The Last Honest Edge in Poker: Training Against the Machine
There's one thing an RTA user at the table can never do, and a player who trains against the engine does every day. It's the difference between winning a hand and owning the game.
Agent Startups
Agent startups: what they ship, what the demo hides
Check benchmark, cost, and fleet math before buying a robosecretary
Run a pre-buy check: public benchmark score, per-task cost, and fleet pricing assumptions before you deploy a computer-use agent.
Audit agent vendor end-to-end claims with three checks
Before trusting an AI employee vendor, map approval points, verify logged actions, and test agent handoffs.
Verify Five Controls Before Routing Agent Traffic
A control plane must prove identity, audit, data, approval, and cost controls before you route agent traffic through it.
Audit Agent Data Access in One Week
Agent access mapping is funded, and operators can still run a practical audit this week.
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Verify Devin Before Critical Path
Check unattended task boundary, decision telemetry, and cost-per-task math before putting Devin on production work.
Audit your agent stack before an over-privileged agent breaks production
An audit for operators: inventory active agents, map machine identities, enforce least privilege, block runtime abuse, and test containment.
Zenity's raise: operator checklist for visibility, enforcement, response
Use the raise as a signal to score agent-governance vendors on visibility, enforcement, and response.
Demo an AI Agent: Mode, Guardrails, One Measured Outcome
Pick the lowest-risk demo mode that still proves the business outcome, script guardrails, and close with a scoped pilot.
Score AI Agent Claims: Workflow Lock-In Beats Cost Cuts
A five-point scorecard separates impressive agent demos from defensible products: workflow lock-in, process data, integrations, compliance, and switching costs.
LLM Provider Routing Checklist for Agent Startups
Pick a primary LLM by task, define fallbacks, and route each agent call by context need, latency budget, cost ceiling, and fallback provider.
Ship a client-facing agent without cross-tenant leaks: the pre-launch isolation, billing, and data-boundary checklist
A client-facing agent is safe to sell only when runtime, memory, tools, billing, egress, and output checks are separated by tenant and tested before launch.
Price an AI agent by finished work, not seats
Set AI agent fees against the labor they replace, define the billable outcome tightly, and cap exposure with usage or escalation rules.
Hire the five roles that keep AI agents from breaking before scale
A hiring trigger checklist for operators deploying AI agents in production, built around runtime, audit, identity, evaluation, and support.
SOC 2 for AI agents: five controls to prove
A practical SOC 2 checklist for AI agent operators: prompt scope, tool permissions, data lineage, access controls, and audit logs.
Cut AI Agent Inference Costs Without Losing Reliability
Treat every agent task as a priced unit, then classify, route, cache, batch, and instrument it to cut inference cost without breaking reliability.
Ship the smallest agent that survives a paid pilot
Ship a minimum agent pilot with one scoped task, evals, one integration, a sandbox, guardrails, audit log, rollback, and a paid success metric.
Pick the AI agent workflow that pays before building
Use a workflow score to choose a profitable AI agent build before writing code.
Pass Enterprise Procurement: AI Agent Evidence Checklist
A four-part checklist for AI agent startups to pass enterprise procurement: identity controls, isolated data, action logs, and human approval thresholds.
AI Agent Startup Funding: Durable Workflow, Not Model Access
Early-stage investors want workflow proof, architecture, metrics, security, enterprise proof, and unit economics.
AI Agent Model-Change Release Gate: Evals, Guardrails, SLAs
Gate every model update with regression evals, shadow traffic, guardrail checks, SLA tests, staged rollout, and rollback triggers before customers feel it.
Find 10 Paying AI Agent Customers by Scoring Public Pain and Timing
Mine public conversations, score prospects on pain, fit, timing, reachability, and evidence, then pitch outcome-based pilots.
Deploy AI Undercover Agents That Hold Up in Court
Undercover AI agents can support investigations only when operators pre-approve legal authority, supervision, evidence capture, and exit rules.