The irreducible epistemic atoms underlying the curriculum. 4,828 atoms across 8 types and 2 molecules
When cognitive load increases or stress appears, rely on pre-defined explicit sequences rather than intuitive ordering, because implicit sequences degrade under pressure while externalized protocols remain stable.
At each handoff point between sequential agents, specify the exact information contract (what specific output the next agent needs from the current agent) to make dependencies explicit and auditable.
Run independent agents (those with no input dependencies on each other) in parallel to compress total execution time, and serialize only those agents where one genuinely requires the other's output.
Identify the critical path (longest chain of dependent tasks) as the minimum project duration, recognizing that no amount of parallelization or additional resources can compress completion time below this constraint.
Distinguish artificial serialization (treating independent tasks as dependent) from premature parallelization (launching tasks before their dependencies resolve) by mapping actual information flow rather than assumed ordering.
Before any contested time block arrives, define the allocation rule (priority ordering, rotation schedule, or time-slice) that resolves contention in advance rather than negotiating access when the block arrives.
Before attempting to resolve paralysis between competing priorities, check whether all four Coffman conditions hold (mutual exclusion, hold-and-wait, no preemption, circular wait)—if so, violate any single condition to make deadlock structurally impossible.
When multiple goals compete for the same scarce resource, match the allocation mechanism to dependency structure—use priority queue when importance differs, rotation when all are equal, and time-slicing when multiple need access within the same period.
For each handoff between agents or pipeline stages, specify three components—defined output format, explicit expectations, and return protocol—to prevent ambiguous handoffs from creating bottlenecks.
Never add agents to sequential reasoning tasks—distribute additional agents only to genuinely parallel workstreams where coordination overhead is measurably less than throughput gain.
Set an explicit coordination budget as a percentage of total available hours (15-25% for most knowledge work), and require any new coordination mechanism to fit within that budget or displace an existing one.
Invest in implicit coordination mechanisms—shared mental models, conventions, templates, and routines—over explicit communication channels, because implicit coordination scales without consuming bandwidth as agent count grows.
For beneficial emergent behaviors, protect the conditions that produced them—keeping agents active, maintaining shared context, and adding lightweight observation—rather than formalizing the pattern into an explicit rule.
When performing ecosystem health assessments, examine agent pairs for three specific failure modes: conflicting outputs, throughput mismatches between producer and consumer, and resource competition for the same limited capacity.
Schedule agent addition reviews 7-14 days after deployment to verify whether actual coordination cost matches pre-addition estimates, removing the agent if cost exceeds estimate by more than 50%.
Before retiring any agent, map all dependencies by identifying what consumes its output, what constraints it enforces, and what failures it masks—then explicitly reroute, replace, or accept each dependency gap.
When removing an agent, execute graduated shutdown by reducing frequency or scope before full elimination, monitoring for hidden dependencies during the transition period.
During 30-minute coordination reviews, answer four diagnostic questions with evidence: which agents produced output, did outputs reach intended consumers, what was the coordination-to-work time ratio, and where did agents actively interfere.
For agents with weak coordination, design hand-off protocols by specifying what information transfers, in what format, and at what trigger point—then practice the hand-off deliberately in the next three executions.
Calculate your attention allocation by categorizing each task as ONLY ME (requires unique judgment), COULD DELEGATE (someone/something else can do it at 80%+ quality), or SHOULD NOT EXIST (adds no value), then delegate or eliminate everything outside ONLY ME to reclaim attention for highest-value work.
When your ONLY ME time falls below 50% of working hours, you have a delegation deficit requiring immediate correction, because spending the majority of your highest-value resource on work that doesn't require it violates the constraint optimization principle.
Before delegating a task, verify it is not ONLY ME by default rather than by necessity—if the task requires your unique judgment only because you've never built documentation, systems, or relationships to make it delegable, it's a disguised delegation candidate.
Default to the delegation hierarchy sequence: first ask 'can a system handle this?', then 'can a system handle 80% with a person handling exceptions?', and only then 'does this require full human judgment?'—to prevent systematic under-investment in systems.
When modifying organizational processes, surface embedded schemas first to distinguish processes encoding hard-won lessons (whose removal reintroduces risk) from processes encoding obsolete assumptions (whose removal reduces waste).