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Agentic AI
multi-agent-orchestrator
multi-agent orchestration
subagents, workflows
System
Techniques · 20
Primitives · 95
multi-agent-orchestrator
Actor model
concurrency · medium: Isolated units of state that interact only by queued messages and handle one at a time: no locks on state, and the same code runs local or remote.
›
Durable job queue
distributed · medium: Persisted tasks that workers lease for a visibility timeout, ack on success and retry with backoff; at-least-once execution that survives worker and queue crashes.
›
Durable workflow execution
distributed · medium: Ordinary code made crash-proof by logging every side-effect result and replaying the code from that log; activities run at least once, workflow logic must be deterministic.
›
Usage metering
finance · medium: Counting tokens/requests per user and key, aggregating for quotas and billing with idempotent events
LLM-as-judge
machine-learning · medium: Grade open-ended outputs with a language model under a rubric, then correct its known biases by order swapping, voting and calibration against human labels.
›
Human-in-the-loop approval
agentic-ai · medium: Classify each proposed action as auto, ask or deny; park asks as durable pending records a human approves, edits or rejects, executing once, with timeouts that deny.
›
Memory consolidation
agentic-ai · medium: Periodically merge near-duplicate memories, resolve contradictions, decay the unused and cap the store, so an agent's long-term memory stays small, current and cheap to search.
›
Leases
distributed · low: A lock that expires on its own: bounded-time ownership that survives crashes and partitions, given bounded clock drift and fencing tokens on writes.
›
Idempotency keys
finance · low: Client-chosen unique key per logical operation, stored with a request fingerprint and the final response, so retries replay the first result instead of acting twice.
›
Exponential backoff with jitter
systems · low: Retry after delays that grow geometrically and are randomized, so failed clients spread out instead of hammering a recovering service in synchronized waves.
›
Event sourcing
finance · low: Persist state changes as an append-only stream of immutable events per entity; current state is a fold over them, guarded by expected-version appends.
›
Topological sort
graphs · low: Order the vertices of a DAG so every edge points forward; the core of build systems, schedulers and dependency resolution, with cycle detection for free.
›
Agent memory
agentic-ai · unknown:
Agent tracing
agentic-ai · unknown:
Agent workflows
agentic-ai · unknown:
Context window management
agentic-ai · low: Keep an agent's growing history inside the model's window by truncating, clearing and summarizing old turns in a cheap-to-lossy ladder, at turn boundaries.
›
Prompt caching
agentic-ai · low: Reuse the attention keys/values of a repeated prompt prefix, so an agent's growing context is prefilled once and later turns pay only for the new tokens.
›
Subagent orchestration
agentic-ai · unknown:
Task planning
agentic-ai · unknown:
Self consistency voting
ml-training · low: Sample several answers and pick by majority or execution agreement to raise reliability
Git object model
storage · low: Content-addressed blobs, trees, commits and refs; packfiles with delta compression; worktrees
Cooperative scheduling
concurrency · low: Green threads/coroutines yielding at await points on a user-space scheduler
MPMC bounded queue
concurrency · low: Vyukov's array queue for many producers and consumers: each slot carries a sequence number, so one CAS per operation claims a slot without locks.
›
+ 13 more techniques
+ 79 more primitives
System
Techniques · 20
Primitives · 95
multi-agent-orchestrator
Actor model
concurrency · medium: Isolated units of state that interact only by queued messages and handle one at a time: no locks on state, and the same code runs local or remote.
›
Durable job queue
distributed · medium: Persisted tasks that workers lease for a visibility timeout, ack on success and retry with backoff; at-least-once execution that survives worker and queue crashes.
›
Durable workflow execution
distributed · medium: Ordinary code made crash-proof by logging every side-effect result and replaying the code from that log; activities run at least once, workflow logic must be deterministic.
›
Usage metering
finance · medium: Counting tokens/requests per user and key, aggregating for quotas and billing with idempotent events
LLM-as-judge
machine-learning · medium: Grade open-ended outputs with a language model under a rubric, then correct its known biases by order swapping, voting and calibration against human labels.
