Qualify the job before the account
A promising feature flag software lead needs more than a company in the right sector. Confirm the job: rolling back a feature requires redeploying the entire application. Identify developers and on-call staff controlling feature exposure as the possible user group, then find who can authorize a pilot; the working buyer hypothesis is an engineering manager responsible for controlled releases.
Ask about the current workaround, environment variables and conditional branches maintained by hand, and what would make changing it worthwhile. Do not assign a budget or procurement timeline from company size, funding, or job title alone.
Use a category-specific qualification rubric
Use the calculator below to organize your judgment after reading the source. Unknown evidence should remain unknown. Its weights are a transparent prioritization convention, not a prediction of purchase probability.
| Dimension | Evidence to seek | Reason to pause |
|---|---|---|
| Problem | What happens when the flag service is unavailable? | The person cannot describe a recent instance of the problem. |
| Product fit | Can you rehearse a cohort rollout and rollback in a test environment with a documented default? | teams whose stack or latency requirements are unsupported |
| Timing | the product needs a staged rollout to a limited customer cohort | The proposed change has no confirmed date or relevance. |
| Implementation | Who can change exposure, and how will stale flags be removed? | fallback behavior, change history, and SDK support need testing in the actual application |
| Value | an authorized operator changes exposure and confirms the intended cohort behavior | The buyer and user disagree on what success looks like. |
Work through an illustrative assessment
Suppose the source says: “We want to enable a feature for a few accounts and turn it off quickly if it fails. Our environment variable approach is getting messy.” That supports investigating the problem, but it does not yet settle purchasing authority or technical compatibility. A reviewer should ask the two discovery questions above and preserve the answers beside the source.
Compare that with: A request for an experiment platform that does not describe release control. This weaker example should not receive the same pain or timing score. A relevant public topic is not evidence of a current evaluation.
Even a strong problem signal should be rejected when the need belongs to teams whose stack or latency requirements are unsupported. Qualifying out prevents a misleading promise and preserves time for a prospect the product can help.
Create a reviewable handoff
A qualified opportunity should contain the original evidence, a summary of the job, confirmed and unknown constraints, the buyer/user distinction, and an agreed next step. Keep a score attached to those facts so another teammate can challenge the conclusion.
Propose a pilot only when the critical gap is addressed: fallback behavior, change history, and SDK support need testing in the actual application. Evaluate the pilot through a real observation that an authorized operator changes exposure and confirms the intended cohort behavior, and keep that observation separate from the initial qualification score.
About these playbooks and examples
Prepared by DemandBolt with AI assistance as practical planning resources for people building and selling software. The category scenarios and message examples are illustrative, not quotations from real prospects or claims of customer results. Adapt the hypotheses to your product, verify original sources, and review capabilities before making an offer.
The workflow follows our first-customer guide and buying-signal review method. Our PyInvesting and Rae records distinguish actual internal work from targets. Published .