Pareto 20, No. 7: Ravoid, for the ways an agent can spend or leak what it should not

A one-person publication on what actually stops a runaway agent: not dashboards, not bans, but controls in the request path. Read it for the failure modes; treat the case studies as the composites they are.

Seat 7 on The Pareto 20 is Ravoid, and it covers two things a solo operator running agents worries about at 2 a.m.: an agent that keeps spending, and an agent that quietly hands out a key.

Who they are

Ravoid is a one-person publication written by Framesta Fernando, who describes himself as an engineering manager and technical architect with five years leading engineers on large backend systems. It publishes several times a week. Roughly half of the site is AI cost economics (GPU rental prices, per-seat pricing, usage billing) and the other half is agent security. The security half is why it is here.

What to read them for

Dashboards are not control. AI Agent Budget Enforcement (September 6, 2026) draws the line that most cost tooling blurs: "Dashboards record spend after the fact. Alerts notify humans after the fact. None of these can stop the next call." It sorts named tools into the ones that only observe and the ones that can actually block a request, and ends with a hardening checklist one person can ship in a day.

The tools nobody approved. Nobody Approved the MCP Tools Your Agents Use (July 23, 2026) is the shadow-MCP piece: connectors installed without review, carrying broad credentials. The verdict on the obvious fix is the useful part: "You cannot prohibit what you cannot detect, and a ban only drives the behavior further underground." Detection and a gateway, not a policy memo.

What the model reads that you do not. Your Agent Reads Tool Metadata You Never See (July 17, 2026) explains tool poisoning through descriptions the human never sees, and proposes pinning tool schemas so a connector cannot change under you.

Agents trusting agents. One Poisoned Agent Infects the Whole Chain (July 29, 2026): "Agents trust each other's outputs the way they trust a system prompt." If you chain agents, the second one has no idea the first was compromised.

A vendor claim, deflated. On long context (August 27, 2026): "Support for a 1M-token window is not the same as performance at a 1M-token window."

Start here

AI Agent Budget Enforcement. It is the piece most likely to save you money this month.

How to read the numbers

Ravoid's about page states that failure stories are "anonymised or composited and labelled as such." Not every article repeats that label at the top, so the dollar figures in its case studies (a $47,000 runaway loop, for instance) are illustrations, not incidents. Some articles also cite specific security advisories by number; we did not verify those against the public vulnerability databases and you should before repeating them. None of this weakens the arguments. It changes what kind of evidence they are.

What they sell, and what that means for you

The contact page offers consulting on architecture and invites sponsorships. We found no sponsored posts, no affiliate links, no course and no newsletter. The register is engineering leaders rather than solo operators, so expect to translate: the failure modes apply at any scale, the reference architectures assume a team.

Not for you if

You want a step-by-step for a one-person setup. Ravoid tells you what breaks and why; the smaller-scale how-to is yours to build.

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Part of The Pareto 20, twenty creators who get a solo operator most of the way on AI decisions. How we chose them. Facts above were checked against the creator's own pages on September 12, 2026.