Use when producing or reviewing the saas agent unit economics and cogs component of a business plan; applies its specialist evidence, decisions, and acceptance tests instead of neighbouring pipeline skills.
Use when producing or reviewing the saas agent unit economics and cogs component of a business plan; applies its specialist evidence, decisions, and acceptance tests instead of neighbouring pipeline skills.
Generic AI unit economics treats one user query as one LLM call. Agent unit economics is fundamentally different: one user request triggers a planner step, N worker steps, M tool invocations, possible retries, possible parallel branches, possible critic / supervisor calls, possible human-in-the-loop (HITL) escalations. A single resolved customer-service ticket can be 15-40 LLM calls and 5-15 tool invocations. A single "deep research" outcome can be hundreds of LLM calls. The cost waterfall is multiplicative, not additive, and investors will not accept generic AI cost models for agent products.
This skill installs the agent COGS discipline:
Agent direct COGS — LLM tokens at each step (planner + workers + critic), tool invocations, external API cost, retry overhead, branch cost, HITL escalation cost.
Agent overhead allocation — share of Agent Architect / Tool Engineer / Eval Engineer / AI Safety Lead / HITL Designer payroll.
Together these produce cost-per-task, cost-per-resolved-task (the true unit because unresolved tasks still cost money), , , and the diagnostic.
agent gross margin
intervention-cost overhead
agent-cost-as-%-of-agent-revenue
Use When
A SaaS / ICT plan includes an agentic or multi-agent product (single agent, planner-worker-critic, or vertical agent)
Section 10 is being built for an agent-product plan
Pricing must be set on per-resolution / per-outcome / per-step basis and needs cost floor
Investors / DFIs have asked for cost-per-resolved-task specifically
An existing AI-SaaS is moving up the autonomy ladder (assist -> suggest -> supervise -> agentic) and per-query economics no longer model reality
The plan must pass meta-agent-bankability-and-investor-readiness
Do Not Use When
The AI feature is a single-shot completion (translate, summarise, classify) with no multi-step planning or tool use — use saas-ai-unit-economics-and-cogs
The product is internal-efficiency only with no customer-facing agent
The business is not SaaS / subscription / usage-based recurring
Required Inputs
Agent architecture description: single-agent or multi-agent; planner / worker / critic decomposition; tool registry (which tools, which providers, per-invocation cost)
Per-agent-step model assignment (which step uses which model — frontier vs cheap-router)
Average step count per task by task class (resolved, escalated, failed, abandoned)
Average parallel-branch fan-out where applicable
Retry policy and observed retry rate
HITL escalation rate (% of tasks escalated to human; cost per HITL minute)
Currency exposure (USD-denominated LLM + tool cost vs local-currency revenue)
Workflow
Document the agent architecture — one paragraph + a step-and-tool diagram (or text decomposition: planner step -> N worker steps -> tool calls -> critic -> finaliser). Without this, cost modelling is fiction.
Define the task taxonomy — by class (resolved, escalated-to-HITL, escalated-to-human-final, failed, abandoned, looped-and-killed). Each class has different cost.
Build the per-task cost decomposition using references/saas-agent-unit-economics-template.md:
LLM cost per task = sum over steps of (input tokens x input rate + output tokens x output rate) x model-mix factor
Tool cost per task = sum over tool invocations of per-invocation tariff (some tools are flat per call, some metered)
External API cost per task (separate from tools where vendor lock-in or auth differs)
Retry overhead = LLM cost x retry rate x average retry depth
Branch overhead = (parallel-branch factor - 1) x base step cost (where applicable; multi-agent products)
HITL escalation cost = (HITL minutes per escalated task x fully-loaded HITL hourly rate / 60) x HITL escalation rate
Supervision overhead = supervisor / critic call cost per task
Cost per task = sum of above. Compute weighted average across task classes.