›
Human-in-the-loop approval
agentic-ai · medium: Classify each proposed action as auto, ask or deny; park asks as durable pending records a human approves, edits or rejects, executing once, with timeouts that deny.
›
Memory consolidation
agentic-ai · medium: Periodically merge near-duplicate memories, resolve contradictions, decay the unused and cap the store, so an agent's long-term memory stays small, current and cheap to search.
›
Work-stealing deque
concurrency · medium: Per-worker deque: the owner pushes and pops at the bottom without contention, idle workers steal from the top; the core of Rayon, Tokio and Go.
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DAG workflow execution
distributed · medium: Run a graph of dependent tasks by releasing each one when its inputs are done, longest chain first, and skip any task whose input hashes are unchanged.
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HNSW
search-sort · medium: Hierarchical Navigable Small World: a layered proximity graph searched greedily from a sparse top layer; the default in-memory approximate nearest-neighbour index.
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Rollup aggregation
storage · medium: Fold raw events into one mergeable partial aggregate per time bucket and dimension key, then merge fine buckets into coarser ones, so long ranges read few rows and stay exact.
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Distributed tracing
systems · medium: Give each request a 128-bit id, record timed spans linked by parent ids, pass the ids in a header across every hop, and join the spans back into a tree afterwards.
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Telemetry sampling
systems · medium: Head, tail and dynamic sampling of traces, events and logs to a budget
Near-duplicate detection with MinHa…
machine-learning · medium: Estimate set Jaccard similarity from k min-hashes and find similar pairs with banded LSH buckets; the standard dedup for web crawls, training corpora and sequence collections.
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Tamper-evident audit log
security · medium: An append-only log whose Merkle root, signed per batch, lets anyone verify an entry is present and history was never rewritten, with log-size proofs.
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Columnar storage
storage · medium: Store each column contiguously so analytic scans read only the columns they need, compress well and run as tight SIMD loops.
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Entity resolution
storage · medium: Decide which records describe the same real-world thing: block to cut the pair space, score pairs with a probabilistic model, cluster the matches transitively.
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Record linkage
search-sort · medium: Probabilistic record matching (Fellegi-Sunter) with blocking for patient or entity indexes
Inverted index
storage · medium: Map each term to a sorted, compressed list of the documents containing it; the core of full-text search and other fast set queries.
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Vectorized execution
storage · medium: Query operators pass batches of about 1-2K values per column instead of single tuples, amortizing interpretation overhead and enabling tight SIMD loops.
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Leases
distributed · low: A lock that expires on its own: bounded-time ownership that survives crashes and partitions, given bounded clock drift and fencing tokens on writes.
›
Idempotency keys
finance · low: Client-chosen unique key per logical operation, stored with a request fingerprint and the final response, so retries replay the first result instead of acting twice.
›
Exponential backoff with jitter
systems · low: Retry after delays that grow geometrically and are randomized, so failed clients spread out instead of hammering a recovering service in synchronized waves.
›
Event sourcing
finance · low: Persist state changes as an append-only stream of immutable events per entity; current state is a fold over them, guarded by expected-version appends.
›
Topological sort
graphs · low: Order the vertices of a DAG so every edge points forward; the core of build systems, schedulers and dependency resolution, with cycle detection for free.
›
Agent memory
agentic-ai · unknown:
Agent tracing
agentic-ai · unknown:
Agent workflows
agentic-ai · unknown:
Context window management
agentic-ai · low: Keep an agent's growing history inside the model's window by truncating, clearing and summarizing old turns in a cheap-to-lossy ladder, at turn boundaries.
›
Prompt caching
agentic-ai · low: Reuse the attention keys/values of a repeated prompt prefix, so an agent's growing context is prefilled once and later turns pay only for the new tokens.
›
Subagent orchestration
agentic-ai · unknown:
Task planning
agentic-ai · unknown:
Self consistency voting
ml-training · low: Sample several answers and pick by majority or execution agreement to raise reliability
Git object model
storage · low: Content-addressed blobs, trees, commits and refs; packfiles with delta compression; worktrees
Cooperative scheduling
concurrency · low: Green threads/coroutines yielding at await points on a user-space scheduler
MPMC bounded queue
concurrency · low: Vyukov's array queue for many producers and consumers: each slot carries a sequence number, so one CAS per operation claims a slot without locks.
