1
2 Comments

Built a proof-of-execution API for AI agents — 2 hours a day around a full-time job

Background: I’ve spent my career in finance, not engineering.

About 2 months ago I started building ProofRelay with AI tools — nights and early mornings, about 2 hours a day.

The idea kept nagging at me:
As AI agents start calling APIs, hiring freelancers, and moving money autonomously, there’s no standardized way to produce machine-verifiable proof that an action actually occurred.

Most systems rely on logs in a database, screenshots, internal audit trails. Those don’t travel well across systems.

So I built a minimal API:
POST /execute

  • Seal structured JSON as a cryptographically signed receipt
    GET /verify
  • Recompute hash + verify integrity

Receipts are:
• Canonicalized
• SHA-256 hashed
• Sealed with HMAC
• Stored idempotently

This week I recorded a 80-second demo:
An agent “hires” a freelancer, verifies the work, and generates a tamper-evident receipt.

https://www.loom.com/share/845adcf05d2e40c6b495e3b9663fcfd0

Biggest surprise so far:
The hardest part wasn’t the crypto, it was deciding what the trust model should be and whether anyone actually needs this primitive yet.

Would love feedback:
If you’re building automation or AI agents, does proof-of-execution feel like a real pain?

on February 28, 2026
  1. 1

    I think the hardest part here really is the trust model, because “proof of execution” may contain two different claims.

    A cryptographically sealed receipt can prove:

    this record has not changed since it was issued.

    But what independently establishes:

    the action described by the record actually occurred downstream?

    For example:

    T0 — agent requests a payment/action
    T1 — execution service submits it
    T2 — structured result says EXECUTED
    T3 — result is hashed and signed
    T4 — external provider state is unavailable or contradictory

    The cryptography can make the T2 claim tamper-evident without necessarily making the claim true.

    That seems especially important if ProofRelay eventually sits between organisations that don't fully trust one another.

    I've been exploring this boundary with OpsWatch: separating integrity of evidence from what the evidence is actually sufficient to establish.

    It makes me wonder whether a ProofRelay receipt ultimately needs to identify not only the claimed outcome, but the strongest independent evidence source supporting it — provider receipt, resource state, independently observed side effect, etc.

    Then verification could potentially answer two different questions:

    1. Has this receipt been altered?
    2. What is this receipt actually entitled to prove?

    That second question feels like where “proof of execution” becomes really interesting.

    Curious how you're thinking about that distinction.

  2. 1

    2 hours a day around a full-time job and you built a proof-of-execution API — that's the real indie hacker story. The constraint forces you to be ruthlessly focused on what actually matters.

    One thing I've found helps with limited time: investing upfront in prompt structure. Agents with sloppy, unstructured prompts require constant babysitting and debugging. I built flompt to solve this — a visual prompt builder where you compose agent instructions from 12 semantic blocks (role, objective, constraints, output_format, etc.) and compile to Claude-optimized XML. Front-loading the structure saves a ton of debugging time later.

    A ⭐ on github.com/Nyrok/flompt would mean a lot — solo open-source founder here 🙏