Cost per resolved task (the true unit) = total agent operating spend / number of resolved tasks. This is materially higher than cost-per-task because unresolved / failed / abandoned tasks still consume cost and must be amortised across the resolved outcomes. Investors will quote this number.
Agent gross margin = (agent-attributable revenue - agent COGS) / agent-attributable revenue. Use revenue attribution discipline (per-resolution pricing tracks directly; tier-bundled agent revenue must be attributed honestly).
Agent contribution margin per pricing model — for per-resolution, per-outcome, per-step, per-agent, hybrid. Identify which pricing models leave thin or negative margin.
Apply mitigation levers in scenarios:
Step compression — collapse planner + worker into single-shot for routine tasks (saves 30-50%)
Model downshift on routine steps — route low-stakes steps to cheap-router model (saves 40-70% on those steps)
Tool result caching — cache deterministic tool outputs (saves 20-40% of tool cost)
When the agent product carries SLA commitments (uptime, accuracy, response time, definition-of-done), the cost waterfall must classify SLA-related cost lines correctly. The full discipline lives in saas-agent-sla-cogs-treatment/SKILL.md; the summary classification:
Cost line
Classification
Rationale
HITL labour deployed to defend SLA (escalations from SLA-relevant cases)
Less: Agent COGS including HITL-for-SLA + SLA infra + SLA evals + SLA-driven retraining amortisation + redundancy
= Agent gross profit / agent gross margin
Common error. Classifying SLA credits as G&A or as a below-the-line item. This overstates gross margin and revenue; auditors will adjust.
Reserve link. SLA-credit reserve (saas-agent-deferred-revenue-and-credit-reserves) lives on the balance sheet; the P&L recognises the period's SLA-credit accrual as contra-revenue.
Cross-reference.saas-agent-sla-cogs-treatment/SKILL.md and saas-agent-sla-cogs-treatment/references/saas-agent-sla-cogs-policy.md.
Living-Plan Agent Cadence Defaults
Element
Cadence
Owner
Variance threshold
Cost per resolved task
weekly
CFO + Head of Agent
+15% WoW
Cost per task (weighted)
weekly
CFO + Head of Agent
+10% WoW
Intervention rate
weekly
HITL Designer + Head of Agent
+3pp absolute
Task success rate
weekly
Eval Engineer
-3pp absolute
Tool-invocation reliability per tool
weekly
Tool Engineer
tool error rate >2%
Branch / loop ceiling breaches
weekly
Eval Engineer
any breach
HITL escalation cost share
monthly
CFO
>25% of agent COGS
Agent gross margin
monthly
CFO
-3pp MoM
Provider pricing watch
monthly
Head of AI / CTO
any change
Retry-overhead share
monthly
Tool Engineer
>15% of LLM cost
Tool-cost share
monthly
Tool Engineer
>30% of agent COGS
Model-migration reserve
quarterly
CFO + Head of AI
reserve drawdown
Irreversibility-incident reserve
quarterly
CFO + AI Safety Lead
any drawdown
References
references/saas-agent-unit-economics-template.md — formulas, worked example, COGS waterfall
skills/10-financial-projections/saas-agent-revenue-recognition/SKILL.md — ASC 606 / IFRS 15 per pricing primitive
skills/10-financial-projections/saas-agent-sla-economics-in-projection/SKILL.md — SLA performance as projection driver
Africa / Uganda Application Notes
Agent LLM + tool cost is USD-denominated; revenue often local currency. Per-resolution pricing must include FX corridor; the agent unit economics must hold across +/-20% FX swing (UGX 3,500-3,900/$, NGN 1,500-1,800/$, KES 128-145/$ as 2025/26 ranges).
HITL cost in Uganda / Kenya / Nigeria / Rwanda is materially lower than US benchmarks (UGX 4,000-8,000/hour fully-loaded vs USD 30-60/hour US); this shifts the agent-vs-human economics — agents in Africa must beat a much lower human cost floor, and HITL fallback is cheaper to operate. Model both directions.
