The Tool Desk
Outbyte Driver Updater FREEScan for outdated or missing drivers - takes under a minuteDriver Scan →Outbyte PC Repair FREEClear out junk files and repair common Windows errorsFree Scan →SaaStr founder Jason Lemkin says its AI revenue agent, 10K, makes 35,000 to 40,000 API calls a day across the applications it uses. One estimate put the annual cost of keeping that access pattern at up to $240,000. Lemkin’s proposed alternative is to copy relevant data into PostgreSQL and have the agent read the copy more often. The comparison is striking, but the article does not disclose the estimate’s assumptions or show that the database approach has been implemented or saved money.
What SaaStr says it was quoted
In his 2026 first-person account for SaaStr, Lemkin describes 10K making 35,000 to 40,000 API calls per day. He says the company received an estimate of up to $240,000 per year to continue running the agent as it then did.
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That is SaaStr’s reported estimate, not a published tariff or a general benchmark for AI agents. The article does not name the estimator, break down the amount by vendor, or explain the usage and pricing assumptions behind it. Lemkin says he did not yet know exactly what each vendor would charge. Readers therefore cannot use the figure to predict their own API bill.
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1Repair Windows errors before they cause bigger problems2Scan for outdated or missing drivers - takes under a minute3Clear out junk files and repair common Windows errorsWhy a Postgres mirror could reduce API calls
The proposed design is to copy useful data from a vendor’s system of record into a PostgreSQL database, then let the agent query that copy instead of repeatedly asking the vendor for the same information. A mirror can reduce calls to the original service when the agent’s work relies on data that can be copied and does not need to be fetched live each time.
#1 Best Overall
Lemkin describes a $5 PostgreSQL instance as the comparison point and writes: “But a $5 Postgres instance with no API limits against $240,000 a year is an easy call for an agent.” That frames the appeal of changing the access pattern; it does not establish that $5 is the total cost of a production-ready mirror. The article does not say what that amount includes, such as synchronization, security, reliability, engineering, or ongoing operations.
What the headline comparison leaves out
The choice is not simply a vendor API bill versus the price of one database instance. A mirror adds a second copy of important data that must be kept useful and trustworthy alongside the original system of record. SaaStr’s account acknowledges synchronization work and the possibility that the copy can drift out of date, but supplies no figures for those costs or their impact.
Rank #2
| Factor | What the account establishes | What a team must assess |
|---|---|---|
| API use and fees | 10K makes 35,000 to 40,000 calls a day, and SaaStr reports an estimate of up to $240,000 per year for its current pattern. | Which vendors charge for which calls, how usage is counted, and how much of the bill a mirror would actually avoid. |
| Database and duplicate-system costs | The article uses a $5 PostgreSQL instance as its comparison point. | Whether that instance meets the workload’s needs, and the costs of storage, security, availability, backup, and operating the copy; the account provides no total-cost figure. |
| Synchronization and maintenance | The author says the mirror must be synchronized and may diverge from the source. | How often data must update, how synchronization failures are detected and repaired, and who maintains the pipeline; no effort or cost is quantified. |
| Stale or divergent data | The article recognizes that a mirrored database can get out of sync with the system of record. | Whether delayed or inconsistent data is acceptable for each agent task, and what happens if the agent acts on an outdated record. |
What SaaStr has—and has not—reported doing
Lemkin says 10K tracked API use for a week and identified calls it could cut. The account does not state how many calls were eliminated or provide measured savings. It presents the PostgreSQL mirror as a proposed alternative, not a completed migration with published results.
He also recounts that SaaStr previously left its Marketo setup after being limited to 10 or 20 minutes of API use a day. That is Lemkin’s account of SaaStr’s experience, not a general statement about Marketo or a benchmark for other vendors.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.How to evaluate the same choice for your agent
Before treating a database mirror as cheaper, compare the costs and consequences for the specific data and vendors involved:
- Establish the real API baseline. Measure calls by vendor and task, and identify which calls are repetitive reads versus actions or requests that need current source data.
- Verify the pricing basis. Ask each vendor how it counts and charges for the relevant API use. A single estimate without its assumptions cannot show which vendor or behavior drives the total.
- Define acceptable freshness. Decide how recent the copied data must be for each agent task, and whether stale or conflicting records could cause a consequential mistake.
- Account for the whole mirror. Include the database, synchronization, monitoring, security, reliability, engineering, and ongoing maintenance rather than comparing API costs only with the instance price.
- Measure the result. Compare calls avoided and the mirror’s operating effort against the original access pattern; do not treat identified opportunities to cut calls as savings already achieved.
A mirror is most compelling when the agent repeatedly reads data that can be copied safely and the avoided API costs outweigh the work and risk of maintaining another representation of that data. If tasks require current vendor data or changes must be reflected promptly, the synchronization design and consequences of lag are part of the decision—not incidental details.
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