Notes from the gmware team.
Practical writing on building and shipping software: what it costs, how to buy it, and how to get it right. From the engineers who do the work.
AI Automation Agency: A Proof-First Selection Guide
Choose an AI automation agency by testing one real task, its failure path, permissions, monitoring, and handoff before you buy a polished demo.
Automation Risk Assessment: A Control-by-Control Review
Assess automation risk across access, data, decision error, change, availability, monitoring, rollback, and ownership with a usable risk register.
Cloud Strategy Consulting: Fit and Non-Fit Guide
Use this fit scorecard to decide when cloud strategy consulting is warranted, what it should deliver, and when a focused engineering task is enough.
Data Integration Consulting: Who Owns the Pipeline Later?
Choose in-house, consulting, managed operations, or build-operate-transfer for data integration by change rate, business criticality, and ownership.
AI Agent Evaluation: Build a Release Gate That Can Say No
Turn AI agent evaluation into a release decision with production-shaped cases, outcome checks, repeated trials, severity gates, and named owners.
Prompt Injection Testing: A Release Gate for AI Agents
Test direct and indirect prompt injection across retrieval, tools, memory, and approvals. Use paired cases and side-effect evidence before release.
AI Integration Services: Put the Boundary in the SOW
Buy AI integration services with a system boundary, permission map, failure replay, acceptance record, operating evidence, and an exit-ready handoff.
LLM Development Company: Scope the Application, Not the Model
Hire an LLM development company against acceptance evidence: eval cases, model-change tests, security boundaries, operating records, and handoff assets.
Software Architecture Consulting: Buy a Decision, Not a Diagram
Software architecture consulting should settle an expensive design choice with constraints, tradeoffs, proof, and a migration sequence. Use this acceptance brief.
Technical Due Diligence: Test the Claims Behind the Deal
Technical due diligence should connect product claims to code, operations, ownership, and repair cost. Use this evidence matrix before a software deal closes.
AI Agent Audit: Reconstruct Every Material Action
An AI agent audit needs versions, permissions, inputs, tool calls, approvals, target responses, and recovery evidence. Build the packet before an incident.
AI Compliance Consulting: Buy Evidence, Not a Badge
AI compliance consulting should map applicable requirements to systems, controls, owners, and evidence. Use this traceability record before hiring.