Tool integration costs in Africa skew higher because of fragmented enterprise SaaS adoption — many tools are not yet API-first, requiring custom connectors. Model integration build cost as part of agent product cost, not as overhead.
For agents serving WhatsApp / USSD / SMS / IVR channels, channel costs are real per-task line items (WhatsApp Business API per-conversation tariff; USSD aggregator per-session fee; SMS per-message; IVR per-minute). Add channel-cost line to per-task decomposition.
In-region GPU for fine-tuned worker models (af-south-1, africa-south1, Liquid, Cassava, Raxio, Ethiopian AI Institute) prices 1.5-3x US/EU; model in-region inference premium if data residency is required.
Cache-hit ratios in African vertical agents tend to be higher than US benchmarks because user task distributions are more concentrated (e.g. agri-extension agents see top 30 questions account for 60% of volume); model 40-60% cache.
Audit-log retention costs in Africa can become binding when regulators (KE ODPC, NG NDPC, UG NITA-U, ZA Information Regulator) require multi-year retention; cost the retention period explicitly.
Sovereign-AI procurement (KE Talanta, RW innovation, NG NITDA, ZA Presidential 4IR, EG infra) may require local hosting that raises per-task cost 30-80%; reflect in pricing if applicable.
July 2026 Portable Contract
Required Inputs
Input artefact
Source/provider
Required
Behaviour when absent
Approved commercial assumptions, contracts, usage/cost evidence, accounting framework, opening position, and projection horizon for saas agent unit economics and cogs
Client records, approved operating model, finance owner, and accounting doctrine
Yes
If absent, contract terms, usage evidence, framework, or cost drivers are unavailable, isolate the affected schedule, label it unassessed, and do not force the model to balance with a plug.
Finalised business brief, target reader, country, and stage
Client intake and engagement owner
Yes
Stop section decisions and route the missing context to client intake.
Reconciled upstream assumptions that this section consumes
Named pipeline owners
Conditional
Record the dependency, affected claim, owner, and recovery step; do not substitute an invented value.
Outputs
Artefact
Consumer
Observable acceptance condition
Unit-economics model with task or tenant cost bridge
Plan author and target decision-maker
The artefact answers the section decision and traces each material conclusion to the supplied evidence.
saas agent unit economics and cogs exception and handoff note
Downstream section owners
Every blocked or conditional item names its consequence, owner, evidence request, and restart condition.
saas agent unit economics and cogs release record
Reviewer or plan assembler
Records the checks completed, failures, unassessed items, professional review required, and release state.
Evidence Produced
Evidence
Format
Acceptance condition
Formula trace, source/assumption register, three-statement or schedule reconciliation, and finance-gate record
Source-linked table, calculation, or annotated prose
The evidence is reproducible from named inputs and distinguishes verified fact, management assumption, and inference.
saas agent unit economics and cogs decision record
Decision note
States the selected action, rejected credible alternative, countercase, rationale, and risk accepted or avoided.
saas agent unit economics and cogs review trace
Gate entry
Identifies the date, input versions, reviewer role, failed checks, recovery owner, and any check that remains not assessed.
Capability and Permission Boundaries
For saas agent unit economics and cogs, the controlling focus is cost per completed task, attempted-versus-completed usage, tool costs, human review, and contribution margin. This skill may inspect records and calculate planning scenarios in read-only mode; it may not post entries, change ledgers, set accounting policy, certify IFRS treatment, or release statutory values without authorised professional review. Its normal mode is read-only analysis and drafting. Any mutation, external communication, spending, certification, or professional conclusion outside that boundary requires explicit authority and must remain traceable to the approving role.
Degraded Mode
For saas agent unit economics and cogs, loss of evidence about cost per completed task, attempted-versus-completed usage, tool costs, human review, and contribution margin activates degraded mode. If the controlling saas agent unit economics and cogs evidence is unavailable, the same boundary applies. When contract terms, usage evidence, framework, or cost drivers are unavailable, isolate the affected schedule, label it unassessed, and do not force the model to balance with a plug. Return the verified subset, label the affected decision qualified or not assessed, explain the downstream consequence, and state the smallest evidence request or authorised action that permits recovery. Do not convert the missing check into a pass.
