Roadmap

Version 0.1.0 · Goal: a developer who tries DDK for fifteen minutes finds three things they cannot get from a base_url and two headers — and one of them saves them from a production incident.

The shared governed transport and the capabilities that hang off it: typed refusals, budget & pacing, the local simulator, simulate() and the conformance suite, OpenTelemetry GenAI spans, correlation IDs and cost tags. Plus a deep LangGraph adapter, connection_kwargs() for seven more frameworks, the decorators and CLI, the documentation site, and the PyPI release. Closing out the phase: steering the gateway’s semantic cache and surfacing cache hits and semantic-routing matches on last_call.

Version 0.2.0 · Goal: capabilities no generic LLM client offers, because they depend on the platform behind the gateway.

Governed tool access (MCP discovery and binding), A2A serve / expose / dev, on-behalf-of identity, human-in-the-loop, scan & publish to the registry with a GitHub Action, declarative refusal handlers and a classification registry for custom policies, typed federated guardrail verdicts, kill-switch awareness with the kill reason, and a second deep framework adapter chosen by demand.

Around them: an inbound correlation ID carried across MCP and A2A hops, a stated concurrency contract for budget and telemetry under parallel fan-out, a per-request business group for shared multi-tenant clients, bring-your-own provider keys, and a token and registry cache. Also in this phase: governed access to TypeSafe Jev , a System One decision model, with the same typed refusals, spans, budget and simulator support as LLM calls, plus worked patterns for confidence-gated review, tool ranking and budget-aware routing.

Version 0.3.0 · Goal: agents that know the rules before they call, not only after they are refused.

The policy handshake (read the in-force policy set, advisory only), policy updates pushed to the code at run boundaries, a governed structured-output path, a model catalog with honest model resolution, evaluation hooks on the run span, monetary spend and wallet warnings, custom cost dimensions, and run-level cost rollups. Much of this phase depends on new gateway endpoints tracked under Upstream gaps.

Version 0.4.0 · Goal: everything a security, compliance and platform team asks for before rolling DDK out broadly.

Independent security review and supply-chain hardening, a latency and overhead budget enforced in CI, a full pass over every error message, the public API contract and deprecation policy, compliance evidence mapping (EU AI Act Art. 12, ISO 42001, OWASP LLM Top 10), log shipping, data residency, workload identity, air-gapped operation, opt-in gateway failover, a clear boundary against the platform’s infrastructure-as-code, and a support model with a release cadence.

Version 1.0.0 · Goal: a stable, multi-language SDK with guarantees.

A TypeScript port of the core capabilities with conformance scenarios shared across Python and TypeScript, the remaining framework adapters brought to the full bar by demand, framework-docs partnerships and launch channels, and the 1.0 release with stability guarantees.

Every endpoint, header, class name and constructor argument DDK relies on is checked against the real platform and the installed framework packages before features are built on it.

Requests to the Omni Gateway team for platform capabilities DDK needs — such as a budget-query endpoint, policy discovery, a dry-run mode and richer guardrail verdicts. They land whenever the gateway ships them.