Institute the inspectable-function rule for AI data access as company-wide hygiene - and refuse to make it either a shared library or retroactive

August 11, 2026 at 2:45 PMtechnicalhigh

Situation

At the Friday AI Committee, Peter re-delivered the rule he had set once before and watched not land. He used Mini-Me as the worked example: AI helped create the capability, but AI is not part of the runtime function of accessing the repositories. Claude cannot get to Slack except through that function. It does not have the keys. He asked for exactly one thing - if you are pulling data in or out of a CIQ system, do it through a function that you write and could inspect - and explicitly declined two obvious extensions. He would not make it a shared implementation, because there is no value in building a library of these things and because forcing an MCP server would block people from experimenting with technology being stood up today. He would not apply it retroactively, because a year from now we are going to have 100 times as many tools running around the company, so he is way more worried about the giant tsunami of stuff that is coming. He named three reasons rather than one: inspectability, 100 percent repeatability, and teaching the company the right pattern, since Claude is going to make everybody at the company a developer and that is incredibly terrifying if we do not teach people to be better developers. He extended the bar to local models when asked, and licensed Michelle to publish the message with his name attached.

Reasoning

The rule is a bet about scale rather than about any current incident. Peter is not defending against a leak that happened; he is pricing what happens when a hundred non-engineers each wire an off-the-shelf connector into a system of record. The mechanism he constrains is the one that cannot be reviewed - a model deciding at runtime what to pull - and he leaves everything else free, because the exploration is the thing he actually wants and a centralised guardrail would kill it. He also had to spend some of his own accumulated permission here: he knows people invoke his name to bypass Michelle, said so out loud, and offered to go talk to the company directly to make clear that this is not a roadblock. Choosing to demonstrate from his own tool rather than assert a policy is deliberate - it makes the bar concrete and provably achievable rather than aspirational.

Additional Context

This was the explicit tomorrow-focus item from the 2026-07-30 reflection: the first delivery of this rule had failed silently and the test was whether anyone could repeat it back. It landed. Ryan Smith volunteered to be the guinea pig on company tooling in the same meeting, and by Aug 5 had filed CUSP-3473 turning it into a Customer Engineering department standard with Mission Control and butler-go as reference implementations - which is repetition back, in the strongest available form. Michelle also surfaced the second-order problem Peter created for her: people cite his laissez-faire stance to avoid review.

Observed Evidence

Direct transcript quotes across a 14-minute stretch of the AI Committee, plus his own follow-up in #announcements the same evening and again on Aug 3. Confirmed downstream by Ryan Smith filing CUSP-3473 on Aug 5 which cites the policy date and reproduces the three pillars back verbatim - inspectability, repeatability, safety.

Matching Patterns

70%
Constrain the Mechanism, Not the Access(keyword match on inspectable/function/data access, same technical category, generalizes from personally validated practice, applies the bar across org boundaries)
42%
Pragmatic Technical Middle Ground(curated interface enabling innovation while respecting boundaries)
20%
Lead by Example with New Tools(demonstrated from his own tool rather than asserting policy)

Confidence Breakdown

35/35
Evidence
28/30
Pattern
20/20
Source
14/15
Corroboration

Reasoning Depth Analysis

Org Signal:That the CTO will constrain one narrow mechanism and leave everything else open - and that he will spend a committee slot re-delivering a rule rather than escalating enforcement. It also signals that his own tool is the reference implementation, which means the bar is provably achievable by a non-specialist.
Who Affected:Everyone building with AI outside engineering - RevOps, marketing, finance, IT - which is precisely who the rule is aimed at and precisely who does not report to Peter. Michelle carries the enforcement load; Ryan volunteered to be the first audited case; Brady confirmed it binds local models too.
Precedent:Sets that AI hygiene is a design-time constraint rather than a runtime guardrail, and that the CIQ answer to a governance question is write the code, not buy the control. Also sets that Peter will publicly retract the loose reading of his own permissive stance when it is being used as cover.
Consequences:Real but unenforced by design - there is no way to enforce it, but I would like to start communicating it. The teeth come from Michelle publishing it with his name and from the AI Builds Board review gate, not from Peter.
Timing:Now because the volume curve is about to bend, not because of an incident. He said explicitly he cares little about the existing applications and a great deal about the hundredfold growth coming. Also now because the first delivery failed and he had committed the day before to re-delivering it personally.

Related Context

🎥
AI Committee Meeting - 2026-07-31

fathom

my ask is that if you are pulling data in or out of a CIQ system, just do it through a function that you write. The AI is super capable of doing that. ... Claude cannot get to Slack, except through that function. It does not have the keys.

💬
#announcements thread

slack

The key is repeatabilty. If your agent is calling a function that you can inspect, you KNOW what is going in/out of that data source. If the AI has direct access to a connector - it can do what it wants in the moment.

💬
#announcements thread

slack

constrain the data returned by different queries to only the columns you need. And remove write abilities you do not need. ... instead of having a generic function that does it have specific, hard coded functions that take a hard coded list of inputs. Then the llm cannot decide to do more than you intend.

Outcome

Held under pressure - extended unchanged to two new AI systems on 2026-08-15 with no policy fork and no per-system approval

Rating: 4/5

Decision ID: 7afc2f64-09c4-41d1-a7b9-323c551164d0