ASTRA Tech Fundamentals — examination objectives

F1.1 Given a short customer-facing situation, identify whether an offer is SaaS, provider-hosted, or installed on the customer's own systems, and name who operates the application, hosting environment, and customer-side components.

The candidate identifies the delivery model shown in an offer, separates provider-operated from customer-operated elements, and names who runs the application, hosting environment, and customer-side components without explaining how the underlying infrastructure or software works internally; the focus remains customer-facing.

F1.2 Given a short customer-facing situation, explain in plain words what an API and an integration mean, and name the two connected systems and the owner on each side.

The candidate explains APIs and integrations in customer-facing language, identifies the two systems being connected, and names the owner responsible on each side so the connection can be discussed without requiring knowledge of code, protocols, or implementation details in practice.

F1.3 Given a short customer-facing situation, distinguish a feature available today from one described as roadmap intent, and name the evidence that shows current availability or future intent.

The candidate distinguishes a feature available today from one described as roadmap intent, then names the evidence appropriate to each status so a customer conversation clearly separates present capability from future intent without turning a roadmap statement into a commitment.

F1.4 Given a short customer-facing situation, recognise what a release, version, or update means for a customer already using the product, including whether the customer's available product state changes.

The candidate recognises release, version, and update language in a customer situation and explains what each term means for an existing user, including whether the customer may receive new capability, fixes, compatibility changes, or a documented product state after release.

F1.5 Given a short customer-facing situation, identify whether an AI feature is built into the product, supplied by another provider, or passed to a third-party model, and name who operates the model.

The candidate identifies whether an AI capability is native to the product, supplied by another provider, or routed to a third-party model, then names who operates the model so responsibility for that customer-facing capability is described without implying engineering knowledge.

F2.1 Given a short customer-facing situation, explain compute, storage, and network in plain words and match each to the corresponding line on a supplied cloud quote.

The candidate explains compute, storage, and network in plain customer-facing terms and matches each concept to the relevant line on a supplied cloud quote, showing understanding of what the customer is paying for without describing technical implementation behind the service.

F2.2 Given a short customer-facing situation, distinguish usage-based billing from a fixed subscription and name what can make each customer's bill rise, fall, or remain unchanged.

The candidate distinguishes usage-based billing from a fixed subscription and names the factors that can change each bill, so a customer can understand whether charges depend on consumption, contracted access, or another stated pricing condition over the stated billing period.

F2.3 Given a short customer-facing situation, recognise a commitment, tier, and overage on a supplied quote and explain what each means for included use, limits, or additional charges.

The candidate recognises commitments, tiers, and overages on a supplied quote and explains what each means for included usage, thresholds, or additional charges, keeping the explanation tied to the quoted terms rather than choosing a commercial option for the customer.

F2.4 Given a short customer-facing situation, identify the pricing unit on a supplied offer—user, seat, transaction, GB, token, or API call—and name what the customer must count to estimate likely charges.

The candidate identifies the unit used to price a product, such as users, seats, transactions, gigabytes, tokens, or API calls, and names what the customer must count so expected usage connects to the corresponding billing basis shown on the offer.

F2.5 Given a short customer-facing situation, explain why an AI feature may be priced by tokens, requests, or minutes, and name the usage information a customer needs to estimate likely charges.

The candidate explains why an AI feature may be priced by tokens, requests, or minutes and names the information a customer needs, connecting AI activity to its charging unit without turning the explanation into a deal-level forecast or pricing choice.

F3.1 Given a short customer-facing situation, identify from a supplied data sheet what customer data the product collects, the stated storage region or residency, and who may access it.

The candidate identifies from a supplied data sheet what customer data the product collects, the stated storage region or residency, and who may access it, keeping the explanation focused on customer-facing data promises rather than technical storage design or engineering.

F3.2 Given a short customer-facing situation, distinguish retention, deletion, and backup, and recognise what each term means when it appears in a customer question.

The candidate distinguishes retention, deletion, and backup and recognises what a customer is asking when each term appears, separating how long data is kept, when it is removed, and whether another copy may remain under stated product or service terms.

F3.3 Given a short customer-facing situation, explain what a statement that customer data is not used to train models does and does not cover, and name the document where that promise is stated.

The candidate explains the scope of a statement that customer data is not used to train models, distinguishes what that statement does not establish, and names the document where the promise is stated so the customer can locate the commitment.

F3.4 Given a short customer-facing situation, recognise a dashboard, report, and export as different customer-facing data promises, and name what data, access, or product capability each needs to exist.

The candidate recognises a dashboard, report, and export as different customer-facing data promises and names what data, access, or product capability each requires before it can exist, avoiding the assumption that offering one automatically means the other two are available.

F4.1 Given a short customer-facing situation, explain identity and access in plain words and distinguish authentication—who may sign in—from permission—what that person may do.

The candidate explains identity and access in plain words, distinguishing authentication as confirming who may sign in from permission as defining what that person may do, so customer questions are answered without requiring knowledge of internal security architecture or implementation.

F4.2 Given a short customer-facing situation, recognise what encryption at rest and in transit protect, and name a customer concern those phrases alone do not answer.