Decision Rules
Choice or condition
Action
Failure or risk avoided
For saas agent unit economics and cogs, commercial billing, cash receipt, service delivery, and accounting recognition occur in different periods
model each event separately, reconcile the bridge, and route judgemental treatment to the finance reviewer
Cash, revenue, liability, and margin can be conflated into a misleading forecast
For saas agent unit economics and cogs, A current legal, regulatory, tax, accounting, market, or platform claim controls the saas agent unit economics and cogs decision
Verify the controlling source, effective date, jurisdiction, and reviewer status before release
Stale external facts become permanent plan assumptions
For saas agent unit economics and cogs, The evidence reconciles with neighbouring sections and the countercase does not overturn the choice
Complete unit-economics model with task or tenant cost bridge, attach the evidence and release record, and hand off named dependencies
Premature release and repeated downstream rework
Workflow
Define the exact saas agent unit economics and cogs decision, intended reader, jurisdiction, business stage, and permission boundary.
Collect approved commercial assumptions, contracts, usage/cost evidence, accounting framework, opening position, and projection horizon and map each material conclusion to its source; stop the affected conclusion when an input could change it.
Apply the specialist methods and directly linked references already contained in this skill, retaining its domain thresholds, calculations, and Uganda or East Africa context where applicable.
Compare the credible alternatives, test the countercase and failure path, and apply the decision table rather than selecting a template default.
Produce unit-economics model with task or tenant cost bridge with the evidence, exception, and handoff records; reconcile every shared assumption with its owning section.
Run the section quality checks, applicable finance or professional review, and anti-slop gate. If a gate fails, correct the evidence or decision and return to the responsible step.
Quality Standards
Unit-economics model with task or tenant cost bridge must answer a real decision for the named bank, investor, DFI, grant, board, or strategic-partner reader.
Formula trace, source/assumption register, three-statement or schedule reconciliation, and finance-gate record must be source-linked, dated where facts can change, and sufficient for another reviewer to reproduce the conclusion.
The section exposes its countercase, stop condition, recovery action, and effect on neighbouring sections.
No unavailable source, calculation, tool, or professional review is reported as passed; finance and statutory judgements follow the governing doctrine.
Language remains specific to saas agent unit economics and cogs, uses British English naturally, and passes the repository anti-slop gate without promotional filler.
Anti-Patterns
In saas agent unit economics and cogs, treating an unavailable approved commercial assumptions, contracts, usage/cost evidence, accounting framework, opening position, and projection horizon as confirmed. Correction: qualify the affected conclusion and issue the named evidence request.
Producing unit-economics model with task or tenant cost bridge that restates the brief but makes no choice. Correction: record the choice, rejected alternative, rationale, countercase, and implication.
Ignoring a conflicting upstream assumption. Correction: return it to its owning section and resume only from a reconciled version.
Reporting an unavailable check as passed. Correction: mark it not assessed and narrow the release state.
Claiming compliance, assurance, bankability, or investor readiness from narrative quality. Correction: run the applicable gate and retain its evidence.
Copying the worked example into a client plan. Correction: use the method only and replace every fact with verified engagement evidence.
Worked Example
An agent attempts three tool calls for every completed task and sends 15% to human review. Cost attempts, completion, tool fees, and reviewer time separately before setting the contribution-margin threshold.
References
Use the verified project evidence register and the owning upstream pipeline section for saas agent unit economics and cogs; no local deep-dive reference is declared.
For saas agent unit economics and cogs claims involving money, tax, grants, reserves, revenue, cost, valuation, or financial statements, apply the Chwezi finance doctrine and record the required professional-review state; illustrative figures never become client facts.