›
Dead-letter queue
distributed · low: A side queue for messages that keep failing: after N delivery attempts or a permanent error, park them with the reason so the main queue keeps moving.
›
Write-ahead log
storage · low: Append each change to a checksummed sequential log and fsync it before touching data pages; the basis of crash durability in nearly every database.
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Record replay
distributed · low: Record every nondeterministic input (time, randomness, I/O, model and tool outputs, per-tick player input) and re-execute deterministically for debugging, replays and state rebuild
Hierarchical timing wheel
systems · low: Timers bucketed by expiry into wheels of slots, coarser wheels for far deadlines: O(1) insert and cancel for millions of timeouts.
›
Sharded counters
concurrency · low: Split one hot counter into per-core or per-thread cells on separate cache lines; increments stay local and reads sum the cells.
›
Event deduplication window
distributed · low: Keep the ids of recently accepted events for a time window and drop repeats; memory stays bounded by rotating time buckets instead of per-entry timers.
›
Token sampling
ml-training · low: Turn a vector of scores into one chosen item with temperature, top-k, top-p, min-p, repetition penalties and a seed.
›
Annotator agreement
statistics · low: Inter-annotator agreement measures: Cohen and Fleiss kappa, Krippendorff alpha, gold-question accuracy
Bradley terry model
statistics · low: Pairwise comparison model P(i beats j)=s_i/(s_i+s_j); MLE fit, link to Elo and reward models
Statecharts
graphics · low: State machines with nesting, parallel regions, history and entry/exit actions, so UI and animation logic stays linear in size instead of exploding.
›
Dual control approval
security · low: Four-eyes / maker-checker approval with quorum policies for sensitive operations
Embeddings
machine-learning · low: A learned table mapping discrete ids to dense vectors: gather forward, sparse scatter-add backward, row-wise optimizers to keep huge tables cheap.
›
Time decay scoring
search-sort · low: Scoring items by recency with exponential decay or half-life, combined with relevance
Epoch-based reclamation
concurrency · low: Threads announce a global epoch while touching shared lock-free data; garbage retired in epoch e is freed once the epoch reaches e + 2.
›
Memory ordering
concurrency · low: What Relaxed, Acquire, Release and SeqCst atomics actually guarantee, what they cost on x86 and ARM, and which one each pattern needs.
›
Content-addressed storage
storage · low: Store each blob under the hash of its bytes: immutable, deduplicated by construction, self-verifying on every read, and composable into Merkle trees.
›
d-ary heap
data-structures · low: Array heap with d children per node (d = 4 typical): half the binary heap's depth, siblings in one cache line, faster priority queues.
›
SIMD programming
hardware-os · low: Process 4-16 lanes per instruction with AVX2, AVX-512 or NEON via Rust std::arch, with runtime dispatch and a portable fallback.
›
PRNGs (PCG, xoshiro)
numerics · low: Small, fast, statistically strong non-cryptographic generators: PCG32 and xoshiro256**, with seeding, parallel streams and unbiased ranges.
›
Scalar quantization
search-sort · low: Per-dimension int8/binary quantization of vectors with rescoring
Hash aggregation
storage · low: GROUP BY via hash tables with partitioning and spill to disk
Time partitioning
storage · low: Cut a table into fixed-interval time blocks so queries read only overlapping blocks and retention drops a whole block as one metadata change.
›
Distributed ID generation
distributed · low: Mint unique, roughly time-sorted IDs on many nodes with no per-ID coordination: Snowflake (time, worker, sequence) or UUIDv7 (time, random).
›
Protobuf wire format
networking · low: Protocol Buffers wire format: tags, varints, length-delimited fields and schema evolution
Hash based sampling
data-structures · low: Deterministic sampling by hashing an entity id so all its events are kept or dropped together
Reservoir sampling
data-structures · low: Uniform k-sample from a stream of unknown length (Algorithm R/L)
Token bucket
systems · low: A bucket of up to b tokens refilled at rate r; requests spend tokens, enforcing an average rate while allowing bursts of b.
