HashiCorp vs Speakeasy
Side-by-side trajectory, velocity, and editorial themes.
HashiCorp under IBM is doubling down on agentic IAM and enterprise-scale Terraform.
Now branded 'IBM Vault' in places, HashiCorp is rolling out its post-acquisition strategy on two fronts: native identity management for AI agents in Vault, and a coordinated Terraform refresh spanning 1.15, Enterprise 2.0, and Infragraph-powered HCP in public preview. Recent capability adds across Vault (envelope encryption for streaming workloads, Azure hub-and-spoke GA) and Terraform (cost visibility, project-level notifications) progress the existing surface while the strategic bets ship in parallel.
Two arcs are clearly pulling: Vault is repositioning as the identity plane for the AI-agent era — issuing, delegating, and tracing credentials for non-human actors — and Terraform is being reorganized around enterprise-scale governance with a single-source-of-truth graph (Infragraph) underneath HCP. The 'AI operating model' marketing layer signals that IBM and HashiCorp are telling enterprise buyers AI is now an operations problem, not an experimentation problem, and HashiCorp is the substrate to operationalize it on.
The AI-agent IAM story is the one to expand fastest — agent-policy primitives, OIDC-for-agents, tighter integration with Vault Secrets Operator and Boundary. On the Terraform side, Infragraph graduating from public preview is the next milestone to watch, and likely the moment 'HCP Terraform powered by Infragraph' replaces classic HCP Terraform as the default.
Speakeasy's Gram is shipping daily — multi-MCP chat, Codex hooks, and long-running assistants in one week.
Speakeasy's Gram platform is moving at multiple-releases-per-day cadence across two trains. The Platform train has shipped issuer-gated OAuth from the playground, release-stage badges, OpenRouter credit monitoring with auto-reconciliation, a v2 assistant runtime foundation, hook telemetry attribution in Datadog, Codex (OpenAI) hooks support, OTEL forwarding to customer destinations, Slack Block Kit with interactive replies, and a full migration to WorkOS-native auth. The Elements train added multi-MCP server chat configuration with namespaced tool merging, and a resilience fix so a failing MCP server doesn't wipe out tools from healthy ones in the same chat. Long-running assistants gained token-aware context compaction, self-wake triggers, and long-term memory via vector embeddings.
Gram is being built as an MCP-native assistant platform — every release reads like infrastructure for assistants that compose many MCP servers, run for a long time, recover from failures, and integrate with enterprise auth and telemetry. The architectural choices (multi-MCP merging with namespacing, per-assistant Fly apps, OTEL forwarding, WorkOS) say the target buyer is a platform team building real production agents, not a tinkerer. Self-healing chat history, credit-exhaustion 402 responses, and per-server failure isolation are the kinds of features that only matter at scale — Speakeasy is building for that scale already.
Expect Gram to formalize its v2 assistant runtime in the next sprint, add usage-based pricing tied to OpenRouter credits and Fly machine-hours, and ship deeper MCP server lifecycle tooling (version pinning, canary deploys for new tool versions). A managed MCP server catalog is a plausible adjacency given how much of the platform already presumes multi-MCP composition.
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