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Agentic Coding Is Creative Destruction, Not a Trap
Agentic coding is not a trap. It is creative destruction: a production shift that will expose bad process, change expertise, and expand who can build software.
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Research notes, release essays, and field reports on turning messy information into useful operating judgment.

Start Here
Agentic coding is not a trap. It is creative destruction: a production shift that will expose bad process, change expertise, and expand who can build software.
Read the featureLatest
Recent research reads, product release notes, and practical essays from the work.
WACCY v0.1.0 is the first released vertical slice of our small-business financial modeling stack: extraction contracts, validated datasets, model builders, and exporters.
GLiNER-Relex extends the GLiNER family into a unified zero-shot NER and relation extraction model.
GraphForge v0.4.0 completed the three-surface architecture: Cypher execution, graph algorithms, and hybrid search.
GraphForge v0.3.10 made the engine easier to integrate with analytical and agentic graph workflows.
GraphForge v0.3.9 kept full TCK compliance while delivering performance improvements across the stack.
GraphForge v0.3.8 reached 100% openCypher TCK compliance with 3,885 of 3,885 scenarios passing.
GraphForge v0.3.7 expanded function coverage and moved reported TCK compliance to 3,235 of 3,885 scenarios.
GraphForge v0.3.6 was a correctness release that moved TCK coverage from 1,694 to 2,507 passing scenarios.
GraphForge v0.3.5 added sqrt, rand, pow, aggregation test fixes, and missing TCK step definitions.
GraphForge v0.3.4 filled in operator and string-function gaps, raising reported feature completeness to 92%.
GraphForge v0.3.3 pushed deeper into expressive graph queries with pattern predicates, CALL subqueries, and pattern comprehension.
GraphForge v0.3.2 completed list functions, adding filter, extract, and reduce with proper scoping and NULL handling.
GraphForge v0.3.1 completed predicate functions and improved NULL-aware list and property testing.
GraphForge v0.3.0 was a major query-language release that substantially expanded openCypher compatibility.
DOREMI focuses on the deployment problem of rare relation performance rather than proposing another relation model.
GraphForge v0.2.1 made it easier to start analysis quickly by adding cached loading for real-world SNAP graph datasets.
GraphForge v0.2.0 moved the query language from early capability toward practical core Cypher coverage.
GraphForge v0.1.4 made the project faster to iterate on by moving coverage feedback and test analytics closer to the developer.
GraphForge v0.1.2 focused on the professional project infrastructure needed for a graph database to mature in public.
CoDe-KG treats scientific KG construction as a pipeline of coreference, simplification, decomposition, and relation extraction.
GRAPHTREX uses span extraction and heterogeneous graph transformers to model long-range temporal relations in clinical notes.
KGGen pairs an LLM text-to-KG pipeline with a benchmark focused on graph usefulness.