Recently, we purchased one of each Anthropic/OpenAI subscription plan and randomly ran long horizon coding tasks until we exhausted the weekly limit. It's widely believed that a $200/month plan maxes out at ~$2000/month worth of tokens (assuming API pricing). However, we found that the subscriptions are actually far more generous. (2/4)
Semantic drift is becoming an infrastructure problem.
Latest article explores why execution admissibility may become a new control layer for automated systems:
“Semantic Drift Is Becoming a Supply-Chain Problem”
linkedin.com/pulse/semantic…#DLX#SemanticSystems#ExecutionControl
Most systems control actions after execution already started.
DLX focuses on an earlier boundary: whether execution itself is admissible before commitment occurs.
DLX semantic pipeline uses deterministic validation and reproducibility checks.
#DLX#SystemsDesign
Allowed ≠ Valid
Systems often assume prior approval remains valid at execution.
The workflow can be followed.
The logs can be complete.
And still: the action should never have been allowe
Because execution became binding under different conditions.
linkedin.com/pulse/allowed-…
Allowed ≠ Valid
AI didn’t fail.
It answered. Cited. Sounded certain.
And was wrong.
→ >60% incorrect
→ fabricated links
→ wrong > refusal
(CJR)
Not generation.
Execution.
Outputs used without validity at commit.
linkedin.com/pulse/allowed-…
Allowed ≠ Valid.
Most systems assume that once something is approved, it is safe to execute.
That assumption often fails at the moment it matters most — commit.
Wrote a breakdown on execution-bound control and admissibility:
medium.com/p/allowed-vali…#AIGovernance#AISafety
Most AI systems don’t fail because they lack validation.
They fail because they can still execute when validation fails.
Detection ≠ control.
If execution is still possible, governance is observation.
#AI#AIAgents
#AIEngineering
#securitynotpolitics#ExecutionControl
Allowed ≠ Valid
Something can be permitted, executable, and still wrong under the conditions it was approved under.
That is how invalid states become real without ever being explicitly approved.
New piece: linkedin.com/pulse/allowed-…
The system already knows the tool call failed.
And still exits cleanly.
That’s not robustness.
That’s failure being treated as success.
`invalid_tool_calls != no-call`
(langchain#33504)
#AIEngineering#LLM#AgentSystems
We asked an LLM to summarize DeciRepo.
It turned a bounded validation claim into broad enforcement.
That is the problem.
Drift rarely arrives as failure.
It arrives as wording drift:
“can verify”-“ensures”
“bounded surface”-“the system”
Control must live where execution begins.
The idea is already public.
FSM, admissibility, execution boundaries:
none of that is secret.
Anyone can describe the boundary.
The question is whether it still holds when execution begins.
That is where most systems fail.
#DeciRepo#Risk#AIGovernance
We let an LLM reconstruct our system from public materials.
It produced a stronger story than the sources supported.
Not communication.
Control failure.
Models remove conditions.
reviewed source != generated claim
Without a boundary check,
governance is just description.
A reviewed message said: no acceptance of liability, no settlement.
The version about to be sent implied settlement anyway.
That is not wording drift.
That is a system that cannot hold its own position.
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