Agent builders
16 articles
Payments for machinesSettlement for AI work
Agents now buy model calls from machines run by many independent operators, often many times a second. That demand needs a layer between buyer and operator that routes each call, settles it, and records what was bought. This is the case for that layer, and what Tenzro does in it.
7 min read
Payments for machinesWhat a receipt for AI work proves
Agent payment schemes prove that a payment was made and that someone consented to it. Inference receipts prove that a machine produced an answer. Neither alone proves that the money matched the work. What each kind of evidence covers, where the gap is, and how Tenzro binds the two.
6 min read
Model routingSettling one job across many operators
A single agent task can touch several independent operators: a primary that stalls, a hedge that answers, a successor that takes over a session, expert shards held on different machines. How Tenzro routes that work, settles each operator for its own part, and what the buyer, each operator and an auditor can see.
6 min read
Payments for machinesPayment rails for machines
Invoices and cards assume a person, a merchant and an amount large enough to carry a fixed cost. Machines buying AI work need per-call settlement, payment channels for high-frequency calls and delegated spending under limits. How those rails work on Tenzro, and how they sit alongside x402 and AP2.
5 min read
Payments for machinesSpending limits and revocation for agents
When software spends money, someone has to answer for it. That takes a responsible party behind every agent, limits the agent cannot raise itself, and a revocation that stops payment on every rail at once. How each of those works on Tenzro, and why each has to be enforced outside the agent.
5 min read
Enterprise AIA Corporate AI Strategy for 2026: From Pilots to Production
Most enterprises use AI; few run it at scale. A practical framework for moving from pilots to production, with a clear answer to the question pilots skip: where the inference capacity comes from.
5 min read
Enterprise AIAgentic AI in the Enterprise: Delegation You Can Audit
When agents call tools and spend money, governance has to move from policy documents into the systems that authorise each action. A delegation model, a control checklist and the records an auditor will ask for.
5 min read
Edge AIAgentic Harnesses on Small Devices: Orchestrating From the Edge
Most of an agent's work is orchestration, not large-model inference. Why the harness belongs on small hardware near the data, what runs on a Tenzro edge node today, and what edge harness hosting will add once it ships.
5 min read
SafetyDesigning Safe Harnesses: Scopes, Limits, Expiry and Revocation
Prompt injection will sometimes succeed, so an agent's safety has to live outside the model. How Tenzro bounds every delegated agent with consensus-enforced scopes, spending limits, expiry, step-up approval and revocation, with an accountable root behind each one.
5 min read
Machine economyThe machine economy: agents, robots and devices as buyers
Software agents, robots and devices are starting to buy and sell AI work themselves. This briefing for decision makers covers what changed in 2025 and 2026, what a machine needs in order to transact safely, and the infrastructure questions to ask before letting machines spend.
5 min read
Machine economyMachines That Pay Machines: Accounting for Autonomous AI Work
When agents buy inference, data and compute from other machines, the hard parts are accounting, receipts, limits and settlement, not the payment rail. How Tenzro records each payment once, binds it to what was asked and delivered, and settles in the rails people already use.
5 min read
Model routingModel Ladders: Answer With Small Models, Escalate Only When Needed
Most requests do not need the largest model. What the research on cascades and routing actually shows, where it falls short, and how Tenzro routes by measured difficulty and closes the loop on escalation.
5 min read
Physical AIPhysical AI: Robots That Buy Compute and Sell Their Work
Robots and field devices increasingly need inference they cannot run on board, and produce data and work others will pay for. What it takes for a machine to transact safely: identity, budgets, placement and verifiable evidence.
5 min read
Voice AIVoice AI Latency Budgets: Serve Speech Close to the Speaker
People expect a reply within a few hundred milliseconds. A latency budget for voice agents, where each millisecond goes, and why speech recognition and synthesis belong near the user while the language model can sit further away.
4 min read
Hardware identityTDIP: one identity protocol for humans and machines
Humans, delegated agents and autonomous agents under one W3C DID method, with keys rooted in passkeys and device hardware. Why agents need an identity of their own.
2 min read
Payments for machinesPayments for AI agents: open rails, one network
x402, MPP, AP2, ACP and stablecoin wallets: why agents should not have to know which rail their counterparty accepts, and how Tenzro settles them all.
2 min read