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Fast hash functions
data-structures · low: Non-cryptographic hashes built from 64×64→128-bit multiplies and xor-shifts; pick by key size, trust level and whether the hash is persisted.
›
Rolling hash
data-structures · low: Rabin-Karp polynomial rolling hashes and winnowing for substring fingerprints and document matching
Swiss table
data-structures · low: Open-addressing hash table that filters 8-16 slots at once with 1-byte hash tags and SIMD, giving fast lookups at 87.5 % load.
›
Merkle tree
data-structures · low: Hash tree for verifying and diffing large datasets with logarithmic proofs
Segmented log
distributed · low: Split an append-only log into files named by their first offset, write only the newest, and find any record by binary search plus a sparse index.
›
Digital signatures (Ed25519)
security · low: Small, fast, deterministic public-key signatures that prove who produced a message; the default for tokens, releases and protocols.
›
Trusted timestamping
security · low: RFC 3161 time-stamp tokens: a TSA signs a hash with time, proving data existed then
Bit packing and PFOR
compression · low: Store blocks of integers with exactly b bits each and patch rare outliers separately (PFOR); the fastest integer codec family, billions of values per second.
›
Delta encoding
compression · low: Store differences between consecutive values instead of the values, turning sorted IDs, timestamps and counters into small numbers that pack into few bits.
›
Dictionary encoding
compression · low: Map values to small integer codes via a dictionary for compact, comparable columns
Zone maps
storage · low: Per-block min/max (and sparse primary) indexes to skip data during scans
Union-find
graphs · low: Disjoint-set forest with union by size and path compression; merges sets and answers same-set queries in effectively constant time.
›
Linear and logistic regression
machine-learning · low: Fit a weighted sum of features to a number (least squares) or a probability (logistic); the baseline every model must beat.
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Fuzzy string matching
search-sort · low: Edit distance, Jaro-Winkler and trigram indexes for approximate name and address matching
Varint (LEB128)
compression · low: Variable-length integers in 7-bit groups with a continuation bit; small numbers take 1 byte, the wire format of Protobuf, WebAssembly and DWARF.
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BM25 ranking
search-sort · low: The standard lexical relevance score: IDF-weighted term frequency with saturation (k1) and length normalization (b); default in Lucene, Elasticsearch and SQLite FTS5.
›
Sorted-list intersection
search-sort · low: Intersect sorted id lists by merging, galloping from the short list into the long one, and skipping whole compressed blocks, shortest list first.
›
Agent loop
agentic-ai · unknown:
Constrained decoding
agentic-ai · low: Force LLM output to match a regex, JSON schema or grammar by masking, at every step, the tokens that would leave the language.
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Tool calling
agentic-ai · low: The model emits a structured call (id, name, JSON arguments) instead of prose; your code validates, runs it and returns a result tagged with the same id.
›
Reference counting
compilers · low: Keep a count of owners in each object, free it when the count hits zero; deterministic and local, but pays on every copy and leaks cycles.
›
False sharing
concurrency · low: Independent variables written by different cores on one cache line force the line to bounce between cores; pad or regroup hot data to fix it.
›
Merkle dag
data-structures · low: Content-addressed DAG of hashed nodes (git trees/commits) for dedupe and verifiable history
Radix trie
data-structures · low: Compressed prefix tree for path routing, domain matching and prefix lookups
Fencing tokens
distributed · low: A number that grows with every lock grant and is checked by the protected resource, so a paused ex-holder's late write is rejected.
›
BFS and DFS
graphs · low: The two basic graph traversals; BFS gives hop distances and levels, DFS gives discovery/finish order for cycles, components and topological order.
›
Atomic file replacement
hardware-os · low: Write temp file, fsync, rename over target, fsync directory: crash-safe whole-file updates
CPU caches and the memory hierarchy
hardware-os · low: Sizes, line widths and latencies of L1/L2/L3/DRAM on modern x86 and Apple M-series, and the data-layout rules that follow from them.
