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  1. September 22, 2026Agents are stupidAn agent does not think, does not remember, and should not be the thing your people talk to. Three ways the technology is dumber than the demo suggests, with the research behind each, and the design that turns it into work you can trust at scale.Business leaders11 min read · Eric Tarnowski
  2. September 17, 2026Enterprise AI? It's all about the harnessWriting an agent loop takes an afternoon. The runtime around it, which decides what an agent may see and do, what survives a failure, and who approves what, is where enterprise programs stall. Pyrana built that runtime once, so that building an application is configuration of agents and workflows rather than a rebuild of the fundamentals.AI and data leaders10 min read · Sam Merkovitz
  3. September 14, 2026Agents lose control when nothing outside the model says noThe Hugging Face intrusion and the calls to pace the frontier are about what a model can do when nothing outside it enforces a boundary. Enterprise agents do not have to run that way. Here is what bounded agents look like, and what we did in the platform to keep the boundary out of the model's hands.AI and data leaders10 min read · Sam Merkovitz
  4. September 9, 2026My AI pilots keep failing. Now what?Most AI pilots are scoped so the demo works, which is why they die in the security review. A production-first pilot answers identity, approval, and audit on day one, and the five questions to ask before you fund the next one.Business leaders7 min read · Eric Tarnowski
  5. September 2, 2026Workflows aren't enough: why knowledge is the moatOrchestration is mostly solved. What is not solved is an agent that knows what the business knows and can prove where each claim came from. Here is what a context unit has to carry, how retrieval should account for it, and what to ask of any context layer.Engineers and architects8 min read · Eric Tarnowski
  6. August 26, 2026Component build vs. platform: what you actually have to build below the waterlineThe agent demo is a model, a prompt, and a few tools. Production is authorization, tenancy, durable execution, approval policy, idempotent effects, audit, secrets, and versioned configuration. Here is what each one costs to build, and how we handle it.AI and data leaders8 min read · Eric Tarnowski
  7. August 19, 2026Approval is a policy, not a booleanA per-tool approval flag approves the tool, not the call. Here is what breaks in production and the design that holds: policy over typed arguments, a frozen invocation, one obligation per lane, revalidation before dispatch, and idempotent effects.Engineers and architects7 min read · Eric Tarnowski
  8. August 12, 2026Governance is not a dashboardControl towers inventory and observe agents. They do not decide whether a specific call may run. The difference between governance above the system and governance in the path of the call, and what to ask a vendor to prove which one they have.AI and data leaders6 min read · Eric Tarnowski
  9. August 5, 2026Digital workers need a manager, not a chatbotAn agent needs what a new hire needs on day one: an identity, scoped access, a spending limit, an approver, a reviewer, and a record. Most companies gave it a chat window instead. Here is the job description for your first digital worker.Business leaders7 min read · Eric Tarnowski
  10. July 29, 2026Twelve agents, twelve permission modelsAgent sprawl is an identity problem before it is a coordination problem. Every vertical tool arrives with its own identity model, permission semantics, and audit format. Here is what governed agent identity looks like, and an inventory exercise for this quarter.AI and data leaders6 min read · Eric Tarnowski
  11. July 22, 2026One operation, five doorsThe same business action reaches your system through a UI, a chat assistant, an API, an MCP tool, and a nightly schedule. If each door grows its own permission check, policy drifts. Define the operation once, compile it, and admit every caller the same way.Engineers and architects8 min read · Eric Tarnowski
  12. July 15, 2026The tenth application is the one that mattersPoint solutions, suite extensions, cloud agent stacks, and application platforms all get one agent live. They diverge at the tenth application and the first incident. How to evaluate vendors for app number ten, and what to put in the RFP.Business leaders7 min read · Eric Tarnowski
  13. October 6, 2025Beyond the Hype: Why OpenAI's Agent Builder Falls Short – And How Pyrana Builds Real Agentic SolutionsOpenAI’s Agent Builder is great for demos—but brittle in production. Here’s why prototypes fail and how Pyrana’s full‑stack, context‑driven approach delivers reliable enterprise value.AI and data leaders5 min read · Ankur Garg
  14. August 25, 2025Orchestration is Not Enough: Why Enterprises Need Agentic ApplicationsMulti-agent orchestration is the next frontier, but orchestration alone isn't enough. Enterprises need complete, production-grade agentic applications that bridge the gap between powerful workflows and business-ready solutions.Business leaders8 min read · Eric Tarnowski
  15. August 18, 2025Closing the Gaps Between AI Capability and Enterprise ValueEvery new model promises everything. Every demo looks like magic. But demos don't translate to enterprise value. Here are the five gaps that kill AI projects – and how to close them.Business leaders4 min read · Sam Merkovitz
  16. August 18, 2025Why We Built Our Own Orchestration Platform vs. Using LangChain, CrewAI, etc.LangChain and CrewAI are great for prototypes, but enterprises need more. Here's why we built Pyrana from scratch instead of wrapping existing frameworks – and why production AI needs different infrastructure than demo AI.Engineers and architects5 min read · Sam Merkovitz
  17. July 22, 2025The Context Unit Blueprint: Architecture, Validation & Graph Retrieval in PyranaMy previous post introduced the idea of Context Units - this is the blueprint. Dive deep into the schema, lifecycle, and engine that powers Pyrana's context-first AI architecture.Engineers and architects12 min read · Jamey Canterbury
  18. July 22, 2025Context EfficiencyHow Context Units (CxUs) maximize knowledge density per token, making LLM reasoning traceable and auditable while transforming messy documents into modular, queryable facts.Engineers and architects8 min read · Jamey Canterbury
  19. July 9, 2025Data Without Context is UselessEnterprises spend over $200 billion on analytics, yet half of collected data goes unused. The problem? Data without context is inert. Here's how Context Units solve the crisis.AI and data leaders8 min read · Eric Tarnowski
  20. June 9, 2025The "Illusion of Thinking" and Why I'm All-In on Orchestrated AIApple's ML Research just exposed the limits of reasoning models. Here's why that validates everything we've been building at Pyrana – and why orchestration beats monolithic AI every time.AI and data leaders7 min read · Sam Merkovitz