The candidate recognises what encryption at rest and encryption in transit are intended to protect and names a customer concern those phrases alone do not answer, keeping the explanation within the evidence stated rather than implying complete security to customers.

F4.3 Given a short customer-facing situation, identify what a supplied security questionnaire question is asking and match it to the evidence type that answers it: policy, audit report, test result, or contract clause.

The candidate identifies what a security questionnaire question is asking and matches it to the evidence type that could answer it, choosing among policy, audit report, test result, or contract clause while staying within evidence recognition rather than security assessment.

F4.4 Given a short customer-facing situation, explain what SOC 2 and ISO 27001 reports can show a customer and distinguish those reports from proof that every control, product configuration, or customer environment is secure.

The candidate explains what SOC 2 and ISO 27001 reports can evidence for a customer and distinguishes those reports from proof that every control, product configuration, or customer environment is secure, keeping the claim within the supplied report's stated scope.

F4.5 Given a short customer-facing situation, identify whether an AI-security question concerns prompt injection, data exposure through AI tools, or model access, and name the team or owner responsible for the answer.

The candidate identifies whether an AI-security question concerns prompt injection, data exposure through AI tools, or model access, then names the team or owner for answering it, keeping the response focused on ownership rather than providing an engineering-level security solution.

F5.1 Given a short customer-facing situation, explain in plain words what a large language model, copilot, agent, and automation each do, and match a supplied product description to the correct term.

The candidate explains a large language model, copilot, agent, and automation in plain customer-facing language and matches a supplied product description to the correct term, focusing clearly on the customer-visible function rather than how its underlying technology is built internally.

F5.2 Given a short customer-facing situation, distinguish an answer based mainly on model training from one grounded with customer documents through retrieval, and name the additional information source retrieval needs.

The candidate distinguishes an answer based mainly on model training from one grounded with customer documents through retrieval, then names the additional information source retrieval requires without explaining model architecture, embeddings, indexing, or other internal mechanisms inside the underlying system.

F5.3 Given a short customer-facing situation, recognise hallucination, bias, and drift as named AI risks and match each to the expected control: human review, testing, or monitoring.

The candidate recognises hallucination, bias, and drift as named AI risks and matches each to the expected control of human review, testing, or monitoring, showing what a customer may ask for without conducting an AI risk assessment for that customer.

F5.4 Given a short customer-facing situation, identify what an AI claim in a supplied product description promises and match it to its evidence status: measured result, demo, pilot, or no supporting evidence yet.

The candidate identifies what an AI claim in a product description promises and matches the claim to its evidence status: measured result, demonstration, pilot, or no supporting evidence yet, keeping the task to claim-and-evidence recognition rather than product suitability judgement.

F5.5 Given a short customer-facing situation, distinguish human-in-the-loop operation from autonomous action and name the approvals or actions the supplied situation keeps with a person.

The candidate distinguishes human-in-the-loop operation from autonomous action and names the approvals or actions the supplied customer situation keeps with a person, making the boundary visible without designing an AI workflow or choosing the appropriate operating model for the customer.

F5.6 Given a short customer-facing situation, recognise safe and unsafe uses of AI tools in customer-facing work and select whether supplied information may be entered into the tool under the stated rules.

The candidate recognises safe and unsafe uses of AI tools in customer-facing work and selects whether supplied information may be entered into the tool under stated rules, applying the given boundaries without creating new data policy or granting an exception.

F6.1 Given a short customer-facing situation, identify the buyer roles in a supplied account—user, economic buyer, technical reviewer, security, procurement, and legal—and match each role to the approval or decision it owns.

The candidate identifies the buyer roles shown in a supplied account and matches each role to the approval or decision it owns, covering user, economic buyer, technical reviewer, security, procurement, and legal responsibilities without prescribing an account strategy or approach.

F6.2 Given a short customer-facing situation, explain what a proof of concept is for and name the three elements that should be stated before it starts: intended decision, success criteria, and stop condition.

The candidate explains the purpose of a proof of concept and names the three elements that should be stated before it starts: the intended decision, success criteria, and stop condition, keeping the explanation customer-facing without designing the proof of concept.

F6.3 Given a short customer-facing situation, recognise on a supplied quote, order form, or SLA what is included, what costs extra, and what is promised about uptime and support.

The candidate recognises on a supplied quote, order form, or service level agreement what is included, what costs extra, and what is promised about uptime and support, separating documented commitments from assumptions that are not written into the evidence provided.

F6.4 Given a short customer-facing situation, identify which customer promises, scope limits, dependencies, owners, and open actions must be recorded at sales-to-delivery handover.

The candidate identifies what must be recorded at sales-to-delivery handover, including customer promises, scope limits, dependencies, owners, and open actions, so the delivery team can see what must be honoured without requiring the candidate to plan how delivery is performed.

F6.5 Given a short customer-facing situation, recognise an AI claim in a supplied proposal that goes beyond the available evidence and select bounded replacement wording that matches the evidence.

The candidate recognises when an AI claim in a supplied proposal goes beyond the available evidence and selects bounded replacement wording that matches what is supported, without deciding whether the customer should buy or whether the product is suitable overall.