›
CRC32C checksums
hardware-os · low: The Castagnoli CRC-32 with dedicated instructions on x86 (SSE4.2) and ARMv8. It is the standard fast integrity check for storage blocks, logs and network frames.
›
fsync, O_DSYNC and O_DIRECT
hardware-os · low: What fsync, fdatasync, O_DSYNC, O_DIRECT and F_FULLFSYNC really guarantee on Linux and macOS, and the exact call sequences for crash-safe files.
›
Byte-pair encoding (BPE) tokenizati…
machine-learning · low: Learn a subword vocabulary by repeatedly merging the most frequent adjacent pair; byte-level BPE encodes any input losslessly with 32k-200k tokens.
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Loss functions
machine-learning · low: The scalar a model minimizes: cross-entropy for classes and tokens, MSE or Huber for values, each with a stable form and simple gradient.
›
Text chunking
machine-learning · low: Cut documents into token-bounded pieces along structure boundaries, keeping offsets and section paths, so each piece embeds well and can be cited.
›
Text normalization
machine-learning · low: Rewrite messy text into one canonical form for matchers and models, or into spoken words for speech output (and back), keeping a map to the original offsets.
›
AdamW
ml-training · low: Adam's per-parameter adaptive steps with weight decay applied directly to the weights; the default optimizer for transformers and LLM pretraining.
›
Paged KV cache
ml-training · low: Store each sequence's attention keys/values in fixed-size blocks mapped through a block table, like virtual memory pages; near-zero fragmentation and copy-on-write sharing.
›
Reverse-mode automatic differentiat…
ml-training · low: Record the forward computation on a tape, then sweep it backwards once to get the gradient of a scalar loss for all inputs.
›
Transformer block
ml-training · low: The decoder-only pre-norm block (attention plus MLP on a residual stream) behind every modern LLM, with exact shapes, parameter, FLOP and KV-cache counts.
›
Json rpc
networking · low: JSON-RPC 2.0 requests, notifications and batching
L-BFGS
numerics · low: Quasi-Newton minimizer that approximates the inverse Hessian from the last m gradient differences via the two-loop recursion; O(m·n) memory and work per step.
›
LU and Cholesky factorization
numerics · low: Factor A = PLU (any square matrix, partial pivoting) or A = LLᵀ (SPD) once in O(n³), then solve each right-hand side in O(n²).
›
Sparse matrices (CSR)
numerics · low: Compressed sparse row stores only nonzeros as row pointers, column indices and values; SpMV streams them once, so it is memory-bandwidth bound.
›
Finite state transducer
search-sort · low: Minimal acyclic FST mapping sorted keys to values; compact term dictionaries with prefix/fuzzy search
Top-k selection
search-sort · low: Keep the k best of n items without sorting all n - bounded min-heap for streams, quickselect for arrays, threshold pruning to skip most items.
›
Unicode text tokenization for search
search-sort · low: Turn multilingual text into index terms: segment words (UAX 29 style, CJK bigrams), normalize, case-fold and accent-fold, identically at index and query time.
›
Cryptographic hashes (SHA-2, BLAKE3)
security · low: Collision-resistant fingerprints of data; SHA-256 for interoperability, BLAKE3 for speed, HMAC/HKDF for keyed uses.
›
Csprng
security · low: OS-backed cryptographically secure random numbers (getrandom), and when a fast PRNG is not enough
JSON Schema validation
security · low: Compile a JSON Schema once, then check every untrusted document against it, within hard size and depth limits, and report failures as JSON Pointers.
›
Optimistic concurrency control
storage · low: Run transactions without locks, record what they read, and validate at commit that nothing changed; fastest when conflicts are rare.
›
Hierarchical state machine
systems · low: Nest states so a substate inherits its parent's reactions and only overrides what differs, with ordered entry and exit actions along the path.
›
LRU and CLOCK
systems · low: LRU evicts the least recently used entry via hash map plus linked list; CLOCK approximates it with a reference bit, so hits take no lock.
›
Slab allocator
systems · low: Pre-carve pages into equal-size slots per size class with an in-place free list: O(1) alloc and free, no external fragmentation, cache-warm reuse.
›
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