and triage.
Somewhere in that process, the actual human being got pushed into the background.
This app is my attempt to push back on that.
Not by pretending the systems do not exist. They do.
Not by telling people to just "be authentic" and hope for the best. That is not enough anymore.
But by giving applicants a way to be more strategic, more complete, more visible, and more effective without losing the truth of who they are.
That is the whole point.
Because behind every rejected application is not just a PDF. It is a person. A person with experience, effort, strengths, gaps, history, context, and potential. A person who deserves a real shot.
And if the front door is guarded by machines now, then people deserve better tools to get through that door.
That is why I built Human, Actually.