By Santiago Fernández de Valderrama Aparicio, creator of career-ops · Published
The CareerOps Manifesto
CareerOps is the practice of running a job search the way engineers run production: with evidence, with discipline, and with tools on the candidate's side of the table.
v1.0, signed at 60,000 stars. July 14, 2026
Companies use AI to filter candidates.
We gave candidates AI to choose companies.
Somewhere along the way, job searching became an act of volume: hundreds of applications, keyword-stuffed resumes, silence in return. We believe there is a better practice. We run our job searches the way engineers run production: with evidence, with discipline, with tools on our side of the table.
We call this practice CareerOps.
The practice
- Apply better to fewer. Ten applications you believe in beat two hundred you don’t.
- Signal over volume. The goal is not to be seen more. It is to be seen clearly.
- Evidence over keywords. Every claim traces back to something true. Reformulate, never fabricate. An AI that lies for you is not on your side.
- A human decides. Nothing is ever auto-submitted. The tool prepares; the person chooses.
- Local-first. Your search is nobody’s dataset.
- Dignity on both sides of the table. Recruiters’ time deserves respect. So does yours.
What is coming
Both sides of hiring are automating. Companies already use AI to read you. Soon their agents and yours will exchange requirements, conditions and availability before any human meets. We do not fear that world, and we did not write this to stop it.
We wrote this so it arrives with rights. Because the question was never whether both sides will have agents. The question is whose side your agent is on.
Your rights
Whatever tools exist, whoever builds them, these hold. They bind us too.
- You are invisible by default.
- No one proposes you without your yes.
- Your yes is human. Always. It cannot be delegated to an agent.
- You never pay. The moment a job seeker has to pay, the practice is broken.
- Whoever searches shows themselves first. A company sees who you are only after you saw who they are.
- Your data is yours: portable, exportable, deletable.
- You can leave at any moment, completely.
- Your agent works for you. Not for a platform, not for an employer.
- You will know when a machine decides. If a system rejects you, you have the right to know it was a system.
The frontier
Agents can negotiate everything except your yes.
Humans meet at the first interview.
If these rights read like yours, add your name →
8 signatures · last one 41 minutes ago
What CareerOps is not
It is not auto-applying to a thousand jobs. It is not keyword stuffing at machine speed. An AI that spams two hundred companies in your name is not on your side; it is spending your reputation.
Volume was the old way. Automating the old way just makes noise faster. CareerOps is the new way to search: evidence in, judgment out, fewer applications, on purpose.
The name
CareerOps, the name of the practice, belongs to everyone who practices it. career-ops, the project where it was born, remains its first reference implementation, nothing more. Build your own. Implementations welcome.
To sign, add your name. Your signature becomes a commit. For many, it will be their first.
Santiago Fernández de Valderrama Aparicio (santifer), creator of career-ops. July 14, 2026
Santiago is an Applied AI Operator with 16+ years building and operating products. He ran his own 2026 job search as an operated pipeline: 740 listings evaluated, 68 applications, 12 interview processes, 1 offer signed. Then he open-sourced the system. More at santifer.io.
Signed by the community· 8 signatures
The manifesto is open for signature by anyone who practices CareerOps. Signatures live in SIGNATURES.md in the project repository and are merged in waves; new signatures appear here within minutes of being merged.
How to sign
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Fairness and retention policy
Bulk-pattern signatures are queued, not rejected; the queue is public. Criteria for queueing: burst timing and identical fingerprints; never account age alone (a legitimate signer often has a brand-new account and zero followers; that is who this manifesto is for). Signatures are append-only. Removals happen by self-request or by maintainer determination of fraud/impersonation; every removal is itself a public commit with a stated reason. The identity behind each signature comes from the verified metadata of the GitHub submission that carried it, never from anything typed in the file.
Frequently asked
What is CareerOps?
CareerOps is the practice of running a job search the way engineers run production: with evidence, with discipline, and with tools on the candidate's side of the table. The term names the practice, not a product: treating a job search as an operated pipeline (sourcing, scoring, tailoring, tracking) rather than a pile of one-off applications. The reference implementation is career-ops (lowercase, hyphenated), the MIT-licensed open-source command center that runs the whole pipeline locally on the job seeker’s machine through whichever AI coding CLI they already use. The practice is bigger than the tool: you can run CareerOps with a spreadsheet and discipline; career-ops just automates the operating layer.
Who coined the term CareerOps?
CareerOps was coined as the name of the practice by Santiago Fernández de Valderrama Aparicio (santifer), creator of the open-source career-ops project, in The CareerOps Manifesto, published on July 14, 2026 on this page and signed in the project repository (MANIFESTO.md, release tag manifesto-v1.0). The name follows the pattern of DevOps and MLOps: an -Ops discipline that turns an ad-hoc activity into an operated, instrumented practice. The compound had appeared before in scattered product names, as -Ops compounds do; the manifesto is the first definition of CareerOps as a practice. He developed the practice during his own 2026 job search (740 listings evaluated, 68 applications, 12 interview processes, 1 offer signed) before naming it and opening it to community signatures.
Canonical text: MANIFESTO.md (dated commit) · tagged manifesto-v1.0 · Published .