You are the person everyone emails when a customer wants a refund, a contractor needs approval, or engineering asks whether a scope cut is acceptable. That flow is burning time and momentum. A decision proxy can represent your judgment, reliably, with an API. Get one working in 30 days and reclaim hours each week while keeping full auditability and control.
Why a decision proxy, and why now
Founders at $500K to $5M ARR are almost always the holder of context. You cannot hire that context overnight, and tools that only automate rules or run workflows miss the nuance. A decision proxy evaluates requests against the judgment you’ve already expressed: policies, precedents, playbooks, templates, and memory. It returns an outcome, a confidence score, and a readable audit trail. When confidence is low it escalates with the minimal follow-up question required.
Here is a concrete fact you can use to justify investing the time: B2B SaaS companies that systematically build and refresh content and processes see measurable returns; for example, teams publishing nine or more posts per month saw 35.8 percent more yearly Google traffic than infrequent publishers. The same discipline applied to decision-making—codify once, iterate—creates similar leverage over founder time.
How to set up a decision proxy in 30 days
Do not try to encode every edge case. The fastest path to value is to choose the two or three recurring decision types that eat the most of your time. Common winners are refunds and credits, vendor and expense approvals, hiring screens, and scope clarifications. Follow this week-by-week plan.
- Week 1: Map and prioritize, 3 hours. List all decision requests you handle weekly. Measure volume and minutes per request for a representative two-week window. Pick the top 2 decision types that total at least 40 percent of your time. Example: refunds (12/week, 15 minutes) and vendor approvals (6/week, 25 minutes).
- Week 2: Draft clear, short policies, 4 hours. For each decision type write a one-paragraph policy and 3 precedents: recent real examples with outcomes. Policies are hard rules, precedents are patterns that teach nuance. Upload these as context entries. DelegateZero documents on context and policies are a good reference: https://delegatezero.com/docs/context and https://delegatezero.com/docs/context/policies.
- Week 3: Run dry runs and tune, 6 hours. Use the API in dry_run mode or the dashboard chat to test 20 real past requests against your new context. Inspect where confidence is low. Two likely fixes: missing a single data field the proxy needs, or an ambiguous policy. Fix the policy or add a data extraction template, then rerun. The platform’s Decision Simulation feature helps here: https://delegatezero.com/docs/advanced-settings/decision-simulation.
- Week 4: Integrate and automate, 8 hours. Hook your inbox or Slack using the Gmail or Slack integrations so qualifying messages land in the proxy queue. Set scan sensitivity conservatively at first. Enable draft replies only; do not auto-send until you hit a sustained high confidence and low override rate. Docs: https://delegatezero.com/docs/integrations/overview.
After day 30 you will be handling fewer routine requests directly and more high-leverage exceptions. That is the goal.
Practical rules that scale
Policies should be short and testable. Prefer numeric thresholds or explicit tradeoffs. Examples that work:
- Refunds under $250 and less than 30 days from purchase, approve automatically unless there are active fraud flags.
- Vendor invoices under $1,000 and already on contract, execute payment; otherwise escalate to finance.
- A candidate moves to take-home exercise after one positive interview score from engineering and recruiter clearance.
When the proxy returns an execute or draft decision, it also returns a confidence score and the minimal reason. Use confidence thresholds empirically. Start at 0.8 and lower to 0.7 if you are comfortable, but track override rates. DelegateZero’s Confidence Autopsy and Decision Debt dashboards show where your policies are under-specified and where memory correction events are piling up: https://delegatezero.com/docs/advanced-settings/confidence-autopsy.
How to avoid common traps
Don’t try to remove yourself from all decisions. The right aim is to stop doing repeatable, low-variance work. Keep these guardrails:
- Make every auto-executed decision auditable with the reasoning text and a permalink you can share.
- Prefer escalation when essential context is missing rather than guessing. Conservative defaults create trust faster than being “helpful but wrong.”
- Measure what matters. Track autonomy rate, escalation rate, average confidence, and the override rate. Compare against your benchmarks monthly.
Teams that measure end up improving. Benchmarks matter; for B2B SaaS a blog conversion rate of 2 to 5 percent is a useful comparator for content programs. For decision proxies, use override rate instead of conversions: if your override rate is under 5 percent after 60 days, you are likely in a sustainable place.
You will get the biggest wins by starting small, measuring, and iterating. If you want a practical starting point, follow the quickstart and add two policies and three precedents today: https://delegatezero.com/docs/quickstart. The work pays back in reclaimed time, fewer late nights, and a faster company.
FAQs
What is a decision proxy and how does it work?
A decision proxy is an API-layer that encodes your judgment to handle repeatable, context-dependent choices. It accepts a plain-language request, consults stored context (policies, precedents, memory), weights relevance and freshness, then returns execute/draft/escalate with reasoning and an audit trail for transparency.
How can I trust an API to make customer-facing decisions?
Trust comes from auditable signals and conservative defaults. DelegateZero uses confidence thresholds, explicit policies, and shareable audit links so every decision shows what was consulted and why. When confidence is low it escalates with minimal questions instead of guessing, and every override feeds back into the system.
What's the difference between a decision proxy and workflow automation?
A decision proxy applies judgment using your context; workflow automation executes predefined triggers and steps. Proxies weigh policies, precedents, and behavioral memory to choose outcomes or escalate, while automation performs fixed actions without higher-order reasoning or auditable confidence scoring.
Will this replace hiring an EA or chief of staff?
No. A decision proxy reduces routine load but doesn't remove strategic human judgment. DelegateZero handles approvals, drafts responses, and surfaces escalations so senior hires focus on high-impact work, not repetitive context-gathering. It changes the role, it doesn't eliminate it.
How do I get started adding policies and precedents to a decision system?
Start with your biggest daily bottlenecks: load the clearest policies first, add a few representative precedents, and supply templates for common replies. Run dry-runs, watch where confidence drops, and iterate — small, high-fidelity context wins over broad, vague rules.